US011185241B2

( 12 ) Ahmed
Unitedet alStates
.
Patent ( 10) Patent No.: US 11,185,241 B2
(45 ) Date of Patent : Nov. 30 , 2021
( 54 ) CONTINUOUS HEART RATE MONITORING ( 58 ) Field of Classification Search
AND INTERPRETATION CPC . A61B 5/02405 ; A61B 5/024 ; A61B 5/02438 ;
A61B 5/0205 ; A61B 5/6824 ; A61B
( 71 ) Applicant: Whoop , Inc. , Boston , MA (US ) 5/6813 ; A61B 5/681 ; A61B 5/721
USPC 600/508
( 72 ) Inventors : William Ahmed , Boston, MA (US ); See application file for complete search history.
John Capodilupo , Boston , MA (US ) ; (56 ) References Cited
Aurelian Nicolae , Brookline, MA (US)
2

U.S. PATENT DOCUMENTS

( 73 ) Assignee : WHOOP, INC . , Boston, MA (US )
4,192,000 A * 3/1980 Lipsey A61B 5/22
( * ) Notice : Subject to any disclaimer, the term of this 250/215
patent is extended or adjusted under 35 4,312,358 A * 1/1982 Barney A61B 5/02438
235/91 H
U.S.C. 154 (b ) by 0 days. ( Continued )
( 21 ) Appl. No .: 14 /198,437 FOREIGN PATENT DOCUMENTS
(22 ) Filed : Mar. 5 , 2014 DE 10313837 10/2004
NL WO 2013038296 A1 * 3/2013 A61B 5/721
( 65 ) Prior Publication Data (Continued )
US 2015/0250396 A1 Sep. 10, 2015
OTHER PUBLICATIONS
(51 ) Int. Cl.
A61B 5/024 ( 2006.01) U.S. Search Authority, “ International Application Serial No. PCT /
A61B 5/00 ( 2006.01 ) US15 / 18803 , Search Report and Written Opinion dated Aug. 12 ,
2015 ” , 11 pages.
(Continued ) ( Continued )
(52) U.S. Cl .
CPC A61B 5/02405 (2013.01 ) ; A61B 5/024 Primary Examiner Jennifer Pitrak McDonald
( 2013.01 ) ; A61B 5/02416 ( 2013.01 ) ; A61B Assistant Examiner Elizabeth K So
5702427 (2013.01 ) ; A61B 5/02438 ( 2013.01 ) ; (74 ) Attorney, Agent, or Firm Strategic Patents, P.C.
A61B 5/681 ( 2013.01 ) ; A61B 5/6824 (57) ABSTRACT
(2013.01 ) ; A61B 5/7278 ( 2013.01 ) ; A61B
5/742 (2013.01 ) ; A63B 71/06 ( 2013.01 ) ; G06F Disclosed herein is a device for continuous physiological
1/163 ( 2013.01 ) ; G06F 1/3206 ( 2013.01 ) ; monitoring as well as systems and methods for interpreting
G16H 20/30 (2018.01 ) ; G16H 40/67 data from such aa device . The device may support intelligent
( 2018.01 ) ; A61B 5/0004 (2013.01 ) ; A61B selection from among two or more different modes for heart
5/0022 (2013.01 ) ; A61B 5/01 (2013.01 ) ; A61B rate detection . In addition, the acquisition of continuous
5/053 (2013.01 ) ; A61B 5/11 (2013.01 ) ; A61B physiological data facilitates automated recommendations
concerning changes to sleep , recovery time, exercise rou
5/4806 (2013.01 ) ; A61B 5/4866 ( 2013.01 ) ; tines and the like.
A61B 5/6898 ( 2013.01 ) ;
(Continued ) 20 Claims , 30 Drawing Sheets
Step
X2 Emit light veing light onuitsers toward user's skin
Stco Detect light reílected from user's in using light derectors
904
Step
9036 Pre -process signals associated with reflected right
Step
08 Esecide peak clevection algorithm detect peaks in pre-processed signals
Sto )
910 Deteorite n & Rioterval beged on detected peaks
Store
112 Determine conídance level asociated with RR inicrva !
Ster
914
Vas Confidence No
level >
Threshold ?

Step lise detected peaks to deternine Execute frecieacy analysis algoriilin to

916 instantaneous heart rato ucina ostaotanuous heart rate taxed SIT
a poe- proxosso signus associated witb 920
cb10ct lgbt
Stoo Determine heart rate variability
918
Step
Determine heari. rate variability 972
 US 11,185,241 B2
Page 2

( 51 ) Int . Ci . 2012/0053471 Al 3/2012 Aarts et al .

GOOF 1/3206 ( 2019.01 ) 2012/0190948 A1 7/2012 Vetter et al .
2012/0271121 A1 * 10/2012 Torre A61B 5/0059
GOOF 1/16 (2006.01 ) 600/301
G16H 20/30 ( 2018.01 ) 2012/0283855 A1 11/2012 Hoffman et al .
G16H 40/67 ( 2018.01 ) 2013/0303837 A1 * 11/2013 Berka A61M 21/02
A63B 71/06 ( 2006.01 ) 600/28
A61B 5/053 ( 2021.01 ) 2014/0213858 A1 7/2014 Presura et al .
A61B 5/01 2014/0350356 A1 11/2014 Ahmed et al .
( 2006.01 ) 2015/0238146 A1 8/2015 Renevey et al .
A61B 5/11 ( 2006.01 ) 2015/02 50385 A1 9/2015 Ahmed et al .
(52) U.S. CI. 2015/0251074 A1 9/2015 Ahmed et al .
CPC A61B 2560/0443 (2013.01 ) ; A63B
2071/0694 (2013.01 ) FOREIGN PATENT DOCUMENTS
References Cited WO WO - 2013038296 3/2013
(56) WO WO - 2015134654 9/2015
U.S. PATENT DOCUMENTS
OTHER PUBLICATIONS
5,228,449 A 7/1993 Christ et al.
5,749,366 A * 5/1998 Odagiri A61B 5/024 USPTO , “ U.S. Appl. No. 14 /290,065 , Preinterview First Office
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6,527,711 B1 3/2003 Stivoric et al. Action dated Nov. 13 , 2017” , 8 pages .
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7,805,186 B2 9/2010 Pulkkinen et al . USPTO , “ U.S. Appl. No. 14/ 290,065 Final Office Action dated Sep.
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8,021,306 B2 9/2011 Martikka et al . WIPO , “ International Application Serial No. PCT/US15 / 18803 ,
8,036,842 B2 10/2011 DeVaul et al . International Preliminary Report on Patentability dated Sep. 15 ,
8,052,580 B2 11/2011 Saalasti et al. 2016 ” , 8 pages.
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8,463,577 B2 6/2013 Yuen et al. Additional Fees with Partial Search Report dated Dec. 16 , 2013 ” , 7
8,494,829 B2 7/2013 Teixeira Pages .
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2005/0054940 A1 3/2005 Almen et al . Jul . 1 , 2019 ", 12 pages.
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600/485 Jun. 21 , 2019 ” , 8 pages .
2005/0245793 A1 * 11/2005 Hilton A61B 5/0002 USPTO , “ U.S. Appl. No. 14/ 289,330 Final Office Action dated Feb.
600/300 1 , 2021" , 11 pages.
2008/0055074 Al 3/2008 Gao et al . USPTO , “ U.S. Appl. No. 14/ 290,065 Non - Final Office Action dated
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2009/0099462 A1 4/2009 Almen et al . 16, 2020 " , 8 pages.
2009/0195350 A1 * 8/2009 Tsern GOOF 1/1626 USPTO , “ U.S. Appl. No. 14/ 289,330 Non - Final Office Action dated
340/ 3.1 May 19 , 2020 " , 10 pages.
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600/485 Aug. 9 , 2021" , 16 pages .
2012/0004519 A1 1/2012 Nazarian et al .
2012/0022384 Al 1/2012 Teixeira * cited by examiner
U.S. Patent Nov. 30 , 2021 Sheet 1 of 30 US 11,185,241 B2

? ••••

FIG . 1
U.S. Patent Nov. 30 , 2021 Sheet 2 of 30 US 11,185,241 B2

124

102

108
170 12:30
00:00 106

o FC 98

FIG . 2
U.S. Patent Nov. 30 , 2021 Sheet 3 of 30 US 11,185,241 B2

PHASE 1

102
108 106
124

PHASE 2

12:30 170
00:00

PHASE 3

HO 121 G OS
FIG . 3
U.S. Patent Nov. 30 , 2021 Sheet 4 of 30 US 11,185,241 B2

124

TURN RIGHT AND DISPLAY

RELEASE HEART RATE

108

108
DE 0

FIG . 4
U.S. Patent Nov. 30 , 2021 Sheet 5 of 30 US 11,185,241 B2

FIG . 5

-610
MEMORY
600 614
NETWORK
INTERFACE

608 612 616

PROCESSOR BUS INTERFACE

602 604
SENSORS BATTERY

STORAGE

FIG . 6
U.S. Patent Nov. 30 , 2021 Sheet 6 of 30 US 11,185,241 B2

100

706
702

FIG . 7A

704 102
702 706

FIG . 7B
U.S. Patent Nov. 30 , 2021 Sheet 7 of 30 US 11,185,241 B2

104
812
802 102

806 810
804 808

FIG . SA

104

826
820 824

FIG . 8B
U.S. Patent Nov. 30 , 2021 Sheet 8 of 30 US 11,185,241 B2

Step
902 Emit light using light emitters toward user's skin
Step Detect light reflected from user's skin using light detectors
Step
Pre - process signals associated with reflected light
Step
Execute peak detection algorithm to detect peaks in pre -processed signals
Step
910 Determine an RR interval based on detected peaks
Step
912 Determine contidence level associated with RR interval

Step
Confidence
Yes level No
Threshold ?

Step Use detected peaks to determine Execute frequency analysis algorithm to

instantaneous heart rate determine instantaneous heart rate based Step
on pre -processed signals associated with 920
Step reflected light
Determine heart rate variability
3
3
Determine heart rate variability Step
922

FIG . 9
U.S. Patent Nov. 30 , 2021 Sheet 9 of 30 US 11,185,241 B2

Step 1002 Convert heart rate readings into heart rate reserve values

Step 1004 Weight heart rate reserve values according to weighting scheme

Step 1006 Sum and normalize weighted time series of heart rate reserve values

Step 1008 Scale summed and normalized values to generate intensity score

Step 1010 Store intensity score on non - transitory computer-readable storage medium

Step 1012 Display intensity score on user interface rendered on display device

FIG . 10
U.S. Patent Nov. 30 , 2021 Sheet 10 of 30 US 11,185,241 B2

Step
Determine heart rate variability based on continuous heart rate data
Step Generate and display iotensity score
1104
Step
Generate and adjust an exercise routine based on intensity score
Step
1108 Generate and display a recovery score
Step
Yes
Recovery No
score > First
threshold ?

Step
Step Recovery
1112 Indicate that user is exercise- ready
Score
No Second
threshold?

Yes

Step Indicate that user may exercise with Indicate that user is not exercise -ready
care

FIG . 11
U.S. Patent Nov. 30 , 2021 Sheet 11 of 30 US 11,185,241 B2
21
MAXIMUM ALL
OUT
020
019
NEAR MAXIMAL
018
017
VERY HARD 19.0
WORKOUT
016
015
HARD WORKOUT
014

MODERATE
WORKOUT
012
EXAMPLE
LIGHT WORKOUT
MODERATE WORKOUT
010 GOOD INTENSITY FORA
ACTIVE TAPERING WORKOUT . SUBJECT
12.5 DID NOT OVERCOME HIS
09 ANAEROBIC THRESHOLD AND
WILL HAVE LITTLE TO NO
SORENESS TOMORROW .

LIGHT ACTIVITY 07

NO ACTIVITY

02

ASLEEP
FIG . 12
U.S. Patent Nov. 30 , 2021 Sheet 12 of 30 US 11,185,241 B2

HEART RATE
VARIABILITY
RESTING HEART RATE %
SLEEP QUALITY 33 %
66 %
RECENT STRAIN
(PHYSICAL &
PSYCHOLOGICAL)
FIG . 13
(A )
HEART RATE
VARIABILITY RECOVERY
RESTING HEART RATE SCORE
SLEEP QUALITY TACTICAL ATHLETE HAS
18 % NOT RECOVERED FROM
RECENT STRAIN C RECENT STRAIN AND
( PHYSICAL & MAY NEED REST
PSYCHOLOGICAL
(B)
RECOVERY
2 HEART RATE SCORE TACTICAL ATHLETE HAS
VARIABILITY AVERAGE SLEEP AND
RESTING HEART RATE HRV READINGS
45 % INDICATING HE HAS
PO SLEEP QUALITY MODERATELY
RECOVERED FROM
RECENT STRAIN RECENT STRAIN , HE IS
( PHYSICAL & PREPARED FOR
PSYCHOLOGICAL) ACTIVITY
(C )
RECOVERY
G HEART RATE SCORE
VARIABILITY TACTICAL ATHLETE IS
NEAR FULLY
SSS RESTING HEART RATE RECOVERED AND
SHOWING SIGNS OF
DR SLEEP QUALITY ???????? GOOD FITNESS . HE IS
RECENT STRAIN WELL PREPARED FOR
( PHYSICAL & INTENSE ACTIVITY
PSYCHOLOGICAL )
FIG . 14
U.S. Patent Nov. 30 , 2021 Sheet 13 of 30 US 11,185,241 B2

150

1530 95 bpm 2:15

OMBAERHTUISN 0O
r1512r1510HCAOLURIESBOFSULREN PD 03h
8
:
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15A
.
17.2 5THT,FEBODAY RAWHRD%OFMAX
1S5LE24P
INTESHYSCORE 1520
DAY
150
.

S88TEOARMES 1516 1542

15A FIG
.
FIG 15B
.
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U
U.S. Patent Nov. 30 , 2021 Sheet 14 of 30 US 11,185,241 B2

1536
TIMEIN
ZONE 9MIN0-10
9
%
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MIN 12
MIN 54 MIN
5
FEB 17.2 TODAY
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O

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1590 1592
1545 1 5 4 8 1546 +ADDNOTE

MAXHROF178ISTHEHYIOGHUESRT ,WAYTOPWINFEUOSKHRS RYGIHRENCOTVRUEDSN .IFYOUWBCGARULEONRAITE,LCMTOBAOUWREINRS%OFMAXAT9THEIN0TE-N1SI0TY TOAN18.5AND172.YOUAREGOING INSTHEG:IPRUTIANSINRTSG

ISTHEFS5ET2WE4PS0T ONAT,DIDYOUSDPIAEMTNEAD TMSAOPINTEMRADEL WTLYOREAKSUOTER SATBEOHMNRUDLOEW COFTFEIRHNVOTIECR
I?NSIGHTS
,YOURSELF B?ICY LE YES
."EX RCIS NG
CAUTION RCEONSVIDRGSUFICENTLY FELINGS NOTES
U.S. Patent Nov. 30 , 2021 Sheet 15 of 30 US 11,185,241 B2

150

1530 95 bpm 2:15

OMBAERHTUISN BHCAOLURIES OFSULREN PD

03h
8
:
1514 BUPEDATE 2:0
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0:45
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0:30 MVAWRK
16A
.
FIG
,FEB5THTODAY RAWHRQ%OFMAX
17.2 U
154 0:15
INTESHYSCORE SLE P
DAY
150
.

16A FIG
.
FIG 16B
. STB8AENOALRYMTEISC
MARTINOBERHAUS BASKET L U
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Pbobo ERSONAL FBEODACK 172 TIPS
U.S. Patent Nov. 30 , 2021 Sheet 16 of 30 US 11,185,241 B2

1536
TIMEIN
ZONE 9MIN0-10 80-90
9
% MIN
32
%
MIN 12
54 MIN
18MIN50-60% 5
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.
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TOCSOTMPARESD AWLEVSKG'T S1532 CATLOERPIS 51,2346029426 INTES Y 20.0
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178 112 DAY
7

1590 1592

WwY.M
+ADDNOTE

MAXHROF178ISTHEHYIOGHUESRT ,WAYTOPWINFEUOSKHRS RGIYHRENCOTVRUEDSN .IFYOUWBCGARULEONRAITE %OFMAXAT9THEIN0TE-N1SI0TY TOAN18.5AND17.2.YOUAREGOING

INSTHEG:IPRUTIANSINRTSG
ONAT,DIDYOUSDPIAEMTNEAD ,LCMTOBAOUWREINRS TMSAOPINTEMRADEL WTLYOREAKSUOTER SATBEOHMNRULDOEW COFTFEIRHNVOTIECR
I?NSIGHTS
,YOURSELF
ISTHEFS5ET2WE4PS0T
B?ICY LE YESNO
."EX RCIS NG
CAUTION RCEONSVIDRGSUFICENTLY FELINGS NOTES
U.S. Patent Nov. 30 , 2021 Sheet 17 of 30 US 11,185,241 B2

-150

1518
UB/PEDATE 15 4 12:0
OMBAERHTUISN CHAOLURIESBOFSULRENPD 4,020 DETAILS
LOGOUT
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,FEB5THTODAY
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3:0
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.
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4020 *****

3250 12:0
STORE INTESHYSCORE SLE P
boy
150 50

WDORAKYUT CTINALOKREINS 1562 1564

*

17A FIG
.
FIG .17B
T88SEANALMYTSIC MARTINOBERHAUS BASKET L U
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17
.
FIG
GCPELORSMBPNAL CNRAELTOGIVSYN 156
WPwNANWARwA.w

bobo
FBEODACK 770 10.24k
U.S. Patent Nov. 30 , 2021 Sheet 18 of 30 US 11,185,241 B2

5
3.05K TODAY 15 8
FEB

30
3
31
2
1

wmT e CJANFEBALORIE

TO AL BURN 20.0 16.0 12.0 8.0 4.0 17B

.
FIG
155612
WSTA S LEAKS'TAVG ?RHR STEPS 1 ,5261 364 58

1590 1592 ADDNOTE

HRAT9YOUHADANEAML:V3AT0ED .DMLAOIVTEHMULDNGETH ?MTCDYORHFIN EUSKG -1572 ,MLASOIWVTEHMAULNGTEHTOBEASATPRHESIAFRSULDAY.INYMOVEMUNRT .CRWOENSKIDTUELRY
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OFLHYOUHAD?AT2E3IV0EGPLHMS OFTFCERIHNOVTIECR
YESNO
1*5CA7U0TION
I?NSIGHTS FELINGS NOTES
U.S. Patent Nov. 30 , 2021 Sheet 19 of 30 US 11,185,241 B2

150
60 40 20

152 M/OVIEMNT 1573

OMBAERHTUISN LOGOUT
a
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.
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17.2 ,FEB5THTODAY 1:0
WIMM
STORE INTESHY SCORE SLE P RAWHR 75 25
12:0 AWAVAWAXAWW.VYA.
50

DAY

18A FIG
.
FIG .18B
M A R T I N OB ER H AU S B A S K E T L U
H NAI V
R E S
COMPS
(
)
10
v TDY W O R K U T 1580
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18
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FIG SUMARY MOVE NT 1584
FBEODACK 8:03 TIPS
U.S. Patent Nov. 30 , 2021 Sheet 20 of 30 US 11,185,241 B2

TIMEIN
ZONE 42h
:
02 14h
:
01 07h
:
04 24h
:
01 5
FEB 18.5h TODAY 1578
FEB
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FEB

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/
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18B
FIG
.
AWEVKG'S ?MAXHR 102 AW KE 4.0 2.0
SLE P DURATION
5?
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NOTE+ADD
M,WNLFRHIAEQGSUCHEYTN .GETAOFOBESVEIRTGAIN G
1586 MAXHRISTHEHYIOGHUESRTSFYRELCOERDTEP 158 PWMYORVETUNRYS TSNGOILEHGT'DPS
INSGHT CAUTION YNOCOMENTS
NOTES
U.S. Patent Nov. 30 , 2021 Sheet 21 of 30 US 11,185,241 B2

190

135 bpm 95 opm

6:30
--ADDCOMP 1908
OMBAERHTUISN OUTLOG
VX

OUHNAIMVEBFRUSTGYOFHCAOLURISESBLUERNPD (87)vFOL OWERS

1910 6:15 W
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al
DAVE MIL ER BASKETL 3,28 BUDATPLIREMTAGONDE 5:45 PM
5:30 PM
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WN.AV FIG
19A
.
,FEB5THTODAY RAWHR%OFMAX W www
4:45 PM
?
“
MX S.
4:30
SLE P
TE

150 50
1O-B9ER0HA4USAER CHOFAOLURIESBSULREN DP4,0208:03h
MARTIN BASKETL
UHN.AIVRESITDY DAY
1918
19A FIG
.
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U.S. Patent Nov. 30 , 2021 Sheet 22 of 30 US 11,185,241 B2

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U.S. Patent Nov. 30 , 2021 Sheet 23 of 30 US 11,185,241 B2

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U.S. Patent Nov. 30 , 2021 Sheet 24 of 30 US 11,185,241 B2

210 WIL AHMED

SEEALL
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U.S. Patent Nov. 30 , 2021 Sheet 25 of 30 US 11,185,241 B2

JOHN YBAYER BRYANT

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U.S. Patent Nov. 30 , 2021 Sheet 26 of 30 US 11,185,241 B2

Computing Device
2200
'''''''' ''

Visual Display Processor , 2202

Device , 2218 Core (s), 2204
User
Interface Memory, 2206
2220
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interface, 2208
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Device , 2222 Pointing
WWW .
Device , 2210 JULOODU

Network
Storage, 2224 Interface, 2212
5

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2214
Data Storage 000.000.000.0

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Processor (s), 2202 }

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FIG . 22
U.S. Patent Nov. 30 , 2021 Sheet 27 of 30 US 11,185,241 B2

DISTRIBUTED 2300
SYSTEM
2302
COMPUTER SYSTEM 2312 2304
MEMORY SYSTEM

2310 2314 2316

PROCESSOR BUS INTERFACE 2308
NETWORK

2318 2306
SYSTEM
STORAGE

FIG . 23
U.S. Patent Nov. 30 , 2021 Sheet 28 of 30 US 11,185,241 B2

2400

Server , 2404
DUUUUUUUUUU

Client, 2406

Network, 241010000

Client , 2408

Server, 2402

FIG . 24
U.S. Patent Nov. 30 , 2021 Sheet 29 of 30 US 11,185,241 B2

2500

PROVIDE STRAP WITH SENSOR AND

HEART RATE MONITORING SYSTEM
2502

DETECT SIGNAL FROM SENSOR

2504

DETERMINE CONDITION OF HEART

RATE MONITORING SYSTEM
2506

SELECT MODE BASED ON CONDITION

2508

ONTINU
STORE CONTINUOUS HEART RATE
DATA
2510

FIG . 25
U.S. Patent Nov. 30 , 2021 Sheet 30 of 30 US 11,185,241 B2

2600

MONITOR DATA FROM

WEARABLE SYSTEM
2602

DETECT EXERCISE ACTIVITY

2604

GENERATE ASSESSMENT OF
EXERCISE ACTIVITY
2606

DETECT RECOVERY STATE

2608

GENERATE ASSESSMENT OF
RECOVERY STATE
2610

ANALYZE ASSESSMENTS
2612

GENERATE RECOMMENDATION
2614

FIG . 26
 US 11,185,241 B2
1 2
CONTINUOUS HEART RATE MONITORING a recovery score ). These indicators or scores may be dis
AND INTERPRETATION played to assist a user in managing the user's health and
exercise regimen .
RELATED APPLICATIONS In one aspect , a device includes a strap shaped and sized
5 to fit about an appendage , a heart rate monitoring system
This application is related to U.S. Provisional Patent coupled to the strap and configured to provide two or more
Application No. 61 / 696,525 , filed Sep. 4 , 2012 , U.S. Pro different modes for detecting a heart rate of a wearer of the
strap , a sensor coupled to the strap , a memory, and a
visional Patent Application No. 61 / 736,310 , filed Dec. 12 , processor
2012 , U.S. patent application Ser. No. 14 / 018,262 , filed Sep. 10 configured coupled
to sense
to the strap . The processor may be
a condition based on a signal from the
4 , 2013 , and International Application No. PCT /US2013/ sensor and to select one
058077 , filed Sep. 4 , 2013. The entire contents of each of the for detecting the heart of the two or more different modes
rate based on the condition . The
aforementioned applications are incorporated herein in their processor may be further configured to operate the heart rate
entirety by reference. monitoring system to obtain continuous heart rate data using
BACKGROUND 15 one of the two or more different modes and to store the
continuous heart rate data in the memory .
Implementations may have one or more of the following
There is an increasing demand for health and fitness features. The condition may be an accuracy of heart rate
monitors and methods for providing health and fitness detection determined using a statistical analysis to provide a
monitoring . Monitoring heart rate , for example , is important 20 confidence level in the accuracy. The processor may be
for various reasons . Monitoring heart rate is critical for configured to select a different one of the modes when the
athletes in understanding their fitness levels and workouts confidence level is below a predetermined threshold . The
over time . Conventional techniques for monitoring heart rate different one of the modes may employ a frequency domain
have numerous drawbacks. Certain conventional heart rate technique. The condition may include a power consumption,
monitors , for example, require the use of a chest strap or 25 a battery charge level , a user activity, or the like . The user
other bulky equipment that causes discomfort and prevents activity may include one or more of exercise, rest, and sleep .
continuous wearing and use . This presents a challenge to The condition may include a location of the sensor or a
adoption and use of such monitors because the monitors are motion of the sensor. The different modes may include at
too obtrusive and / or are directed to assessing general well- least one mode using light emitted from a light source on the
being rather than continuous, around -the- clock monitoring 30 strap and detected by an optical detector on the strap. The at
least one mode may employ a peak detection technique
of fitness . Certain conventional heart rate monitors do not
enable continuous sensing of heart rate , thereby preventing mode applied to signals from the optical detector. The at least one
continuous fitness monitoring and reliable analysis of physi signalsmay employ a frequency domain technique applied
ological data . Additionally, a challenge to adoption of fitness 35 include one orthemore
from optical detector. The different modes may
modes using variable optical charac
monitors by athletes is the lack of a vibrant and interactive teristics of the light source
online community for displaying and sharing physiological istics may include at least .one The variable optical character
of a brightness of the light
data among users . source , a duty cycle of the light source , and a color of the
There remains a need for improved continuous heart rate light source . The different modes may include at least one
monitoring and interpretation . 40 non - optical mode . The sensor may include one or more of a
SUMMARY motion sensor, a position sensor, a timer, a temperature
sensor, a electrodermal activity (EDA) sensor (also referred
to as a Galvanic Skin Response (GSR) sensor ), and a
Disclosed herein is aa device for continuous physiological humidity sensor.
monitoring as well as systems and methods for interpreting 45 In another aspect , a method includes providing a strap
data from such a device. The device may support intelligent shaped and sized to fit about an appendage, where the strap
selection from among two or more different modes for heart includes a sensor and a heart rate monitoring system con
rate detection . In addition , the acquisition of continuous figured to provide two or more different modes for detecting
physiological data facilitates automated recommendations a heart rate of a wearer of the strap. The method may further
concerning changes to sleep , recovery time , exercise rou- 50 include detecting a signal from the sensor, determining a
tines and the like . condition of the heart rate monitoring system based upon the
In general, embodiments may provide physiological mea- signal, selecting one of the two or more different modes for
surement systems , devices, and methods for continuous detecting the heart rate based on the condition , and storing
health and fitness monitoring. A lightweight wearable sys- continuous heart rate data using the one of the two or more
tem with a strap may collect various physiological data 55 different modes.
continuously from a wearer without the need for additional Implementations may have one or more of the following
sensing devices. The systems may also enable monitoring of features. The method may include communicating the con
one or more physiological parameters in addition to heart tinuous heart rate data from the strap to a remote data
rate including, but not limited to , body temperature, heart repository. The method may include detecting a change in
rate variability, motion, sleep , stress , fitness level, recovery 60 the condition, responsively selecting a different one of the
level , effect of aa workout routine on health , caloric expen- two or more different modes, and storing additional con
diture, and the like . Embodiments may also include com- tinuous heart rate data obtained using the different one of the
puter - executable instructions that, when executed, enable two or more different modes .
automatic interpretation of one or more physiological In yet another aspect , a computer program product for
parameters to assess the cardiovascular intensity experi- 65 operating a wearable physical monitoring system including
enced by a user ( embodied in an intensity score or indicator) a sensor and a heart rate monitoring system configured to
and the user's recovery after physical exertion ( embodied in provide two or more different modes for detecting a heart
 US 11,185,241 B2
3 4
rate of a wearer of the wearable physical monitoring system, quantitative assessment of the physical recovery to auto
the computer program product including non - transitory matically generate a recommendation on a change to an
computer executable code embodied in a computer readable exercise routine of the user .
medium that, when executing on the wearable physical Implementations may have one or more of the following
monitoring system , performs the steps of: detecting a signal 5 features. Generating a quantitative assessment of the exer
from the sensor ; determining a condition of the heart rate cise activity may include analyzing the exercise activity on
monitoring system based upon the signal ; selecting one of a remote server . The method may further include determin
the two or more different modes for detecting the heart rate ing a qualitative assessment of the exercise activity and
communicating the qualitative assessment to the user. Gen
based on the condition ; and storing continuous heart rate 10 erating a quantitative assessment of the physical recovery
data using the one of the two or more different modes . state may include analyzing the physical recovery state on a
In another aspect , a device includes a wearable strap remote server. The method may further include determining
configured to be couplable to an appendage of a user , one or a qualitative assessment of the physical
more light emitters for emitting light toward the user's skin , communicating the qualitative assessmentrecovery state and
to the user. The
one or more light detectors for receiving light reflected from 15 method further include generating periodic updates to
the user's skin, and a processor configured to analyze data the user may
corresponding to the reflected light to automatically and mendationconcerning the physical recover state . The recom
may be generated on a remote server . The method
continually determine a heart rate of the user, thereby may further include communicating the recommendation to
providing continuous heart rate data. The device may further the user in an electronic mail . The method may further
include a communication system configured to transmit the 20 include presenting the recommendation to the user in a web
continuous heart rate data to a remote data repository, and a page . The method may further include generating the rec
privacy switch operable by the user to controllably restrict ommendation based upon a number of cycles of exercise and
communication of a portion of the continuous heart rate data rest .
to the remote data repository. In another aspect , a computer program product including
Implementations may have one or more of the following 25 non -transitory computer executable code embodied in a
features. The privacy switch may include a shared setting non - transitory computer - readable medium that, when
where continuous heart rate data is available to a shared data executing on one or more computing devices, performs the
repository. The shared data repository may be maintained by steps of: monitoring data from a wearable, continuous
an administrator for a sports team . The shared data reposi- monitoring, physiological measurement system worn by a
tory may be maintained on a social networking website 30 user ; automatically detecting exercise activity of the user;
available to one or more members of a social network of the generating a quantitative assessment of the exercise activity;
user. The privacy switch may include a private setting where automatically detecting a physical recovery state of the user ;
continuous heart rate data is not shared by the user. Con- generating a quantitative assessment of the physical recov
tinuous heart rate data may be stored locally for private use ery state ; and analyzing the quantitative assessment of the
by the user when in the private setting. Continuous heart rate 35 exercise activity and the quantitative assessment of the
data may not be saved when in the private setting. The physical recovery to automatically generate a recommenda
privacy switch may toggle between a private setting and a tion on a change to an exercise routine of the user.
shared setting. The device may include a display with an Implementations may have one or more of the following
indicator of a current privacy setting of the privacy switch . features. Generating a quantitative assessment of the exer
The privacy switch may be located on the strap of the device . 40 cise activity may include analyzing the exercise activity on
The privacy switch may be located on a local computing a remote server . The computer program product may further
device associated with the user . The local computing device include code that performs the step of determining a quali
may include a mobile computing device . The mobile com- tative assessment of the exercise activity and communicat
puting device may include one or more of a laptop , a tablet, ing the qualitative assessment to the user. Generating a
and a smart phone. The privacy switch may be hosted on a 45 quantitative assessment of the physical recovery state may
website accessible to the user through a web page . The include analyzing the physical recovery state on a remote
device may also include aa schedule configured to automati- server. The computer program product may further include
cally change a setting of the privacy switch on a predeter- code that performs the steps of determining a qualitative
mined schedule. The privacy switch may provide three or assessment of the physical recovery state and communicat
more different user - selectable privacy settings. The continu- 50 ing the qualitative assessment to the user . The computer
ous heart rate data may include summary data for a con- program product may further include code that performs the
tinuous heart rate of the user. The privacy switch may be step of generating periodic updates to the user concerning
operable by the user to controllably restrict communication the physical recover state . The computer program product
of other fitness data obtained by the device . The other fitness may further include code that performs the step of commu
data may include an activity of the user, where the activity 55 nicating the recommendation to the user in an electronic
selected from a group consisting of exercising, resting, and mail . The computer program product may further include
sleeping. The device may include one or more sensors , code that performs the step of presenting the recommenda
where the other fitness data includes data from the one or tion to the user in a web page . The computer program
more sensors . product may further include code that performs the step of
In yet another aspect , a method includes : monitoring data 60
from a wearable , continuous - monitoring , physiological
generating the recommendation based upon a number of
cycles of exercise and rest .
measurement system worn by a user ; automatically detect- In yet another aspect , a system includes a memory con
ing exercise activity of the user; generating a quantitative figured to store data received from a wearable , continuous
assessment of the exercise activity ; automatically detecting monitoring, physiological measurement system worn by a
a physical recovery state of the user ; generating a quantita- 65 user . The system may further include a server configured to
tive assessment of the physical recovery state; and analyzing automatically detect exercise activity of the user , generate a
the quantitative assessment of the exercise activity and the quantitative assessment of the exercise activity, automati
 US 11,185,241 B2
5 6
cally detect a physical recovery state of the user, generate a listing of users ( e.g. , a trainer's clients ) whose health infor
quantitative assessment of the physical recovery state , and mation is available for display.
analyze the quantitative assessment of the exercise activity FIG . 22 is aa block diagram of a computing device that
and the quantitative assessment of the physical recovery to may be used herein .
automatically generate a recommendation on a change to an 5 FIG . 23 is a block diagram of a distributed computer
exercise routine of the user. Additionally, the system may system in which various aspects and functions in accord
include a communications interface configured to transmit with the present disclosure may be practiced .
the recommendation from the server to the user. FIG . 24 is a diagram of a network environment suitable
for a distributed implementation of embodiments described
BRIEF DESCRIPTION OF THE DRAWINGS 10 herein .
FIG . 25 is a flow chart illustrating a method according to
The foregoing and other objects, features , and advantages an implementation .
of the devices, systems, and methods described herein will FIG . 26 is a flow chart illustrating a method according to
be apparent from the following description of particular an implementation .
embodiments thereof, as illustrated in the accompanying 15
figures. The figures are not necessarily to scale , emphasis DETAILED DESCRIPTION
instead being placed upon illustrating the principles of the
devices, systems , and methods described herein . The embodiments will now be described more fully
FIG . 1 illustrates front and back perspective views of a hereinafter with reference to the accompanying figures, in
wearable system configured as a bracelet including one or 20 which preferred embodiments are shown . The foregoing
more straps. may , however, be embodied in many different forms and
FIGS . 2-4 illustrate various embodiments of aa bracelet . should not be construed as limited to the illustrated embodi
FIG . 5 illustrates placement of a wearable physiological ments set forth herein . Rather, these illustrated embodiments
measurement system on a user's wrist . are provided so that this disclosure will convey the scope to
FIG . 6 shows aa block diagram illustrating components of 25 those skilled in the art .
a wearable physiological measurement system configured to All documents mentioned herein are hereby incorporated
provide continuous collection and monitoring of physiologi- by reference in their entirety . References to items in the
cal data . singular should be understood to include items in the plural,
FIG . 7A illustrates a side view of a physiological mea- and vice versa , unless explicitly stated otherwise or clear
surement system including a strap that is not coupled to a 30 from the text . Grammatical conjunctions are intended to
modular head portion. express any and all disjunctive and conjunctive combina
FIG . 7B illustrates a side view of a physiological mea- tions of conjoined clauses , sentences, words , and the like ,
surement system in which a modular head portion is remov- unless otherwise stated or clear from the context. Thus, the
ably coupled to the strap . term “ or ” should generally be understood to mean “ and /or”
FIGS . 8A and 8B depict a schematic side view and top 35 and so forth .
view , respectively, of a physiological measurement system Recitations of ranges of values herein are not intended to
including a head portion , a strap , and a multi- chip module . be limiting , referring instead individually to any and all
FIG . 9 is a flowchart illustrating a signal processing values falling within the range, unless otherwise indicated
algorithm for generating a sequence of heart rates for every herein, and each separate value within such a range is
detected heartbeat that may be embodied in computer- 40 incorporated into the specification as if it were individually
executable instructions stored on one or more non - transitory recited herein . The words “ about, ” “ approximately,” or the
computer- readable media . like, when accompanying a numerical value , are to be
FIG . 10 is aa flowchart illustrating a method of determining construed as indicating a deviation as would be appreciated
an intensity score . by one of ordinary skill in the art to operate satisfactorily for
FIG . 11 is a flowchart illustrating a method by which a 45 an intended purpose . Ranges of values and / or numeric
user may use intensity and recovery scores . values are provided herein as examples only, and do not
FIG . 12 illustrates a display of an intensity score index constitute aa limitation on the scope of the described embodi
indicated in a circular graphic component with an exemplary ments . The use of any and all examples, or exemplary
current score of 19.0 indicated . language (“ e.g., ” “ such as,” or the like ) provided herein , is
FIG . 13 illustrates a display of a recovery score index 50 intended merely to better illuminate the embodiments and
indicated in a circular graphic component with aa first thresh- does not pose a limitation on the scope of the embodiments .
old of 66 % and a second threshold of 33 % indicated . No language in the specification should be construed as
FIGS . 14A - 14C illustrate the recovery score graphic indicating any unclaimed element as essential to the practice
component with recovery scores and qualitative information of the embodiments .
corresponding to the recovery scores. 55 In the following description , it is understood that terms
FIGS . 15A - 18B illustrate a user interface for displaying such as “ first,” “ second,” “ above , ” “ below , " and the like , are
physiological data specific to a user as rendered on visual words of convenience and are not to be construed as limiting
display device. terms.
FIGS . 19A and 19B illustrate a user interface rendered on Exemplary embodiments provide physiological measure
a visual display device for displaying physiological data on 60 ment systems, devices and methods for continuous health
a plurality of users . and fitness monitoring , and provide improvements to over
FIG . 20 illustrates a user interface that may be used to come the drawbacks of conventional heart rate monitors .
independently select time periods of data for multiple users One aspect of the present disclosure is directed to providing
so that the data from the selected periods may be displayed a lightweight wearable system with a strap that collects
together. 65 various physiological data or signals from a wearer . The
FIGS . 21A and 21B illustrate a user interface viewable by strap may be used to position the system on an appendage or
an administrative user, including a selectable and editable extremity of a user, for example, wrist , ankle , and the like .
 US 11,185,241 B2
7 8
Exemplary systems are wearable and enable real- time and manner, only authorized users will be able to view the data
continuous monitoring of heart rate without the need for a and any associated scores. In addition, or in the alternative,
chest strap or other bulky equipment which could otherwise the website may allow users to monitor their own fitness
cause discomfort and prevent continuous wearing and use . results, share information with their teammates and coaches ,
The system may determine the user's heart rate without the 5 compete with other users , and win status. Both the wearable
use of electrocardiography and without the need for a chest system and the website allow a user to provide feedback
strap . Exemplary systems can thereby be used in not only regarding his /her day , exercise and /or sleep, which enables
assessing general well -being but also in continuous moni- recovery and performance ratings.
toring of fitness. Exemplary systems also enable monitoring In an exemplary technique of data transmission , data
of one or more physiological parameters in addition to heart 10 collected by a wearable system may be transmitted directly
rate including, but not limited to , body temperature, heart to a cloud -based data storage , from which data may be
rate variability, motion, sleep , stress, fitness level, recovery downloaded for display and analysis on a website . In another
level , effect of a workout routine on health and fitness , exemplary technique of data transmission , data collected by
caloric expenditure, and the like . a wearable system may be transmitted via a mobile com
A health or fitness monitor that includes bulky compo- 15 munication device application to a cloud -based data storage ,
nents may hinder continuous wear. Existing fitness monitors from which data may be downloaded for display and analy
often include the functionality of a watch , thereby making sis on a website.
the health or fitness monitor quite bulky and inconvenient In some embodiments, the website may be a social
for continuous wear . Accordingly, one aspect is directed to networking site . In some embodiments, the website may be
providing a wearable health or fitness system that does not 20 displayed using a mobile website or a mobile application. In
include bulky components, thereby making the bracelet some embodiments , the website may be configured to com
slimmer, unobtrusive and appropriate for continuous wear. municate data to other websites or applications. In some
The ability to continuously wear the bracelet further allows embodiments, the website may be configured to provide an
continuous collection of physiological data , as well as interactive user interface . The website may be configured to
continuous and more reliable health or fitness monitoring. 25 display results based on analysis on physiological data
For example, embodiments of the bracelet disclosed herein received from one or more devices . The website may be
allow users to monitor data at all times , not just during a configured to provide competitive ways to compare one user
fitness session . In some embodiments, the wearable system to another, and ultimately a more interactive experience for
may or may not include a display screen for displaying heart the user . For example, in some embodiments , instead of
rate and other information . In other embodiments, the wear- 30 merely comparing a user's physiological data and perfor
able system may include one or more light emitting diodes mance relative to that user's past performances, the user may
( LEDs ) to provide feedback to a user and display heart rate be allowed to compete with other users and the user's
selectively . In some embodiments, the wearable system may performance may be compared to that of other users .
include a removable or releasable modular head that may
provide additional features and may display additional infor- 35 I. DEFINITIONS OF TERMS
mation . Such aa modular head can be releasably installed on
the wearable system when additional information display is Certain terms are defined below to facilitate understand
desired , and removed to improve the comfort and appear- ing of exemplary embodiments.
ance of the wearable system . In other embodiments, the head The term “ user” as used herein , refers to any type of
may be integrally formed in the wearable system . 40 animal, human or non -human , whose physiological infor
Exemplary embodiments also include computer-execut- mation may be monitored using an exemplary wearable
able instructions that, when executed, enable automatic physiological monitoring system .
interpretation of one or more physiological parameters to The term “ body , " as used herein, refers to the body of a
assess the cardiovascular intensity experienced by a user user .
( embodied in an intensity score or indicator) and the user's 45 The term " continuous," as used herein in connection with
recovery after physical exertion or daily stress given sleep heart rate data collection , refers to collection of heart rate
and other forms of rest ( embodied in a recovery score ) . data at a sufficient frequency to enable detection of every
These indicators or scores may be stored and displayed in a heart beat and also refers to collection of heart rate data
meaningful format to assist a user in managing his health continuously throughout the day and night.
and exercise regimen . Exemplary computer -executable 50 The term “ pointing device , ” as used herein , refers to any
instructions may be provided in a cloud implementation. suitable input interface , specifically, a human interface
Exemplary embodiments also provide a vibrant and inter- device, that allows a user to input spatial data to a computing
active online community, in the form of a website , for system or device . In an exemplary embodiment, the pointing
displaying and sharing physiological data among users . A device may allow a user to provide input to the computer
user of the website may include an individual whose health 55 using physical gestures, for example, pointing, clicking ,
or fitness is being monitored , such as an individual wearing dragging, and dropping. Exemplary pointing devices may
a wearable system disclosed herein , an athlete, a sports team include, but are not limited to , a mouse , a touchpad, a
member, a personal trainer or a coach . In some embodi- touchscreen , and the like .
ments , a user may pick his / her own trainer from a list to The term “ multi - chip module , ” as used herein , refers to an
>

comment on their performance. Exemplary systems have the 60 electronic package in which multiple integrated circuits (IC )
ability to stream all physiological information wirelessly, are packaged with a unifying substrate, facilitating their use
directly or through a mobile communication device appli- as a single component, i.e. , as a higher processing capacity
cation, to an online website using data transfer to a cell IC packaged in a much smaller volume .
phone / computer. This information , as well as any data The term “ computer -readable medium ,” as used herein ,
described herein , may be encrypted ( e.g. , the data may 65 refers to a non - transitory storage hardware , non - transitory
include encrypted biometric data ). Thus, the encrypted data storage device or non -transitory computer system memory
may be streamed to a secure server for processing. In this that may be accessed by a controller, a microcontroller, a
 US 11,185,241 B2
9 10
computational system or a module of a computational sys- the narrower side into the thicker side and squeeze the two
tem to encode thereon computer -executable instructions or together until the strap is tight around the wrist, as shown in
software programs. The “ computer -readable medium ” may FIG . 5. To remove the strap, a user may push the strap
be accessed by a computational system or a module of a further inwards, which unlocks the strap and allows it to be
computational system to retrieve and / or execute the com- 5 released from the wrist . In other embodiments , various other
puter -executable instructions or software programs encoded fastening means may be provided. For example, the fasten
on the medium . The non - transitory computer - readable ing mechanism may include, without limitation , a clasp ,
media may include , but are not limited to , one or more types clamp, clip , dock, friction fit, hook and loop , latch , lock, pin ,
of hardware memory , non - transitory tangible media ( for
example , one or more magnetic storage disks , one or more 10 screw , slider, snap , button , spring , yoke, and so on .
optical disks, one or more USB flash drives ), computer slim elastic embodiments
In some , the strap of the bracelet may be a
system memory or random access memory ( such as , DRAM , example , rubber. Certainof embodiments
band formed any suitable elastic material, for
of the wearable
SRAM , EDO RAM ) and the like .
The term “ distal, ” as used herein , refers to a portion , end system may be configured to have one size that fits all . Other
or component of aa physiological measurement system that is 15 wrist embodiments may provide the ability to adjust for different
sizes . In one aspect , a combination of constant module
farthest from a user's body when worn by the user.
The term “ proximal, ” as used herein , refers to a portion , strap material, a spring - loaded, floating optical system and a
end or component of aa physiological measurement system silicon - rubber finish may be used in order to achieve cou
that is closest to a user's body when worn by the user . pling while maintaining the strap's comfort for continuous
The term “ equal, ” as used herein, refers, in a broad lay 20 use . Use of medical -grade materials to avoid skin irritations
sense , to exact equality or approximate equality within some may be utilized .
tolerance. As shown in FIG . 1 , the wearable system may include
components configured to provide various functions such as
II . EXEMPLARY WEARABLE data collection and streaming functions of the bracelet. In
PHYSIOLOGICAL MEASUREMENT SYSTEMS 25 some embodiments, the wearable system may include a
button underneath the wearable system . In some embodi
Exemplary embodiments provide wearable physiological ments, the button may be configured such that, when the
measurements systems that are configured to provide con- wearable system is properly tightened to one's wrist as
tinuous measurement of heart rate . Exemplary systems are shown in FIG . 3A , the button may press down and activate
configured to be continuously wearable on an appendage , 30 the bracelet to begin storing information . In other embodi
for example, wrist or ankle , and do not rely on electrocar- ments, the button may be disposed and configured such that
diography or chest straps in detection of heart rate . The it may be pressed manually at the discretion of a user to
exemplary system includes one or more light emitters for begin storing information or otherwise to mark the start or
emitting light at one or more desired frequencies toward the end of an activity period. In some embodiments, the button
user's skin , and one or more light detectors for received light 35 may be held to initiate a time stamp and held again to end
reflected from the user's skin . The light detectors may a time stamp, which may be transmitted , directly or through
include a photo - resistor, a photo - transistor, a photo -diode, a mobile communication device application , to a website as
and the like . As light from the light emitters ( for example, a time stamp.
green light) pierces through the skin of the user, the blood's Time stamp information may be used , for example, as a
natural absorbance or transmittance for the light provides 40 privacy setting to indicate periods of activity during which
fluctuations in the photo - resistor readouts . These waves physiological data may not be shared with other users . In
have the same frequency as the user's pulse since increased one aspect , the button may be tapped , double - tapped ( or
absorbance or transmittance occurs only when the blood triple -tapped or more) , or held down in order to perform
flow has increased after a heartbeat. The system includes a different functions or display different information ( e.g. ,
processing module implemented in software, hardware or a 45 display battery information , generate time stamps, etc. ) .
combination thereof for processing the optical data received Other implementations may include more or less buttons or
at the light detectors and continuously determining the heart other forms of interfaces. More general, a privacy switch
rate based on the optical data. The optical data may be such as any of the user inputs or controls described herein
combined with data from one or more motion sensors , e.g. , may be operated to control restrictions on sharing, distribu
accelerometers and / or gyroscopes, to minimize or eliminate 50 tion , or use of heart rate or other continuously monitored
noise in the heart rate signal caused by motion or other physiological data . For example , the privacy switch may
artifacts (or with other optical data of another wavelength ). include a toggle switch to switch between a private setting
FIG . 1 illustrates front and back perspective views of one where data is either not gathered at all or where data is stored
embodiment of a wearable system configured as a bracelet locally for a user, and between a public , shared , or other
100 including one or more straps 102. FIGS . 2 and 3 show 55 non -private setting where data is communicated over a
various exemplary embodiments of a bracelet according to network and / or to a shared data repository . The privacy
aspects disclosed herein . FIG . 4 illustrates an exemplary switch may also support numerous levels of privacy, e.g. ,
user interface of a bracelet. The bracelet is sleek and using a hierarchical, role - based, and / or identity -based
lightweight, thereby making it appropriate for continuous arrangement of permitted users and /or uses . As another
wear. The bracelet may or may not include a display screen , 60 example, various levels of privacy may be available for the
e.g. , a screen 106 such as a light emitting diode (LED ) type and amount of data that is shared versus private. In
display for displaying any desired data ( e.g. , instantaneous general, the privacy switch may be a physical switch on the
heart rate ), as shown and described below with reference to wearable system , or a logical switch or the like maintained
the exemplary embodiments in FIGS . 2-4 . on a computer or other local or mobile computing device of
As shown in the non - limiting embodiment in FIG . 1 , the 65 the user , or on a website or other network -accessible
strap 102 of the bracelet may have a wider side and a resource where the user can select and otherwise control
narrower side . In one embodiment, a user may simply insert privacy settings for monitored physiological data .
 US 11,185,241 B2
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In some embodiments, the wearable system may be In some embodiments, the wearable system may further
waterproof so that users never need to remove it , thereby be configured such that aa button underneath the system may
allowing for continuous wear . be pressed against the user's wrist, thus triggering the
The wearable system may include aa heart rate monitor. In system to begin one or more of collecting data , calculating
one example , the heart rate may be detected from the radial 5 metrics and communicating the information to a network . In
artery, in the exemplary positioning shown in FIG . 5. See , some embodiments, the sensor used for, e.g. , measuring
Certified Nursing Association , “ Regular monitoring of your heart rate or GSR or any combination of these , may be used
patient's radial pulse can help you detect changes in their to indicate whether the user is wearing the wearable system
condition and assist in providing potentially life -saving or not . In some embodiments, power to the one or more
care.” See , http://cnatraininghelp.com/cna-skills/counting- 10 LEDs may be cut off as soon as this situation is detected, and
and -recording - a - radial -pulse, the entire contents of which reset once the user has put the wearable system back on their
are incorporated herein by reference. Thus, the wearable wrist.
system may include a pulse sensor. In one embodiment, the The wearable system may include one, two or more
wearable system may be configured such that, when a user sources of battery life , e.g. , two or more batteries. In some
wears it around their wrist and tightens it , the sensor portion 15 embodiments, it may have a battery that can slip in and out
of the wearable system is secured over the user's radial of the head of the wearable system and can be recharged
artery or other blood vessel . Secure connection and place- using an included accessory. Additionally, the wearable
ment of the pulse sensor over the radial artery or other blood system may have a built - in battery that is less powerful.
vessel may allow measurement of heart rate and pulse . It When the more powerful battery is being charged, the user
will be understood that this configuration is provided by way 20 does not need to remove the wearable system and can still
of example only, and that other sensors , sensor positions , record data (during sleep , for example ) .
and monitoring techniques may also or instead be employed In some embodiments, an application associated with data
without departing from the scope of this disclosure . from an exemplary wearable system (e.g. , a mobile com
In some embodiments, the pulse or heart rate may be munication device application ) may include a user input
taken using an optical sensor coupled with one or more light 25 component for enabling additional contextual data , e.g. ,
emitting diodes (LEDs ) , all directly in contact with the emotional ( e.g. , the user's feelings ), perceived intensity, and
user's wrist. The LEDs are provided in a suitable position the like . When the data is uploaded from the wearable
from which light can be emitted into the user's skin . In one system directly or indirectly to a website , the website may
example, the LEDs mounted on a side or top surface of a record a user's “ Vibes ” alongside their duration of exercise
circuit board in the system to prevent heat buildup on the 30 and sleep .
LEDs and to prevent burns on the skin . The circuit board In exemplary embodiments, the wearable system is
may be designed with the intent of dissipating heat, e.g. , by enabled to automatically detect when the user is asleep ,
including thick conductive layers, exposed copper, heatsink, awake but at rest and exercising based on physiological data
or similar. In one aspect , the pulse repetition frequency is collected by the system .
such that the amount of power thermally dissipated by the 35 As shown in the exemplary embodiment of FIG . 4 , a
LED is negligible . Cleverly designed elastic wrist straps can rotatable wheel 108 may be provided at the center of the
ensure that the sensors are always in contact with the skin wearable system to control whether the system is displaying
and that there is a minimal amount of outside light seeping the heart rate . For example, when the wheel is turned to the
into the sensors . In addition to the elastic wrist strap, the right however, the system continuously shows heart rate, and
design of the strap may allow for continuous micro adjust- 40 turns off the heart rate display when the wheel is turned to
ments ( no preset sizes ) in order to achieve an optimal fit, and the right again . In one example, turning the wheel to the
a floating sensor module. The sensor module may be free to right and holding it there creates aa time stamp to indicate the
move with the natural movements caused by flexion and duration of exercise . Turning the wheel to the left and
extension of the wrist. holding it there forces data transmission to a cell phone ,
In some embodiments , the wearable system may be 45 external computer or the Internet. In other embodiments , the
configured to record other physiological parameters includ- wheel 108 may be absent in the wearable system . In some
ing , but not limited to , skin temperature ( using a thermom- embodiments , the functionality of a rotatable wheel
eter ), galvanic skin response (using a galvanic skin response described herein may be provided in an application of a
sensor ), motion ( using one or more multi -axes accelerom- mobile communication device that is associated with physi
eters and / or gyroscope ), and the like, and environmental or 50 ological data collected from a wearable system .
contextual parameters, e.g. , ambient temperature, humidity, FIG . 6 shows a block diagram illustrating exemplary
time of day, and the like . In an implementation , sensors are components of a wearable physiological measurement sys
used to provide at least one of continuous motion detection , tem 600 configured to provide continuous collection and
environmental temperature sensing, electrodermal activity toring of physiological data . The wearable system 600
( EDA) sensing , galvanic skin response (GSR) sensing, and 55 includes one or more sensors 602. As discussed above, the
the like . In this manner, an implementation can identify the sensors 602 may include a heart rate monitor. In some
cause of aa detected physiological event . Reflectance Pho- embodiments , the wearable system 600 may further include
toPlethysmoGraphy (RPPG) may be used for the detection one or more of sensors for detecting calorie burn, distance
of cardiac activity, which may provide for non - intrusive data and activity. Calorie burn may be based on a user's heart
collection , usability in wet, dusty and otherwise harsh envi- 60 rate, and aa calorie burn measurement may be improved if a
ronments, and low power requirements . For example , as user chooses to provide his or her weight and / or other
explained herein , using the physiological readouts of the physical parameters. In some embodiments, manual entering
device and the analytics described herein , an “ Intensity of data is not required in order to derive calorie burn ;
Score ” ( e.g. , 0-21 ) (e.g. , that measures a user's recent however, data entry may be used to improve the accuracy of
exertion ), a “ Recovery Score” ( e.g. , 0-100% ) , and “ Sleep 65 the results . In some embodiments, if a user has forgotten to
Score ” (e.g. , 0-100 ) may together measure readiness for enter a new weight, he / she can enter it for past weeks and the
physical and psychological exertion . calorie burn may be updated accordingly.
 US 11,185,241 B2
13 14
The sensors 602 may include one or more sensors for network interface 614 is configured to wirelessly commu
activity measurement. In some embodiments, the system nicate data to an external network . Some embodiments of
may include one or more multi - axes accelerometers and /or the wearable system may be configured to stream informa
gyroscope to provide a measurement of activity . In some tion wirelessly to a social network . In some embodiments ,
embodiments, the accelerometer may further be used to filter 5 data streamed from a user's wearable system to an external
a signal from the optical sensor for measuring heart rate and network may be accessed by the user via a website . The
to provide a more accurate measurement of the heart rate . In network interface may be configured such that data collected
some embodiments, the wearable system may include a by the system may be streamed wirelessly. In some embodi
multi - axis accelerometer to measure motion and calculate ments, data may be transmitted automatically, without the
distance , whether it be in real terms as steps or miles or as 10 need to manually press any buttons. In some embodiments,
a converted number. Activity sensors may be used, for the system may include a cellular chip built into the system .
example, to classify or categorize activity, such as walking,
running, performing another sport, standing, sitting or lying In one example, the network interface may be configured to
down . In some embodiments , one or more of collected the stream data using Bluetooth technology. In another example,
physiological data may be aggregated to generate an aggre- 15 usingnetwork interface may be configured to stream data
gate activity level. For example, heart rate, calorie burn , and networka cellular
.
data service, such as via aa 3G or 4G cellular
distance may be used to derive an aggregate activity level.
The aggregate level may be compared with or evaluated In some embodiments, a physiological measurement sys
relative to previous recordings of the user's aggregate activ- tem may be configured in a modular design to enable
ity level, as well as the aggregate activity levels of other 20 continuous operation of the system in monitoring physi
users . ological information of a user wearing the system . The
The sensors 602 may include a thermometer for monitor- module design may include a strap and a separate modular
ing the user's body or skin temperature . In one embodiment, head portion or housing that is removably couplable to the
the sensors may be used to recognize sleep based on a strap . FIG . 7A illustrates a side view of an exemplary
temperature drop, GSR data , lack of activity according to 25 physiological measurement system 100 including a strap
data collected by the accelerometer, and reduced heart rate 102 that is not coupled to a modular head portion or housing
as measured by the heart rate monitor. The body tempera- 104. FIG . 7B illustrates a side view of the system 100 in
ture, in conjunction with heart rate mmonitoring and motion , which the modular head portion 104 is removably coupled
may be used to interpret whether a user is sleeping or just
resting , as body temperature drops significantly when an 30 to Inthethestrapnon102 .
individual is about to fall asleep ), and how well an indi 102 of a physiologicalillustrative
-limiting module design, the strap
vidual is sleeping as motion indicates a lower quality of vided with a set of components thatsystem
measurement may be pro
sleep . The body temperature may also be used to determine monitoring of at least a heart rate of theenables continuous
whether the user is exercising and to categorize and / or independent and fully self - sufficient in continuouslythatmoni
user so it is
analyze activities . 35
The system 600 includes one or more batteries 604 . toring the heart rate without requiring the modular head
According to one embodiment, the one or more batteries rality portion 104. In one embodiment, the strap includes a plu
may be configured to allow continuous wear and usage of of light emitters for emitting light toward the user's
the wearable system . In one embodiment, the wearable skin, a plurality of light detectors for receiving light reflected
system may include two or more batteries. The system may 40 from the user's skin , an electronic circuit board comprising
include a removable battery that may be recharged using a a plurality of electronic components configured for analyz
charger. In one example, the removable battery may be ing data corresponding to the reflected light to automatically
configured to slip in and out of a head portion of the system , and continually determine aa heart rate of the user, and aa first
attach onto the bracelet , or the like . In one example, the set of one or more batteries for supplying electrical power to
removable battery may be able to power the system for 45 the light emitters, the light detectors and the electronic
around a week . Additionally, the system may include a circuit board . In some embodiments, the strap may also
built - in battery. The built - in battery may be recharged by the detect one or more other physiological characteristics of the
removable battery. The built - in battery may be configured to user including, but not limited to , temperature, galvanic skin
power the bracelet for around a day on its own . When the response , and the like. The strap may include one or more
more removable battery is being charged, the user does not 50 slots for permanently or removably coupling batteries 702 to
need to remove the system and may continue collecting data the strap 102
using the built - in battery. In other embodiments , the two The strap 102 may include an attachment mechanism 706 ,
batteries may both be removable and rechargeable . e.g. , a press - fit mechanism , for coupling the modular head
In some embodiments, the system 600 may include a portion 104 to the strap 102. The modular head portion 104
battery that is aa wireless rechargeable battery. For example, 55 may be coupled to the strap 102 at any desired time by the
the battery may be recharged by placing the system or the user to impart additional functionality to the system 100. In
battery on a rechargeable mat . In other example, the battery one embodiment, the modular head portion 104 includes a
may be a long range wireless rechargeable battery. In other second set of one or more batteries 704 chargeable by an
embodiments, the battery may be a rechargeable via motion . external power source so that the second set of batteries can
In yet other embodiments, the battery may be rechargeable 60 be used to charge or recharge the first set of batteries 702 in
using a solar energy source . the strap 102. The combination of the first and second sets
The wearable system 600 includes one or more non- of batteries enables the user to continuously monitor his /her
transitory computer- readable media 606 for storing raw data physiological information without having to remove the
detected by the sensors of the system and processed data strap for recharging. In some embodiments, the module head
calculated by a processing module of the system . 65 portion may include one or more additional components
The system 600 includes a processor 608 , a memory 610 , including, but not limited to , an interface 616 including
a bus 612 , a network interface 614 and an interface 616. The visual display device configured to render a user interface
 US 11,185,241 B2
15 16
for displaying physiological information of the user, a GPS chip modules may be stacked vertically on top of one
sensor, an electronic circuit board ( e.g. , to process GPS another on the circuit board to further minimize the pack
signals ), and the like . aging size and the footprint of the circuit board .
Certain exemplary systems may be configured to be In one multi -chip embodiment, two or more electrically
coupled to any desired part of a user's body so that the 5 coupled circuit boards of a multi -chip module may be
system may be moved from one portion of the body ( e.g. , provided in a physiological measurement system in a ver
wrist) to another portion of the body (e.g. , ankle ) without tically stacked manner to minimize the packaging size and
affecting its function and operation. An exemplary system the footprint of the circuit board . Vertically stacking the
may include an electronic circuit board comprising a plu- components on a circuit board minimizes the packaging size
rality of electronic components configured for analyzing 10 (e.g. , the length and width ) and the footprint occupied by the
data corresponding to the reflected light to automatically and chips on the circuit board . In certain non - limiting embodi
continually determine aa heart rate of the user . The electronic ments , a circuit board including one or more physiological
circuit board implements a processing module configured to sensors may be placed closest to , proximal to or in contact
detect an identity of a portion of the user's body, for with the user's skin , while one or more circuit boards
example, an appendage like wrist , ankle, to which the strap 15 including one or more processors, storage devices , commu
is coupled based on one or more signals associated with the nication components and non -physiological sensors may be
heart rate of the user, and, based on the identity of the provided in vertical layers that are distal to the user's skin .
appendage, adjust data analysis of the reflected light to FIGS . 8A and 8B depict a schematic side view and top
determine the heart rate of the user. view , respectively, of an exemplary physiological measure
In one embodiment, the identity of the portion of the 20 ment system 100 including a head portion 104, a strap 102
user's body to which the wearable system is attached may be and a multi -chip module . The head portion and / or the strap
determined based on one or more parameters including , but may include a circuit board 802 including a multi - chip
not limited to , absorbance level of light as returned from the module assembled in a vertically stacked configuration. Two
user's skin , reflectance level of light as returned from the or more layers of active electronic integrated circuit (IC )
user's skin , motion sensor data (e.g. , accelerometer and / or 25 components are integrated vertically into a single circuit in
gyroscope ), altitude of the wearable system , and the like . the circuit board . The IC layers are oriented in spaced planes
In some embodiments, the processing module is config- that extend substantially parallel to one another in a verti
ured to determine that the wearable system is taken off from cally stacked configuration . As illustrated in FIG . 8A , the
the user's body. In one example, the processing module may circuit board 802 includes a substrate 804 for supporting the
determine that the wearable system has been taken offif data 30 multi-chip module . A first integrated circuit chip 806 is
from the galvanic skin response sensor indicates data atypi- coupled to the substrate 804 using any suitable coupling
cal of a user's skin . If the wearable system is determined to mechanism , for example, epoxy application and curing. A
be taken off from the user's body, the processing module is first spacer layer 808 is coupled the surface of the first
configured to deactivate the light emitters and the light integrated circuit chip 806 opposite to the substrate 804
detectors and cease monitoring of the heart rate of the user 35 using, for example , epoxy application and curing. A second
to conserve power. integrated circuit chip 810 is coupled to the surface of the
In some exemplary embodiments, the electronic compo- first spacer layer 808 opposite to the first integrated circuit
nents of the physiological measurement system may be chip 806 using , for example, epoxy application and curing.
provided in the form of a multi - chip module in which a The first and second integrated circuit chips 806 and 810 are
plurality of electrically -coupled electronic circuit boards are 40 electrically coupled using wiring 812 .
provided separately within the system . In one non- limiting In some embodiments, a metal frame may be provided for
example , the processor and random - access memory (RAM ) mechanical and / or electrical connection among the inte
may be provided on a first circuit board , wireless commu- grated circuit chips. An exemplary metal frame may take the
nication components may be provided on a second circuit form of aa lead frame. The first and second integrated circuit
board , and sensors may be provided on a third circuit board . 45 chips may be coupled to the metal frame using wiring . A
The separate electronic circuit boards may be provided in a packaging may be provided to encapsulate the multi-chip
modular head of the system and / or along a strap of the module assembly and to maintain the multiple integrated
system . The term “ multi - chip module , ” as used herein , refers circuit chips in substantially parallel arrangement with
to an electronic package in which multiple integrated cir- respect to one another.
cuits (IC ) are packaged with a unifying substrate, facilitating 50 As illustrated in FIG . 8A , the vertical three - dimensional
their use as a single component, i.e. , as a higher processing stacking of the first integrated circuit chip 806 and the
capacity IC packaged in a much smaller volume . Each IC second integrated circuit chip 810 provides high -density
can comprise a circuit fabricated in a thinned semiconductor functionality on the circuit board while minimizing overall
wafer. Any suitable set of one or more electronic compo- packaging size and footprint (as compared to a circuit board
nents may be provided in the circuit boards of a multi -chip 55 that does not employ a vertically stacked multi-chip mod
module . Exemplary embodiments also provide methods for ule ) . One of ordinary skill in the art will recognize that an
fabricating and assembling multi - chip modules as taught exemplary multi-chip module is not limited to two stacked
herein . integrated circuit chips. Exemplary numbers of chips verti
Exemplary numbers of chips integrated in a multi - chip cally integrated in a multi -chip module may include, but are
module may include , but are not limited to , two , three, four, 60 not limited to , two, three , four, five, six , seven , eight, and the
five, six , seven , eight, and the like . In one embodiment of a like.
physiological measurement system , a single multi - chip In one embodiment, a single multi- chip module is pro
module is provided on a circuit board that performs opera- vided . In other embodiments, a plurality of multi - chip
tions to generate physiological information associated with modules as illustrated in FIG . 8A is provided. In an exem
a user of the system . In other embodiments, a plurality of 65 plary embodiment, a plurality of multi-chip modules ( for
multi - chip modules are provided on a circuit board of the example, two multi - chip modules) may be stacked vertically
physiological measurement system . The plurality of multi- on top of one another on a circuit board of a physiological
 US 11,185,241 B2
17 18
measurement system to further minimize the packaging size lating over these impulses , an aspect can account for more
and footprint of the circuit board . extreme cases of motion . Additionally , an investigation into
In addition to the need for reducing the footprint, there is different LED wavelengths, intensities, and configurations
also a need for decreasing the overall package height in can allow the systems described herein to extract a signal
multi- chip modules. Exemplary embodiments may employ 5 across a wide spectrum of skin types and wrist sizes . In other
wafer thinning to sub -hundreds micron to reduce the pack- words, motion filtering algorithms and signal processing
age height in multi - chip modules . Any suitable technique techniques may assist in mitigating the risk caused by
can be used to assemble aa multi -chip module on a substrate . movement.
Exemplary assembly techniques include , but are not limited
9 FIG . 9 is a flowchart illustrating an exemplary signal
to , laminated MCM ( MCM - L ) in which the substrate is a 10 processing algorithm for generating a sequence of heart rates
multi - layer laminated printed circuit board, deposited MCM for every detected heartbeat that is embodied in computer
( MCM - D ) in which the multi -chip modules are deposited on executable instructions stored on one or more non - transitory
the base substrate using thin film technology , and ceramic computer - readable media . In step 902 , light emitters of a
substrate MCM (MCM - C ) in which several conductive wearable physiological measurement system emit light
layers are deposited on a ceramic substrate and embedded in 15 toward a user's skin . In step 904 , light reflected from the
glass layers that layers are co - fired at high temperatures user's skin is detected at the light detectors in the system . In
( HTCC ) or low temperatures ( LTCC ). step 906 , signals or data associated with the reflected light
In another multi-chip embodiment illustrated in FIG . 8B , are pre -processed using any suitable technique to facilitate
two or more electrically -coupled circuit boards of a multi- detection of heart beats . In step 908 , a processing module of
chip module may be provided in a physiological measure- 20 the system executes one or more computer -executable
ment system in a horizontally spaced manner to minimize instructions associated with a peak detection algorithm to
the height of the circuit board . Providing the components on process data corresponding to the reflected light to detect a
a circuit board in a horizontally spaced manner minimizes plurality of peaks associated with a plurality of beats of the
the packaging height occupied by the chips on the circuit user's heart. In step 910 , the processing module determines
board . In certain non - limiting embodiments, a circuit board 25 an RR interval based on the plurality of peaks detected by
including one or more physiological sensors may be placed the peak detection algorithm . In step 912 , the processing
close to or in contact with the user's skin so that physiologi- module determines a confidence level associated with the
cal signals are detected reliably, while one or more circuit RR interval.
boards including one or more processors , storage devices , Based on the confidence level associated with the RR
communication components and non -physiological sensors 30 interval estimate, the processing module selects either the
may be provided may be distributed throughout the wearable peak detection algorithm or a frequency analysis algorithm
system to provide improved flexibility, wearability, comfort to process data corresponding to the reflected light to
and durability of the system . determine the sequence of instantaneous heart rates of the
FIG . 8B depicts a schematic top view of an exemplary user . The frequency analysis algorithm may process the data
physiological measurement system 100 including a head 35 corresponding to the reflected light based on the motion of
portion 104 and a strap 102. The head portion 104 and /or the the user detected using , for example , an accelerometer. The
strap 102 may include a circuit board including a plurality of processing module may select the peak detection algorithm
integrated circuit boards or chips 820 , 822 , 824 forming a or the frequency analysis algorithm regardless of a motion
multi-chip module assembled in aa horizontally spaced con- status of the user. It is advantageous to use the confidence in
figuration. The integrated circuit chips are electrically 40 the estimate in deciding whether to switch to frequency
coupled to one another using wiring 826. The circuit chips based methods as certain frequency -based approaches are
may be distributed through the head portion and / or the strap unable to obtain accurate RR intervals for heart rate vari
of the system . In the non -limiting illustrative embodiment, ability analysis. Therefore, an implementation maintains the
for example, one chip is provided in the head portion and ability to obtain the RR intervals for as long as possible ,
two chips are provided in the strap . 45 even in the case of motion , thereby maximizing the infor
Exemplary systems include a processing module config- mation that can be extracted .
ured to filter the raw photoplethysmography data received For example, in step 914 , it is determined whether the
from the light detectors to minimize contributions due to confidence level associated with the RR interval is above (or
motion , and subsequently process the filtered data to detect equal to or above) a threshold . In certain embodiments, the
peaks in the data that correspond with heart beats of a user. 50 threshold may be predefined, for example, about 50 % -90 %
The overall algorithm for detecting heart beats takes as input in some embodiments and about 80 % in one non -limiting
the analog signals from optical sensors (mV ) and acceler- embodiment. In other embodiments, the threshold may be
ometer, and outputs an implied beats per minute (heart rate ) adaptive, i.e. , the threshold may be dynamically and auto
of the signal accurate within aa few beats per minute as that matically determined based on previous confidence levels .
determined by an electrocardiography machine even during 55 For example, if one or more previous confidence levels were
motion . high ( i.e. , above a certain level ), the system may determine
In one aspect , using multiple LEDs with different wave- that a present confidence level that is relatively low com
lengths reacting to movement in different ways can allow for pared to the previous levels is indicative of a less reliable
signal recovery with standard signal processing techniques. signal. In this case , the threshold may be dynamically
The availability of accelerometer information can also be 60 adjusted to be higher so that a frequency -based analysis
used to compensate for coarse movement signal corruption . method may be selected to process the less reliable signal .
In order to increase the range of movements that the algo- If the confidence level is above ( or equal to or above ) the
rithm can successfully filter out, an aspect utilizes tech- threshold, in step 916 , the processing module may use the
niques that augment the algorithm already in place . For plurality of peaks to determine an instantaneous heart rate of
example, filtering violent movements of the arm during very 65 the user . On the other hand, in step 920 , based on a
short periods of time, such as boxing as exercising, may be determination that the confidence level associated with the
utilized by the system . By selective sampling and interpo- RR interval is equal to or below the predetermined thresh
 US 11,185,241 B2
19 20
old , the processing module may execute one or more com- parameter space , at each step declaring the mode of the
puter - executable instructions associated with the frequency distribution to be the heart rate estimate . A discrete uniform
analysis algorithm to determine an instantaneous heart rate prior may be set :
of the user . The confidence threshold may be dynamically 1 ~ DiscUnif (0 )
set based on previous confidence levels. 5

In some embodiments, in steps 918 or 922 , the processing The un - normalized , univariate likelihood is defined by a
module determines a heart rate variability of the user based mixture of a Gaussian function and a uniform :
on the sequence of the instantaneous heart rates /beats . 1 -IG + (1-1) U , G - N ( Yao ),I - Ber ( p)
The system may include a display device configured to 10
render a user interface for displaying the sequence of the where
instantaneous heart rates of the user, the RR intervals and /or
the heart rate variability determined by the processing U - DiscUnif ( 0 )
module. The system may include a storage device config- and where o and p are predetermined constants .
ured to store the sequence of the instantaneous heart rates, 15 Bayes ' rule is applied to determine the posterior density
the RR intervals and /or the heart rate variability determined on 0 , for example, by component-wise multiplying the prior
by the processing module. density vector (T , ( O ) eco with the likelihood vector (1 , ( 0 ) )
In one aspect , the system may switch between different DEO to obtain the posterior distribution ni . Then , the follow
analytical techniques for determining a heart rate such as a ing is set :
statistical technique for detecting a heart rate and a fre- 20 Bi = argmaxgeoni(0 )
quency domain technique for detecting a heart rate . These For kz2 , the variance in signal S (t) due to process noise
two different modes have different advantages in terms of is determined . Then , the following variable is set to imbue
accuracy , processing efficiency, and information content, temporally long RR intervals with more process /interpeak
and as such may be useful at different times and under noise and set the post -normalization convolution :
different conditions. Rather than selecting one such mode or 25
technique as an attempted optimization , the system may
usefully switch back and forth between these differing Tik = nk - 1 * INOA )
techniques, or other analytical techniques, using a predeter
mined criterion . For example, where statistical techniques 30
are used, a confidence level may be determined and used as where f is a density function of the following:
a threshold for switching to an alternative technique such as Z - N ( 0,2 )
a frequency domain technique. The threshold may also or
instead depend on historical , subjective, and / or adapted data Then , the following expressions are calculated :
for a particular user. For example, selection of a threshold 35 Ix -PGx + ( 1 - p ) U ,GX - N (1,02)
may depend on data for a particular user including without The expression is then normalized and recorded :
limitation subjective information about how a heart rate for
a particular user responds to stress, exercise, and so forth . Bk = argmaxpeon ( 0 )
Similarly, the threshold may adapt to changes in fitness of a Finally, the confidence level of the above expression for
user, context
system , signalprovided
noise, andfrom other. sensors of the wearable
so forth 40 a particular precision threshold is determined:
An exemplary statistical technique employs probabilistic
peak detection . In this technique, a discrete probabilistic step Ck = ? nk .
may be set , and a likelihood function may be established as HE [Bk - e1.5k + e] 0
a mixture of a Gaussian random variable and a uniform . The 45
heart of the likelihood function encodes the assumption that
with aa first probability (p ) the peak detection algorithm has An exemplary frequency analysis algorithm used in an
produced a reasonable initial estimate , but with a second implementation isolates the highest frequency components
probability ( 1 - p ) it has not . In a subsequent step , Bayes ' rule of the optical data , checks for harmonics common in both
is applied to determine the posterior density on the param- 50 the accelerometer data and the optical data, and performs
eter space , of which the maximum is taken (that is , the filtering of the optical data . The algorithm takes as input raw
argument ( parameter) that maximizes the posterior distribu- analog signals from the accelerometer ( 3 - axis ) and pulse
tion ). This value is the estimate for the heart rate . In a sensors , and outputs heart rate values or beats per minute
subsequent step , the previous two steps are reapplied for the (BPM) for a given period of time related to the window of
rest of the sample. There is some variance in the signal due 55 the spectrogram .
to process noise , which is dependent on the length of the The isolation of the highest frequency components is
interval. This process noise becomes the variance in the performed in a plurality of stages , gradually winnowing the
Gaussians used for the likelihood function . Then , the esti- window - sizes of consideration , thereby narrowing the range
mate is obtained as the maximum a posteriori on the new of errors . In one implementation, a spectrogram of 2º15
posterior distribution . A confidence value is recorded for the 60 samples with overlap 2 ^ 13 samples of the optical data is
estimate which , for some precision measurement, the pos- generated. The spectrogram is restricted to frequencies in
terior value is summed at points in the parameter space which heart rate can lie . These restriction boundaries may be
centered at our estimate +/- the precision . updated when smaller window sizes are considered . The
The beats per minute (BPM) parameter space , 0 , may frequency estimate is extracted from the spectrogram by
range between about 20 and about 240 , corresponding to the 65 identifying the most prominent frequency component of the
empirical bounds on human heart rates. In an exemplary spectrogram for the optical data. The frequency may be
method, a probability distribution is calculated over this extracted using the following exemplary steps . The most
 US 11,185,241 B2
21 22
prominent frequency of the spectrogram is identified in the 3334/30/12/005 . URL : http://www.ncbi.nlm.nih.gov/
signal. It is determined if the frequency estimate is a pubmed / 19864707; and Lu , S, et . al . " Can
harmonic of the true frequency. The frequency estimate is photoplethysmography variability serve as an alternative
replaced with the true frequency if the estimate is aa harmonic approach to obtain heart rate variability information ?” Jour
of the true frequency. It is determined if the current fre- 5 nal of Clinical Monitoring and Computing. 2008 February;
quency estimate is a harmonic of the motion sensor data . The 22 ( 1 ) : 23-9 . URL : http://www.ncbi.nlm.nih.gov/pubmed/
frequency estimate is replaced with a previous temporal 17987395 , the entire contents of which are incorporated
estimate if it is a harmonic of the motion sensor data . The herein by reference .
upper and lower bounds on the frequency obtained are 10 Exemplary physiological measurement systems are con
saved. A constant value may be added or subtracted in some figured to minimize power consumption so that the systems
cases . In subsequent steps , the constant added or subtracted may be worn continuously without requiring power recharg
may be reduced to provide narrower searches. A number of ing at frequent intervals. The majority of current draw in an
the previous steps are repeated one or more times , e.g. , three
times , except taking 2 ^ { 15 - i } samples for the window size exemplary system is allocated to power the light emitters ,
and 2" { 13 –i } for the overlap in the spectrogram where i is 15 peripherals
e.g., LEDs,. theIn wireless transceiver, the
one embodiment ,thecircuit
microcontroller
board of and
the
the current number of iteration . The final output is the system may include aa boost converter that runs a current of
average of the final symmetric endpoints of the frequency about 10 mA through each of the light emitters with an
estimation .
The table below demonstrates the performance of the efficiency of about 80 % and may draw power directly from
algorithm disclosed herein . To arrive at the results below, 20 the batteries at substantially constant power. With exemplary
experiments were conducted in which a subject wore an batteries at about 3.7 V , the current draw from the battery
exemplary wearable physiological measurement system and may be about 40 mW . In some embodiments, the wireless
a 3 - lead ECG which were both wired to the same micro- transceiver may draw about 10-20 mA of current when it is
controller ( e.g. , Arduino ) in order to provide time -synced actively transferring data. In some embodiments, the micro
data . Approximately 50 data sets were analyzed which 25 controller and peripherals may draw about 5 mA of current.
included the subject standing still , walking, and running on An exemplary system may include a processing module
a treadmill. that is configured to automatically adjust one or more
operational characteristics of the light emitters and /or the
TABLE 1 light detectors to minimize power consumption while ensur
30 ing that all heart beats of the user are reliably and continu
Performance of signal processing algorithm disclosed herein ously detected . The operational characteristics may include,
Clean data error Noisy data error but are not limited to , a frequency of light emitted by the
(mean, std . dev .) in BPM (mean, std . dev .) in BPM light emitters, the number of light emitters activated, a duty
cycle of the light emitters, a brightness of the light emitters ,
4 -level spectrogram 0.2 , 2.3 0.8 , 5.1 35 a sampling rate of the light detectors, and the like .
( 80 second blocks ) The processing module may adjust the operational char
acteristics based on one or more signals or indicators
The algorithm's performance comes from a combination obtained or derived from one or more sensors in the system
of a probabilistic and frequency based approach. The three including, but not limited to , a motion status of the user , a
difficulties in creating algorithms for heart rate calculations 40 sleep status of the user, historical information on the user's
from the PPG data are 1 ) false detections of beats, 2 ) missed physiological and / or habits , an environmental or contextual
detections of real beats , and 3 ) errors in the precise timing condition ( e.g. , ambient light conditions), a physical char
of the beat detection . The algorithms disclosed herein pro- acteristic of the user (e.g. , the optical characteristics of the
vide improvements in these three sources of error and, in user's skin) , and the like .
some cases , the error is bound to within 2 BPM of ECG 45 In one embodiment, the processing module may receive
values at all times even during the most motion intense data on the motion of the user using, for example, an
activities . accelerometer. The processing module may process the
The exemplary wearable system computes heart rate motion data to determine aa motion status of the user which
variability (HRV ) to obtain an understanding of the recovery indicates the level of motion of the user, for example ,
status of the body. These values are captured right before a 50 exercise , light motion ( e.g. , walking ) , no motion or rest,
user awakes or when the user is not moving , in both cases sleep, and the like . The processing module may adjust the
photoplethysmography (PPG) variability yielding equiva- duty cycle of one or more light emitters and the correspond
lence to the ECG HRV . HRV is traditionally measured using ing sampling rate of the one or more light detectors based on
an ECG machine and obtaining a time series of R - R inter- the motion status. For example, upon determining that the
vals . Because an exemplary wearable system utilizes pho- 55 motion status indicates that the user is at a first higher level
toplethysmography ( PPG) , it does not obtain the electric of motion, the processing module may activate the light
signature from the heart beats; instead, the peaks in the emitters at a first higher duty cycle and sample the reflected
obtained signal correspond to arterial blood volume. At rest, light using light detectors sampling at a first higher sampling
these peaks are directly correlated with cardiac cycles , rate . Upon determining that the motion status indicates that
which enables the calculation of HRV via analyzing peak- 60 the user is at aa second lower level of motion , the processing
to - peak intervals ( the PPG analog of RR intervals ). It has module may activate the light emitters at a second lower
been demonstrated in the medical literature that these peak- duty cycle and sample the reflected light using light detec
to - peak intervals, the “ PPG variability , ” is identical to ECG tors sampling at a second lower sampling rate . That is , the
HRV while at rest. See , Charlot K , et al . “ Interchangeability duty cycle of the light emitters and the corresponding
between heart rate and photoplethysmography variabilities 65 sampling rate of the light detectors may be adjusted in a
during sympathetic stimulations . ” Physiological Measure- graduated or continuous manner based on the motion status
ment. 2009 December; 30 ( 12 ) : 1357-69 . doi: 10.1088 /0967- or level of motion of the user. This adjustment ensures that
 US 11,185,241 B2
23 24
heart rate data is detected at a sufficiently high frequency Shorter -wavelength LEDs may require more power than
during motion to reliably detect all of the heart beats of the is required by longer -wavelength LEDs . Therefore , an
user . exemplary wearable system may provide and use light
In non - limiting examples, the light emitters may be acti- emitted at two or more different frequencies based on the
vated at a duty cycle ranging from about 1 % to about 100 % . 5 level of motion detected in order to save battery life. For
In another example, the light emitters may be activated at a example, upon determining that the motion status indicates
duty cycle ranging from about 20 % to about 50 % to mini that the user is at a first higher level of motion ( e.g. ,
mize power consumption . Certain exemplary sampling rates exercising ), one or more light emitters may be activated to
of the light detectors may range from about 50 Hz to about 10 emit light at a first wavelength. Upon determining that the
1000 Hz , but are not limited to these exemplary rates. motion status indicates that the user is at a second lower
Certain non - limiting sampling rates are, for example , about level of motion (e.g. , at rest) , one or more light emitters may
100 Hz , 200 Hz , 500 Hz , and the like . belonger
activated to emit light at a second wavelength that is
than the first wavelength . Upon determining that the
In one non- limiting example , the light detectors may motion status indicates that the user is at a third lower level
sample continuously when the user is performing an exer 15 of motion (e.g. , sleeping ), one or more light emitters may be
cise routine so that the error standard deviation is kept within activated to emit light at third wavelength that is longer
5 beats per minute ( BPM) . When the user is at rest, the light than the first and second wavelengths. Other levels of
detectors may be activated for about a 1 % duty cycle — 10 motion may be predetermined and corresponding wave
milliseconds each second ( i.e. , 1 % of the time) so that the lengths of emitted light may be selected . The threshold
error standard deviation is kept within 5 BPM ( including an 20 levels of motion that trigger adjustment of the light wave
error standard deviation in the heart rate measurement of 2 length may be based on one or more factors including , but
BPM and an error standard deviation in the heart rate are not limited to , skin properties , ambient light conditions ,
changes between measurement of 3 BPM ) . When the user is and the like. Any suitable combination of light wavelengths
in light motion ( e.g. , walking ) , the light detectors may be may be selected , for example, green ( for a higher level of
activated for about a 10% duty cycle— 100 milliseconds 25 motion )/ red ( for a lower level of motion ); red ( for a higher
each second (i.e. , 10 % of the time) so that the error standard level of motion ) / infrared ( for a lower level of motion) ; blue
deviation is kept within 6 BPM (including an error standard ( for a higher level of motion )/green ( for a lower level of
deviation in the heart rate measurement of 2 BPM and an motion ); and the like.
error standard deviation in the heart rate changes between Shorter -wavelength LEDs may require more power than
measurement of 4 BPM) . 30 is required by other types of heart rate sensors , such as , a
The processing module may adjust the brightness of one piezo - sensor or an infrared sensor. Therefore , an exemplary
or more light emitters by adjusting the current supplied to wearable system may provide and use a unique combination
the light emitters . For example, a first level of brightness of sensors — one or more light detectors for periods where
may be set by current ranging between about 1 mA to about motion is expected and one or more piezo and / or infrared
10 mA , but is not limited to this exemplary range . A second 35 sensors for low motion periods (e.g. , sleep ) —to save battery
higher level of brightness may be set by current ranging life . Certain other embodiments of a wearable system may
from about 11 mA to about 30 mA , but is not limited to this exclude piezo - sensors and / or infrared sensors .
exemplary range. A third higher level of brightness may be For example, upon determining that the motion status
set by current ranging from about 80 mA to about 120 mA , indicates that the user is at a first higher level of motion ( e.g. ,
but is not limited to this exemplary range . In one non- 40 exercising ), one or more light emitters may be activated to
limiting example, first, second and third levels of brightness emit light at a first wavelength . Upon determining that the
may be set by current of about 5 mA, about 20 mA and about motion status indicates that the user is at a second lower
100 mA , respectively. level ofmotion ( e.g. , at rest) , non - light based sensors may be
In some embodiments , the processing module may detect activated . The threshold levels of motion that trigger adjust
an environmental or contextual condition (e.g. , level of 45 ment of the type of sensor may be based on one or more
ambient light) and adjust the brightness of the light emitters factors including , but are not limited to , skin properties,
accordingly to ensure that the light detectors reliably detect ambient light conditions , and the like .
light reflected from the user's skin while minimizing power The system may determine the type of sensor to use at a
consumption. For example, if it is determined that the given time based on the level of motion (e.g. , via an
ambient light is at a first higher level, the brightness of the 50 accelerometer) and whether the user is asleep (e.g. , based on
light emitters may be set at a first higher level. If it is movement input, skin temperature and heart rate ). Based on
determined that the ambient light is at a second lower level, a combination of these factors the system selectively
the brightness of the light emitters may be set at a second chooses which type of sensor to use in monitoring the heart
lower level. In some cases , the brightness may be adjusted rate of the user. Common symptoms of being asleep are
in a continuous manner based on the detected environment 55 periods of no movement or small bursts of movement ( such
condition . as shifting in bed) , lower skin temperature ( although it is not
In some embodiments, the processing module may detect a dramatic drop from normal), drastic GSR changes, and
a physiological condition of the user ( e.g. , an optical char- heart rate that is below the typical resting heart rate when the
acteristic of the user's skin) and adjust the brightness of the user is awake. These variables depend on the physiology of
light emitters accordingly to ensure that the light detectors 60 a person and thus a machine learning algorithm is trained
reliably detect light reflected from the user's skin while with user-specific input to determine when he /she is awake /
minimizing power consumption . For example, if it is deter- asleep and determine from that the exact parameters that
mined that the user's skin is highly reflective, the brightness cause the algorithm to deem someone asleep .
of the light emitters may be set at a first lower level. If it is In an exemplary configuration, the light detectors may be
determined that the user's skin is not very reflective, the 65 positioned on the underside of the wearable system and all
brightness of the light emitters may be set at a second higher of the heart rate sensors may be positioned adjacent to each
level . other. For example, the low power sensor ( s) may be adjacent
 US 11,185,241 B2
25 26
to the high power sensor ( s ) as the sensors may be chosen and be determined every morning upon waking up , the intensity
placed where the strongest signal occurs . In one example score may be determined in real - time or after a workout
configuration , a 3 - axis accelerometer may be used that is routine or for an entire day.
located on the top part of the wearable system . In certain exemplary embodiments, a fitness score may be
In some embodiments, the processing module may be 5 automatically determined based on the physiological data of
configured to automatically adjust a rate at which data is twoAnor intensity
more users of exemplary wearable systems.
score or indicator provides an accurate
transmitted by the wireless transmitter to minimize power
consumption while ensuring that raw and processed data indication of the cardiovascular intensities experienced by
generated by the system is reliably transmitted to external 10 the user during a portion of a day, during the entire day or
during any desired period of time (e.g. , during a week or
computing devices. In one embodiment, the processing month ). The intensity score is customized and adapted for
module determines an amount of data to be transmitted ( e.g. ,
based on the amount of data generated since the time of the the unique physiological properties of the user and takes into
account, for example, the user's age , gender, anaerobic
last data transmission ), and may select the next data trans threshold , resting heart rate , maximum heart rate , and the
mission time based on the amount of data to be transmitted . 15 like. If determined for an exercise routine, the intensity score
For example, if it is determined that the amount of data provides an indication of the cardiovascular intensities expe
exceeds ( or is equal to or greater than ) a threshold level , the rienced by the user continuously throughout the routine. If
processing module may transmit the data or may schedule a determined for a period of including and beyond an exercise
time for transmitting the data . On the other hand, if it is routine, the intensity score provides an indication of the
determined that the amount of data does not exceed ( or is 20 cardiovascular intensities experienced by the user during the
equal to or lower than ) the threshold level, the processing routine and also the activities the user performed after the
module may postpone data transmission to minimize power routine (e.g. , resting on the couch, active day of shopping )
consumption by the transmitter. In one non - limiting that may affect their recovery or exercise readiness .
example , the threshold may be set to the amount of data that In exemplary embodiments, the intensity score is calcu
may be sent in two seconds under current conditions . 25 lated based on the user's heart rate reserve ( HRR) as
Exemplary data transmission rates may range from about 50 detected continuously throughout the desired time period,
kbytes per second to about 1 MByte per second, but are not for example , throughout the entire day. In one embodiment,
limiting to this exemplary range . the intensity score is an integral sum of the weighted HRR
In some embodiments, an operational characteristic of the detected continuously throughout the desired time period.
microprocessor may be automatically adjusted to minimize 30 FIG . 10 is a flowchart illustrating an exemplary method of
power consumption. This adjustment may be based on a determining an intensity score .
level of motion of the user's body. In step 1002 , continuous heart rate readings are converted
More generally, the above description contemplates a to HRR values . A time series of heart rate data used in step
variety of techniques for sensing conditions relating to heart 1002 may be denoted as:
rate monitoring or related physiological activity either 35 HET
directly ( e.g. , confidence levels or accuracy of calculated A time series of HRR measurements, v (t) , may be defined
heart rate ) or indirectly (e.g. , motion detection, tempera in the following expression in which MHR is the
ture ). However measured, these sensed conditions can be maximum heart rate and RHR is the resting heart rate
used to intelligently select from among a number of different of the user :
modes , including hardware modes , software modes , and 40
combinations of the foregoing, for monitoring heart rate
based on, e.g. , accuracy, power usage , detected activity H (1) – RHR
states , and so forth . Thus there is disclosed herein techniques v (t) = MHR - RHR
for selecting from among two or more different heart rate
monitoring modes according to a sensed condition . 45
In step 1004 , the HRR values are weighted according to
III . EXEMPLARY PHYSIOLOGICAL a suitable weighting scheme . Cardiovascular intensity, indi
ANALYTICS SYSTEM cated by an intensity score, is defined in the following
expression in which w is a weighting function of the HRR
Exemplary embodiments provide an analytics system for 50 measurements :
providing qualitative and quantitative monitoring of a user's
body, health and physical training. The analytics system is
implemented in computer -executable instructions encoded I?to, 11 ) =
271
w ( v (t ))dt
on one or more non - transitory computer -readable media . TO
The analytics system relies on and uses continuous data on 55
one or more physiological parameters including , but not In step 1006 , the weighted time series of HRR values is
limited to , heart rate . The continuous data used by the summed and normalized .
analytics system may be obtained or derived from an exem
plary physiological measurement system disclosed herein , 1 = f7w ( v( t) ) dtsw ( 1 ) | 7|
or may be obtained or derived from a derived source or 60 Thus, the weighted sum is normalized to the unit interval,
system , for example, a database of physiological data . In i.e. , [ 0 , 1 ] :
some embodiments, the analytics system computes, stores
and displays one or more indicators or scores relating to the
user's body, health and physical training including , but not Ni
IT
limited to , an intensity score and a recovery score . The 65 =

w ( 1 ) . 24 hr
scores may be updated in real - time and continuously or at
specific time periods, for example, the recovery score may
 US 11,185,241 B2
27 28
In step 1008 , the summed and normalized values are levels , there is a further subsequent threshold (CPT ) at
scaled to generate user- friendly intensity score values . That which creatine triphosphate (CTP ) is employed for respira
is , the unit interval is transformed to have any desired tion with even less efficiency .
distribution in aa scale ( e.g. , a scale including 21 points from In order to account for the differing levels of cardiovas
0 to 21 ) , for example, arctangent, sigmoid , sinusoidal, and 5 cular exertion and efficiency at the different HRR levels, in
the like. In certain distributions, the intensity values increase one embodiment, the possible values of HRR are divided
at a linear rate along the scale , and in others , at the highest into a plurality of categories, sections or levels (e.g. , three )
ranges the intensity values increase at more than aa linear rate dependent on the efficiency of cellular respiration at the
to indicate that it is more difficult to climb in the scale respective categories . The HRR parameter range may be
toward the extreme end of the scale . In some embodiments, 10 divided in any suitable manner , such as , piecewise, includ
ing piecewise - linear, piecewise -exponential, and the like .
the raw intensity scores are scaled by fitting a curve to a An
selected group of " canonical ” exercise routines that are eterexemplary range
piecewise -linear division of the HRR param
enables weighting each ca with strictly
predefined to have particular intensity scores .
In one embodiment, monotonic transformations of the 15 tion of the cardiovascular intensity experienced by theindica
increasing values . This scheme captures an accurate
user
unit interval are achieved to transform the raw HRR values
to user - friendly intensity scores . An exemplary scaling values because it is more difficult to spend time at higher HRR
scheme, expressed as f : [ 0 , 1 ] -- [ 0 , 1 ] , is performed using increase, which suggests that the weighting function should
at the increasing weight categories.
the following function: In one non - limiting example, the HRR parameter range
20
may be considered a range from zero (0 ) to one ( 1 ) and
divided into categories with strictly increasing weights. In
(x , N , p ) = 0.51arctan A( N/ 2( x – p ) ) +1
=
one example, the HRR parameter range may be divided into
a first category of a zero HRR value and may assign this
category a weight of zero ; a second category of HRR values
To generate an intensity score , the resulting value may be 25 falling between zero (0 ) and the user's anaerobic threshold
multiplied by a number based on the desired scale of the ( AT ) and may assign this category a weight of one ( 1 ) ; a
intensity score . For example, if the intensity score is gradu- third category of HRR values falling between the user's
ated from zero to 21 , then the value may be multiplied by 21 . anaerobic threshold ( AT ) and aa threshold at which the user's
In step 1010 , the intensity score values are stored on a body employs creatine triphosphate for respiration ( CPT )
non -transitory storage medium for retrieval, display and 30 and may assign this category a weight of 18 ; and aa fourth
usage . In step 1012 , the intensity score values are , in some category of HRR values falling between the creatine tri
embodiments, displayed on a user interface rendered on a phosphate threshold ( CPT ) and one ( 1 ) and may assign this
visual display device . The intensity score values may be category a weight of 42 , although other numbers of HRR
displayed as numbers and / or with the aid of graphical tools , categories and different weight values are possible . That is ,
e.g. , a graphical display of the scale of intensity scores with 35 in this example, the weights are defined as :
current score , and the like . In some embodiments , the
intensity score may be indicated by audio . In step 1012 , the
intensity score values are , in some embodiments, displayed 0: V=0
along with one or more quantitative or qualitative pieces of W( v ) =
1: VE (0 , AT ]
information on the user including, but not limited to , 40 18 : VE ( AT , CPT]
whether the user has exceeded his / her anaerobic threshold , 42 : VE (CPT , 1 ]
the heart rate zones experienced by the user during an
exercise routine, how difficult an exercise routine was in the
context of the user's training, the user's perceived exertion
In another exemplary embodiment of the weighting
during an exercise routine, whether the exercise regimen of
45 scheme, the HRR time series is weighted iteratively based
the user should be automatically adjusted (e.g. , made easier
on the intensity scores determined thus far ( e.g. , the intensity
if the intensity scores are consistently high ), whether the
score accrued thus far) and the path taken by the HRR values
user is likely to experience soreness the next day and the
to get to the present intensity score . The path may be
level of expected soreness , characteristics of the exercise
detected automatically based on the historical HRR values
routine ( e.g. , how difficult it was for the user , whether the
50 and may indicate, for example, whether the user is perform
exercise was in bursts or activity, whether the exercise was
ing high intensity interval training (during which the inten
tapering, etc. ), and the like. In one embodiment, the analyt-
sity scores are rapidly rising and falling ), whether the user
ics system may automatically generate, store and display an
is taking long breaks between bursts of exercise ( during
exercise regimen customized based on the intensity scores of
which the intensity scores are rising after longer periods) ,
the user. 55 and the like . The path may be used to dynamically determine
Step 1006 may use any of aa number of exemplary staticand adjust the weights applied to the HRR values . For
or dynamic weighting schemes that enable the intensity example, in the case of high intensity interval training, the
score to be customized and adapted for the unique physi- weights applied may be higher than in the case of a more
ological properties of the user. In one exemplary static traditional exercise routine .
weighting scheme , the weights applied to the HRR values
60 In another exemplary embodiment of the weighting
are based on static models of a physiological process . The
scheme, a predictive approach is used by modeling the
human body employs different sources of energy with vary-weights or coefficients to be the coefficient estimates of a
ing efficiencies and advantages at different HRR levels . For
logistic regression model . In this scheme, a training data set
example , at the anaerobic threshold (AT ), the body shifts to
is obtained by continuously detecting the heart rate time
anaerobic respiration in which the cells produce two adenos-
65 series and other personal parameters of a group of individu
ine triphosphate ( ATP ) molecules per glucose molecule , as
als . The training data set is used to train a machine learning
opposed to 36 at lower HRR levels . At even higher HRR system to predict the cardiovascular intensities experienced
 US 11,185,241 B2
29 30
by the individuals based on the heart rate and other personal score , and recent strain ( indicated , in one example, by the
data . The trained system models a regression in which the intensity score of the user ). In an exemplar, the sleep score
coefficient estimates correspond to the weights or coeffi- combined with performance readiness measures ( such as ,
cients of the weighting scheme. In the training phase, user morning heart rate and morning heart rate variability ) pro
input on perceived exertion and the intensity scores are 5 vides a complete overview of recovery to the user . By
compared . The learning algorithm also alters the weighs considering sleep and HRV alone or in combination , the user
based on the improving or declining health of a user as well can understand how exercise - ready he/ she is each day and to
as their qualitative feedback . This yields a unique algorithm understand how he / she arrived at the exercise - readiness
that incorporates physiology, qualitative feedback, and score each day, for example, whether aa low exercise -readi
quantitative data . In determining a weighting scheme for a 10 ness score is a predictor of poor recovery habits or an
specific user , the trained machine learning system is run by inappropriate training schedule. This insight aids the user in
executing computer - executable instructions encoded on one adjusting his/her daily activities , exercise regimen and
or more non - transitory computer -readable media , and gen- sleeping schedule therefore obtain the most out of his / her
erates the coefficient estimates which are then used to weight training
the user's HRR time series. 15 In some cases , the recovery score may take into account
One of ordinary skill in the art will recognize that two or perceived psychological strain experienced by the user . In
more aspects of any of the disclosed weighting schemes may some cases , perceived psychological strain may be detected
be applied separately or in combination in an exemplary from user input via , for example, a questionnaire on a mobile
method for determining an intensity score . device or web application . In other cases , psychological
In one aspect , heart rate zones quantify the intensity of 20 strain may be determined automatically by detecting
workouts by weighing and comparing different levels of changes in sympathetic activation based on one or more
heart activity as percentages of maximum heart rate. Analy- parameters including, but not limited to , heart rate variabil
sis of the amount of time an individual spends training at a ity, heart rate, galvanic skin response , and the like .
certain percentage of his / her MHR may reveal his / her state With regard to the user's HRV used in determining the
of physical exertion during a workout. This intensity, devel- 25 recovery score , suitable techniques for analyzing HRV
oped from the heart rate zone analysis, motion, and activity, include, but are not limited to , time - domain methods, fre
may then indicate his /her need for rest and recovery after the quencyy - domain methods, geometric methods and non - linear
workout, e.g. , to minimize delayed onset muscle soreness methods. In one embodiment, the HRV metric of the root
( DOMS ) and prepare him / her for further activity. As dis- mean - square of successive differences (RMSSD ) of RR
cussed above, MHR , heart rate zones , time spent above the 30 intervals is used . The analytics system may consider the
anaerobic threshold , and HRV in RSA ( Respiratory Sinus magnitude of the differences between 7 - day moving aver
Arrhythmia ) regions as well as personal information (gen- ages and 3 - day moving averages of these readings for a
age , height, weight, etc. ) may be utilized in data given day. Other embodiments may use Poincaré Plot analy
processing. sis or other suitable metrics of HRV .
A recovery score or indicator provides an accurate indi- 35 The recovery score algorithm may take into account RHR
cation of the level of recovery of aa user's body and health along with history of past intensity and recovery scores .
after a period of physical exertion . The human autonomic With regard to the user's resting heart rate , moving
nervous system controls the involuntary aspects of the averages of the resting heart rate are analyzed to determine
body's physiology and is typically subdivided into two significant deviations . Consideration of the moving averages
branches: parasympathetic ( deactivating) and sympathetic 40 is important since day - to - day physiological variation is quite
( activating ). Heart rate variability (HRV ), i.e. , the fluctuation large even in healthy individuals. Therefore, the analytics
in inter -heartbeat interval time , is a commonly studied result system may perform a smoothing operation to distinguish
of the interplay between these two competing branches . changes from normal fluctuations.
Parasympathetic activation reflects inputs from internal Although an inactive condition , sleep is a highly active
organs, causing a decrease in heart rate . Sympathetic acti- 45 recovery state during which a major portion of the physi
vation increases in response to stress, exercise and disease , ological recovery process takes place . Nonetheless, a small ,
causing an increase in heart rate . For example, when high yet significant, amount of recovery can occur throughout the
intensity exercise takes place , the sympathetic response to day by rehydration, macronutrient replacement, lactic acid
the exercise persists long after the completion of the exer- removal, glycogen re -synthesis, growth hormone production
cise . When high intensity exercise is followed by insufficient 50 and a limited amount of musculoskeletal repair. In assessing
recovery, this imbalance lasts typically until the next morn- the user's sleep quality, the analytics system generates a
ing , resulting in a low morning HRV. This result should be sleep score using continuous data collected by an exemplary
taken as a warning sign as it indicates that the parasympa- physiological measurement system regarding the user's
thetic system was suppressed throughout the night. While heart rate, skin conductivity, ambient temperature and accel
suppressed, normal repair and maintenance processes that 55 erometer /gyroscope data throughout the user's sleep . Col
ordinarily would occur during sleep were suppressed as lection and use of these four streams of data enable an
well . Suppression of the normal repair and maintenance understanding of sleep previously only accessible through
processes results in an unprepared state for the next day, invasive and disruptive over-night laboratory testing. For
making subsequent exercise attempts more challenging. example, an increase in skin conductivity when ambient
The recovery score is customized and adapted for the 60 temperature is not increasing , the wearer's heart rate is low ,
unique physiological properties of the user and takes into and the accelerometer / gyroscope shows little motion , may
account, for example, the user's heart rate variability ( HRV ), indicate that the wearer has fallen asleep. The sleep score
resting heart rate, sleep quality and recent physiological indicates and is a measure of sleep efficiency (how good the
strain (indicated, in one example , by the intensity score of user's sleep was ) and sleep duration (if the user had suffi
the user ). In one exemplary embodiment, the recovery score 65 cient sleep ). Each of these measures is determined by a
is a weighted combination of the user's heart rate variability combination of physiological parameters, personal habits
(HRV ), resting heart rate, sleep quality indicated by a sleep and daily stress / strain intensity ) inputs. The actual data
 US 11,185,241 B2
31 32
measuring the time spent in various stages of sleep may be the like . The display may indicate, for example, that the
combined with the wearer's recent daily history and a intensity score corresponds to a good and tapering exercise
longer - term data set describing the wearer's personal habits routine, that the user did not overcome his anaerobic thresh
to assess the level of sleep sufficiency achieved by the user . old and that the user will have little to no soreness the next
The sleep score is designed to model sleep quality in the 5 dayIn. step 1106 , in an exemplary embodiment, the analytics
context of sleep duration and history . It thus takes advantage system may automatically generate or adjust an exercise
of the continuous monitoring nature of the exemplary physi
ological measurement systems disclosed herein by consid routine or regimen based on the user's actual intensity scores
ering each sleep period in the context of biologically or desired intensity scores . For example , based on inputs of
determined sleep needs, pattern -determined sleep needs and 10 the user's actual intensity scores, a desired intensity score
( that is higher than the actual intensity scores ) and a first
historically -determined sleep debt. exercise routine currently performed by the user (e.g. , walk
The recovery and sleep score values are stored on a ing ) , the analytics system may recommend a second differ
non - transitory storage medium for retrieval, display and ent exercise routine that is typically associated with higher
usage . The recovery and /or sleep score values are, in some intensity scores than the first exercise routine (e.g. , running ).
embodiments, displayed on a user interface rendered on a 15 In step 1108 , at any given time during the day ( e.g. , every
visual display device. The recovery and / or sleep score morning ), the analytics system may generate and display a
values may be displayed as numbers and / or with the aid of recovery score . In some cases , the analytics system may
graphical tools , e.g. , a graphical display of the scale of display quantitative and / or qualitative information corre
recovery scores with current score, and the like . In some sponding to the intensity score . For example, in step 1110 ,
embodiments , the recovery and / or sleep score may be indi- 20 in an exemplary embodiment, the analytics system may
cated by audio . The recovery score values are , in some determine if the recovery is greater than (or equal to or
embodiments, displayed along with one or more quantitative greater than ) a first predetermined threshold (e.g. , about 60 %
or qualitative pieces of information on the user including, to about 80 % in some examples) that indicates that the user
but not limited to , whether the user has recovered suffi- is recovered and is ready for exercise . If this is the case , in
ciently, what level of activity the user is prepared to perform , 25 step 1112 , the analytics system may indicate that the user is
whether the user is prepared to perform an exercise routine ready to perform an exercise routine at a desired intensity or
a particular desired intensity, whether the user should rest that the user is ready to perform an exercise routine more
and the duration of recommended rest, whether the exercise challenging than the past day's routine . Otherwise , in step
regimen of the user should be automatically adjusted (e.g. , 1114 , the analytics system may determine if the recovery is
made easier if the recovery score is low ) , and the like . In one 30 lower than (or equal to or lower than ) a second predeter
embodiment , the analytics system may automatically gen- mined threshold (e.g. , about 10% to about 40 % in some
erate , store and display an exercise regimen customized examples) that indicates that the user has not recovered . If
based on the recovery scores of the user alone or in com- this is the case , in step 1116 , the analytics system may
bination with the intensity scores. indicate that the user should not exercise and should rest for
As discussed above , the sleep performance metric may be 35 an extended period. The analytics system may, in some
based on parameters like the number of hours of sleep , sleep cases , the duration of recommended rest . Otherwise , in step
onset latency, and the number of sleep disturbances. In this 1118 , the analytics system may indicate that the user may
manner, the score may compare a tactical athlete's duration exercise according to his / her exercise regimen while being
and quality of sleep in relation to the tactical athlete's careful not to overexert him /herself. The thresholds may , in
evolving sleep need ( e.g., a number of hours based on recent 40 some cases , be adjusted based on a desired intensity at which
strain, habitual sleep need , signs of sickness, and sleep debt). the user desires to exercise . For example, the thresholds may
By way of example, a soldier may have a dynamically be increased for higher planned intensity scores.
changing need for sleep , and it may be important to consider FIG . 13 illustrates an exemplary display of a recovery
the total hours of sleep in relation to the amount of sleep that score index indicated in a circular graphic component with
may have been required. By providing an accurate sensor for 45 a first threshold of 66 % and a second threshold of 33 %
sleep and sleep performance, an aspect may evaluate sleep indicated . FIGS . 14A - 14C illustrate the recovery score
in the context of the overall day and lifestyle of a specific graphic component with exemplary recovery scores and
user. qualitative information corresponding to the recovery
FIG . 11 is a flowchart illustrating an exemplary method by scores .
which a user may use intensity and recovery scores . In step 50 Optionally, in an exemplary embodiment, the analytics
1102 , the wearable physiological measurement system system may automatically generate or adjust an exercise
begins determining heart rate variability (HRV ) measure- routine or regimen based on the user's actual recovery
ments based on continuous heart rate data collected by an scores ( e.g. , to recommend lighter exercise for days during
exemplary physiological measurement system . In some which the user has not recovered sufficiently ). This process
cases , it may take the collection of several days of heart rate 55 may also use a combination of the intensity and recovery
data to obtain an accurate baseline for the HRV. In step 1104 , scores .
the analytics system may generate and display intensity The analytics system may , in some embodiments , deter
score for an entire day or an exercise routine. In some cases , mine and display the intensity and /or recovery scores of a
the analytics system may display quantitative and / or quali- plurality of users in a comparative manner. This enables
tative information corresponding to the intensity score . FIG . 60 users to match exercise routines with others based on
12 illustrates an exemplary display of an intensity score comparisons among their intensity scores .
index indicated in a circular graphic component with an
exemplary current score of 19.0 indicated . The graphic IV . EXEMPLARY DISPLAYS AND USER
component may indicate a degree of difficulty of the exercise INTERFACES
corresponding to the current score selected from , for 65
example, maximum all out , near maximal , very hard , hard, Exemplary embodiments also provide a vibrant and inter
moderate, light, active , light active , no activity, asleep , and active online community for displaying and sharing physi
 US 11,185,241 B2
33 34
ological data among users . Exemplary systems have the panel 1514 accessible using tab 1516 , day — a day panel
ability to stream the physiological information wirelessly, 1518 accessible using tab 1520 , and sleepa sleep panel
directly or through a mobile device application, to an online 1522 accessible using tab 1524. The same or different
website . The website allows users to monitor their own feedback panels may be associated with the workout, day
fitness results, share information with their teammates and 5 and sleep panels. The panels may enable the user to select
coaches, compete with other users , and win status. Both the and customize one or more informative panels that appear in
wearable system and the website allow a user to provide his /her user interface display.
feedback regarding his day, which enables recovery and The workout panel 1514 may present quantitative infor
performance ratings. One aspect is directed to providing an mation on the user's health and exercise routines, for
online website for health and fitness monitoring. In some 10 example, a graph 1530 of the user's continuous heart rate
embodiments, the website may be aa social networking site . during the exercise, statistics 1532 on the maximum heart
The website may allow users , such as young athletes, to rate, average heart rate, duration of exercise, number of steps
monitor their own fitness results, share information with taken and calories expended, zones 1534 in which the
their teammates and coaches , compete with other users, and maximum heart rate fell during the exercise , and a graph
win prizes . A user may include an individual whose health 15 1536 of the intensity scores over a period of time ( e.g. , seven
or fitness is being monitored , such as an individual wearing days ) .
a bracelet disclosed herein , an athlete, a sports team member, A feedback panel 1538 associated with the workout panel
a personal trainer or a coach . In some embodiments, a user 1514 may present information on the intensity score and the
may pick their own trainer from a list to comment on their exercise routines performed by the user during a selected
performance. 20 period of time including, but not limited to , quantitative
In some embodiments, the website may be configured to information , qualitative information, feedback , recommen
provide an interactive user interface. The website may be dations on future exercise routines, and the like . The feed
configured to display results based on analysis on physi- back panel 1538 may present the intensity score along with
ological data received from one or more devices . The a qualitative summary 1540 of the score indicating, for
website may be configured to provide competitive ways to 25 example , whether the user pushed past his anaerobic thresh
compare one user to another, and ultimately a more inter- old for a considerable period of the exercise, whether the
active experience for the user. For example, in some exercise is likely to cause muscle pain and soreness, and the
embodiments, instead of merely comparing a user's physi- like . Based on analysis of the quantitative health parameters
ological data and performance relative to that user's past monitored during the exercise routine, the feedback panel
performances, the user may be allowed to compete with 30 1538 may present one or more tips 1542 on adjusting the
other users and the user's performance may be compared to exercise routine, for example, that the exercise routine
that of other users . started too rapidly and that the user should warm up for
In some embodiments, the website may be a mobile longer. In some cases , upon selection of the tips sub -panel
website or a mobile application . In some embodiments, the 1542 , a corresponding indicator 1544 may be provided in the
website may be configured to communicate data to other 35 heart rate graph 1530 .
websites or applications . Based on analysis of the quantitative health parameters
The exemplary website may include a brief and free monitored during the exercise routine, the feedback panel
sign- up process during which a user may create an account 1538 may also present qualitative information 1545 on the
with his /her name, account name, email , home address , user's exercise routine, for example, comparison of the
height, weight, age , and a unique code provided in his /her 40 present day's exercise routine to the user's historical exer
wearable physiological measurement system . The unique cise data . Such information may indicate , for example, that
code may be provided, for example, on the wearable system the user's maximum heart rate for the day's exercise was the
itself or in the packaged kit . Once subscribed, continuous highest ever recorded , that the steps taken by the user that
physiological data received from the user's system may be day was the fewest ever recorded , that the user burned a lot
retrieved in a real - time continuous basis and presented 45 of calories and that more calories may be burned by low
automatically on a webpage associated with the user . Addi- ering the intensity of the exercise, and the like . The feedback
tionally, the user can add information to his profile, such as , panel 1538 may also present cautionary indicators 1546 to
a picture, favorite activities , sports team ( s ) , and the user may warn the user of future anticipated health events, for
search for teammates / friends on the website for sharing example, the likelihood of soreness (e.g. , if the intensity
information . 50 score is higher than a predefined threshold ), and the like .
FIGS . 15A - 18B illustrate an exemplary user interface An exemplary analytics system may analyze the informa
1500 for displaying physiological data specific to a user as tion presented in the workout panel 1514 and determine
rendered on visual display device . The user interface 1500 whether the user performed a specific exercise routine or
may take the form of a webpage in some embodiments. One activity. As one example, given a small number of steps
of ordinary skill in the art will recognize that the information 55 taken and aa high calorie burn and heart rate, the system may
in FIGS . 15A - 18B represent non- limiting illustrative determine that it is possible the user rode a bicycle that day.
examples. The user interface 1500 may include a summary In some cases , the feedback panel 1538 may prompt the user
panel 1502 including an identification 1504 of the user ( e.g. , to confirm whether he / she indeed performed that activity in
a real or account name ) with , optionally , a picture or photo a user field 1548. This user input may be displayed and / or
corresponding to the user. The summary panel 1502 may 60 used to improve an understanding of the user's health and
also display the current intensity score 1506 and the current exercise routines .
recovery score 1508 of the user. In some embodiments, the The day panel 1518 may include information on health
summary panel 1502 may display the number of calories parameters of the user during the current day including, but
burned by the user 1510 that day and the number of hours not limited to , the number of calories burned and the number
of sleep 1512 obtained by the user the previous night. 65 of calories taken in 1500 ( which may be based on user input
The user interface 1500 may also include panels for on the foods eaten ), a graph 1554 of the day's continuous
presenting information on the user's workouts- a workout heart rate , statistics 1556 on the resting heart rate and steps
 US 11,185,241 B2
35 36
taken by the user that day, a graph 1558 of the calories example , a sign of overtraining and aa recommendation to get
burned that and other days, and the like. more sleep (e.g. , if the user awoke many times during sleep
In some cases , an analytics system may analyze the and / or if the user moved around during sleep .
physiological data ( e.g. , heart rate data ) and estimate the The user interface 1500 may provide a user input field
durations of sleep , activity and workout during the day. A 5 1590 for enabling the user to indicate his/her feelings, e.g. ,
feedback panel 1562 associated with the day panel 1518 activities performed perceived exertion , energy level , per
may present these durations 1564. In some cases , the feed- formance . The user interface 1500 may also provide a user
back panel 1562 may display a net number of calories input field 1592 for enabling the user to indicate other facts
consumed by the user that day 1566. Based on analysis of about his exercise routine, e.g. , comments on what the user
the quantitative health parameters monitored during the 10 was doing at a specific point in the exercise routine with a
exercise routine, the feedback panel 1562 may also present link 1594 to a corresponding point in the heart rate graph
qualitative information 1568 on the user's exercise routine . 1530. In some embodiments, the user may specify a route
Such information may indicate, for example, that the user and /or location on a map at which the exercise routine was
was stressed at a certain point in the day (e.g. , if there was performed
a high level of sweat with little activity ), that the user's 15 Exemplary embodiments also enable a user to compare
maximum heart rate for the day's exercise was the highest his / her quantitative and / or qualitative physiological data
ever recorded , that the steps taken by the user that day was with those of one or more additional users . A user may be
the fewest ever recorded , that the user burned a lot of presented with user selection components representing other
calories and that more calories may be burned by lowering users who data is available for display. When a pointer is
the intensity of the exercise , and the like . The feedback panel 20 hovered over a user selection component ( e.g. , an icon
1562 may also present cautionary indicators 1570 to warn representing a user ), a snapshot of the user's information is
the user of future anticipated health events, for example , presented in a popup component, and clicking on the user
tachycardia, susceptibility to illness or overtraining ( e.g. , if selection component opens up the full user interface dis
the resting heart rate is elevated for aa few days ) , and the like. playing the user's information . In some cases , the user
An exemplary analytics system may analyze the informa- 25 selection components include certain user - specific data sur
tion presented in the day panel 1518 and determine whether rounding an image representing the user, for example, a
the user performed a specific exercise routine or activity. As graphic element indicating the user's intensity score . The
one example, given an elevated heart rate with little activity, user selection components may be provided in a grid as
the system may determine that it is possible the user drank shown or in a linear listing for easier sorting. The users
coffee at that point. In some cases , the feedback panel 1562 30 appearing in the user selection components may be sorted
may prompt the user to confirm whether he /she indeed and / or ranked based on any desired criteria, e.g. , intensity
performed that activity in a user field 1572. This user input scores, who is experiencing soreness, and the like . A user
may be displayed and / or used to improve an understanding may leave comi nts on other users ' pages .
of the user's health and exercise routines. Similarly, a user may select privacy settings to indicate
The sleep panel 1522 may include information on health 35 which aspects of his /her own data may be viewed by other
parameters of the user during sleep including, but not limited users . Because the wearable systems described herein sup
to , an overlaid graph 1573 of heart rate and movement port truly continuous monitoring, a user may wish to care
during sleep , statistics 1574 on the maximum heart rate, fully control whether and when data is transmitted wire
minimum heart rate , number of times the user awoke during lessly, stored in a remote data repository, and shared with
sleep, average movement during sleep , a sleep cycle indi- 40 others. A privacy switch as described herein may be usefully
cator 1576 showing durations spent awake , in light sleep , in employed to toggle between various privacy settings or to
deep sleep and in REM sleep , and a sleep duration graph explicitly select private or restricted times when no moni
1578 showing the number of hours slept over a period of toring should occur.
time . FIGS . 19A and 19B illustrate an exemplary user interface
A feedback panel 1580 associated with the sleep panel 45 1900 rendered on a visual display device for displaying
1522 may present information on the user's sleep including, physiological data on a plurality of users . In some cases , a
but not limited to , quantitative information, qualitative infor- user may freely compare the data of any users whose data is
mation , feedback , recommendations on future exercise rou- available and accessible , i.e. , set to an appropriate privacy
tines , and the like . The feedback panel 1580 may present a level . In some cases , comparative data may correspond to a
sleep score and / or a number of hours of sleep along with a 50 plurality of users who may be grouped together based on any
qualitative summary of the score 1582 indicating, for suitable criteria , e.g. , members of a gym , military team , and
example, whether the user slept enough , whether the sleep the like . In some cases , the user may be able to discover
was efficient or inefficient, whether the user moved around other users or comparable data by searching or performing
and how much during sleep , and the like . Based on analysis queries on any desired parameters, for example, workouts,
of the quantitative health parameters monitored during 55 activities , age groups, locations , intensities, recoveries and
sleep , the feedback panel 1580 may present one or more tips the like . For example , a user may perform a query for
1584 on adjusting sleep , for example, that the woke up a “ Workouts above a 17 Intensity in Boston for runners my
number of times during sleep and that user can try to sleep age.” The exemplary user interface may also identify or
on his side rather than on his back . suggest users with whom to exchange data based on similar
Based on analysis of the quantitative health parameters 60 parameters. Data on any number of users may be presented
monitored during the exercise routine , the feedback panel and compared including , but not limited to , 2 , 3 , 4 , 5 , 6 , 7 ,
9

1580 may also present qualitative information 1586 on the 8 , 9 , 10 , and the like .
>

user's sleep . Such information may indicate, for example , In a default option , data from the same time period ( s) may
that the user's maximum heart rate for the day's exercise be presented for all of the users . In some embodiments, time
was the highest ever recorded during sleep . The feedback 65 periods for each user may be selected independently and
panel 1580 may also present cautionary indicators 1588 to data from the selected time periods may be displayed in a
warn the user of future anticipated health events, for comparative manner on the same user interface, e.g. , in one
 US 11,185,241 B2
37 38
or more overlaid graphs. FIG . 20 illustrates a user interface soreness , and the like . Selection of any one user causes the
2000 that may be used to independently select time periods user interface specific to that user to be opened , for example,
of data for each of five users so that the data from the as shown in FIGS . 15A - 18B . The administrative user may
selected periods may be displayed together. The user inter- leave messages on the user interfaces of the different users .
face 2000 includes a representation of each user 2002a- 5 Selection of more than one user causes a user interface
2002e , optionally an indication of each user's intensity comparing the selected users to be opened, for example, as
score , a calendar component 2004 for selecting the time shown in FIGS . 19A and 19B .
periods, and a component 2006a - 2006e indicating the time The administrative user interface 2100 may include a
periods selected for each user . In some cases , data from listing of users 2104 who recently performed exercise rou
different time periods ( but, for example, for the same time 10 tines including the time of their last workout and their
duration ) for the same user may be presented on the same intensity scores , a listing of users 2106 who are off - schedule
user interface for comparative purpose, for example, to in their exercise regimen and how many days they have not
determine training progress. been exercising, a listing of users 2108 who are experiencing
In FIGS . 19A and 19B , the user interface 1900 may soreness ( that may be determined automatically based on
include a summary panel 1902 including an identification 15 intensity scores), a listing of users who are sleep -deprived
1904a - 1904b of the users ( e.g. , a real or account name) with , ( that may be determined automatically based on sleep data ),
optionally, a picture or photo corresponding to the user . In and the like . The user interface 2100 may also display a
some cases , the summary panel 1902 may also display calendar or portion of a calendar 2110 indicating training
certain information associated with the users, for example, times for different users . The calendar feature enables the
their intensity scores . 20 administrative user to review exercise schedules over time
A workout panel 1908 may present quantitative informa- and understand how well individuals or teams are meeting
tion on the users ' health and exercise routines, for example, goals . For example, the administrative user may determine
an overlaid graph 1910 of the users ' continuous heart rate that an individual is undertraining if his intensity for the day
during the exercise , statistics 1912 on the users' maximum was 18 whereas the team average was 14 .
heart rate, average heart rate, duration of exercise , number 25 In any of the exemplary user interfaces disclosed herein ,
of steps taken and calories expended , zones 1914 in which color coding may be used to indicate categories of any
the users ' maximum heart rate fell during the exercise , and parameter. For example , in a day panel of a user interface ,
an overlaid graph 1916 of the intensity scores over a period color coding may be used to indicate whether aa user's day
of time (e.g. , seven days ). A feedback panel 1918 associated was difficult (e.g. , with the color red) , tapering ( e.g. , with the
with the workout panel 1908 may present comparative 30 color yellow ) , or a day off from training (e.g. , with the color
qualitative information on the users ' exercise routines blue) .
including , but not limited to , whether the users were work- Exemplary embodiments enable selected qualitative and /
ing out the same which user had a more difficult or quantitative data from any of the user interfaces disclosed
workout, the comparative efficiencies of the users , and the herein to be selected, packaged and exported to an external
like . Similarly, a day panel and a sleep panel may present 35 application , computational device or webpage ( e.g. , a blog )
comparative information for the selected users . for display, storage and analysis . The data may be selected
The analytics system may analyze comparative data based on any desired characteristic including, but not limited
among a plurality of users and provide rankings of individu to , gender, age , location , activity, intensity level , and any
als , teams and groups of individuals (e.g. , employees of a combinations thereof. An online blog may be presented to
company, members of a gym) based on , for example , 40 display the data and allow users to comment on the data .
average intensity scores . For each user, the analytics system
may calculate and display percentile rankings of the user V. EXEMPLARY COMPUTING DEVICES
with respect to all of the users in a community in terms of,
for example, intensity scores, quality of sleep, and the like . Various aspects and functions described herein may be
Exemplary embodiments also provide user interfaces to 45 implemented as hardware, software or a combination of
enable intuitive and efficient monitoring of a plurality of hardware and software on one or more computer systems .
users by an individual with administrative powers to view Exemplary computer systems that may be used include , but
the users ' health data . Such an administrative user may be a are not limited to , personal computers, embedded computing
physical instructor, trainer or coach who may use the inter- systems , network appliances , workstations, mainframes ,
face to manage his /her clients ' workout regimen . 50 networked clients, servers , media servers , application serv
FIGS . 21A and 21B illustrate an exemplary user interface ers , database servers , web servers, virtual servers, and the
2100 viewable by an administrative user, including a select- like. Other examples of computer systems that may be used
able and editable representation or listing 2102 of the users include, but are not limited to , mobile computing devices ,
( e.g. , a trainer's clients) whose health information is avail- such as wearable devices, cellular phones and personal
able for display. When a mouse is hovered over a user 55 digital assistants , and network equipment, such as load
selection component (e.g. , an icon representing a user ), a balancers, routers and switches .
snapshot of the user's information is presented in a popup FIG . 22 is a block diagram of an exemplary computing
component, and clicking on the user selection component device 2200 that may be used in to perform any of the
opens up the full user interface displaying the user's infor- methods provided by exemplary embodiments. The com
mation . In some cases , the user selection components 60 puting device may be configured as an embedded system in
include certain user -specific data surrounding an image the integrated circuit board ( s ) of a wearable physiological
representing the user, for example, a graphic element indi- measurements system and /or as an external computing
cating the user's intensity score . The user selection compo- device that may receive data from a wearable physiological
nents in the listing 2102 may be provided in a grid as shown measurement system .
or in a linear listing for easier sorting. The users appearing 65 The computing device 2200 includes one or more non
in the listing 2102 may be sorted and / or ranked based on any transitory computer - readable media for storing one or more
desired criteria , e.g. , intensity scores , who is experiencing computer -executable instructions or software for imple
 US 11,185,241 B2
39 40
menting exemplary embodiments. The non -transitory com- card bus network adapter, wireless network adapter, USB
puter -readable media may include , but are not limited to , one network adapter, modem or any other device suitable for
or more types of hardware memory, non -transitory tangible interfacing the computing device 2200 to any type of
media (for example, one or more magnetic storage disks , network capable of communication and performing the
one or more optical disks, one or more USB flash drives ), 5 operations described herein . Moreover, the computing
and the like . For example, memory 2206 included in the device 2200 may be any computer system , such as a
computing device 2200 may store computer- readable and workstation, desktop computer, server , laptop , handheld
computer -executable instructions or software for imple- computer, tablet computer ( e.g. , the iPad® tablet computer ),
menting exemplary embodiments. The computing device mobile computing or communication device ( e.g. , the
2200 also includes processor 2202 and associated core 2204 , 10 iPhone® communication device ), or other form of comput
and optionally, one or more additional processor ( s) 2202 ing or telecommunications device that is capable of com
and associated core (s ) 2204 ' ( for example, in the case of munication and that has sufficient processor power and
computer systems having multiple processors /cores ), for memory capacity to perform the operations described
executing computer -readable and computer -executable herein .
instructions or software stored in the memory 2206 and 15 The wearable physiological measurement system may
other programs for controlling system hardware. Processor record and transmit at least the following types of data to an
2202 and processor ( s) 2202 ' may each be a single core external computing system , mobile communication system
processor or multiple core (2204 and 2204 ' ) processor. or the Internet: raw continuously -detected data (e.g. , heart
Virtualization may be employed in the computing device rate data , movement data, galvanic skin response data ) and
2200 so that infrastructure and resources in the computing 20 processed data based on the raw data (e.g. , RR intervals
device may be shared dynamically. A virtual machine 2214 determined from the heart rate data ) . Transmission modes
may be provided to handle a process running on multiple may be wired ( e.g. , using USB stick inserted into a USB port
processors so that the process appears to be using only one on the system ) or wireless ( e.g. , using a wireless transmit
computing resource rather than multiple computing ter ). The raw and processed data may be transmitted together
resources . Multiple virtual machines may also be used with 25 or separately using different transmission modes . Since a
one processor. raw data file is typically substantially larger than a processed
Memory 2206 may include a computer system memory or data file, the raw data file may be transmitted using WiFi or
random access memory , such as DRAM , SRAM , EDO a USB stick, while the processed data file may be transmit
RAM , and the like . Memory 2206 may include other types ted using Bluetooth .
of memory as well , or combinations thereof. 30 An exemplary wearable system may include a 2G , 3G or
A user may interact with the computing device 2200 4G chip that wirelessly uploads all data to the website
through a visual display device 2218 , such as a computer disclosed herein without requiring any other external device .
or, which may display one or more user interfaces A 3G or 4G chip may be used preferably as a 2G connection
2220 that may be provided in accordance with exemplary on a Nokia 5800 was found to transfer data at a rate of 520
embodiments . The visual display device 2218 may also 35 kbps using 1.69 W , while aa 3G connection transferred at 960
display other aspects , elements and / or information or data kbps using 1.73 W. Therefore , the 3G chip would use
associated with exemplary embodiments, for example , negligibly more power for almost twice the transfer speed ,
views of databases , photos, and the like . The computing thereby halving half the transfer time and using much less
device 2200 may include other I/ O devices for receiving energy from the battery.
input from a user, for example, a keyboard or any suitable 40 In some cases , the wearable system may opportunistically
multi-point touch interface 2208 , a pointing device 2210 transfer data when in close proximity to a streaming outlet.
9

( e.g. , a mouse ) . The keyboard 2208 and the pointing device For example, the system may avoid data transmission when
2210 may be coupled to the visual display device 2218. The it is not within close proximity of a streaming outlet, and ,
computing device 2200 may include other suitable conven- when nearby a streaming outlet (e.g. , a linked phone ), may
tional I/O peripherals. 45 send the data to the external device via Bluetooth and to the
The computing device 2200 may also include one or more Internet via the external device . This is both convenient and
storage devices 2224 , such as a hard - drive, CD - ROM , or " free” in the sense that it utilizes existing cellular data plans .
other computer readable media , for storing data and com- Limiting the frequency with which data is streamed
puter - readable instructions and / or software that implement increases the wearable system's battery life. In one non
exemplary methods as taught herein . Exemplary storage 50 limiting example, the system may be set to stream automati
device 2224 may also store one or more databases 2026 for cally in the morning and following a time stamp. Regardless
storing any suitable information required to implement of the data transmission scheme, the system stores all the
exemplary embodiments. The databases may be updated by data it collects . Data may also be streamed on demand by a
a user or automatically at any suitable time to add , delete or user, for example, by turning a physical component on the
update one or more items in the databases. 55 system and holding it or by initiating a process on the mobile
The computing device 2200 may include a network application or receiving device . In some embodiments, the
interface 2212 configured to interface via one or more data transmission frequency may be automatically adjusted
network devices 2222 with one or more networks, for based on one or more physiological parameters, e.g. , heart
example, Local Area Network (LAN ), Wide Area Network rate . For example , higher heart rates may prompt more
(WAN ) or the Internet through a variety of connections 60 frequent and real -time streaming transmission of data .
including , but not limited to , standard telephone lines , LAN The computing device 2200 may run any operating sys
or WAN links ( for example , 802.11 , T1 , T3 , 56 kb, X.25 ) , tem 2216 , such as any of the versions of the Microsoft®
broadband connections ( for example, ISDN , Frame Relay, Windows® operating systems , the different releases of the
ATM ), wireless connections, controller area network Unix and Linux operating systems, any version of the
( CAN ), or some combination of any or all of the above . The 65 MacOS® for Macintosh computers, any embedded operat
network interface 2212 may include a built - in network ing system , any real - time operating system , any open source
adapter, network interface card, PCMCIA network card, operating system , any proprietary operating system , any
 US 11,185,241 B2
41 42
operating systems for mobile computing devices, or any shown, the processor 2310 is connected to other system
other operating system capable of running on the computing placements, including a memory 2312 , by the bus 2314 .
device and performing the operations described herein . In The memory 2312 may be used for storing programs and
exemplary embodiments, the operating system 2216 may be data during operation of the computer system 2300. Thus,
run in native mode or emulated mode. In an exemplary 5 the memory 2312 may be a relatively high performance,
embodiment, the operating system 2216 may be run on one volatile, random access memory such as a dynamic random
or more cloud machine instances. access memory (DRAM ) or static memory ( SRAM ). How
ever, the memory 2312 may include any device for storing
VI . EXEMPLARY NETWORK ENVIRONMENTS data, such a disk drive or other non - volatile storage device ,
10 such as flash memory or phase - change memory (PCM) .
Various aspects and functions of the implementations may Various embodiments can organize the memory 2312 into
be distributed among one or more computer systems con- particularized and , in some cases , unique structures to
figured to provide a service to one or more client computers, perform the aspects and functions disclosed herein .
or to perform an overall task as part of aa distributed system . Components of the computer system 2300 may be
Additionally, aspects may be performed on a client-server or 15 coupled by an interconnection element such as the bus 2314 .
multi - tier system that includes components distributed The bus 2314 may include one or more physical busses ( for
among one or more server systems that perform various example, buses between components that are integrated
functions . Thus, the implementations are not limited to within the same machine ) and may include any communi
executing on any particular system or group of systems. cation coupling between system placements including spe
Further, aspects may be implemented in software, hardware 20 cialized or standard computing bus technologies such as
or firmware , or any combination thereof. Thus, aspects may IDE , SCSI , PCI and InfiniBand. Thus, the bus 2314 enables
be implemented within methods, acts , systems , system communications ( for example , data and instructions ) to be
placements and components using a variety of hardware and exchanged between system mponents of the computer
software configurations, and they are not limited to any system 2300 .
particular distributed architecture, network or communica- 25 Computer system 2300 also includes one or more inter
tion protocol. Furthermore, aspects may be implemented as face devices 2316 , such as input devices , output devices and
specially -programmed hardware and / or software . combination input /output devices . The interface devices
FIG . 23 is aa block diagram of an exemplary distributed 2316 may receive input, provide output, or both . For
computer system 2300 in which various aspects and func- example, output devices may render information for external
tions may be practiced . The distributed computer system 30 presentation . Input devices may accept information from
2300 may include one or more computer systems . For external sources . Examples of interface devices include, but
example, as illustrated, the distributed computer system are not limited to , keyboards, mouse devices, trackballs,
2300 includes three computer systems 2302 , 2304 and 2306 . microphones , touch screens , printing devic display
As shown , the computer systems 2302 , 2304 , 2306 are screens , speakers, network interface cards, and the like. The
interconnected by, and may exchange data through, a com- 35 interface devices 2316 allow the computer system 2300 to
munication network 2308. The network 2308 may include exchange information and communicate with external enti
any communication network through which computer sys- ties , such as users and other systems.
tems may exchange data . To exchange data via the network Storage system 2318 may include one or more computer
2308 , the computer systems and the network may use readable and computer-writeable non - volatile and non - tran
various methods, protocols and standards including, but not 40 sitory storage media on which computer - executable instruc
limited to , token ring, Ethernet, wireless Ethernet, Blu- tions are encoded that define a program to be executed by the
etooth , TCP / IP , UDP, HTTP, FTP, SNMP, SMS , MMS , SS7 , processor. The storage system 2318 also may include infor
JSON , XML , REST, SOAP, CORBA , HOP, RMI , DCOM mation that is recorded on or in the media , and this infor
and Web Services. To ensure data transfer is secure , the mation may be processed by the program . More specifically,
computer systems may transmit data via the network using 45 the information may be stored in one or more data structures
a variety of security measures including, but not limited to , specifically configured to conserve storage space or increase
TSL , SSL and VPN . While the distributed computer system data exchange performance. The instructions may be per
2300 illustrates three networked computer systems , the sistently stored as encoded signals, and the instructions may
distributed computer system may include any number of cause a processor to perform any of the functions described
computer systems , networked using any medium and com- 50 herein . A medium that can be used with various embodi
munication protocol. ments may include, for example, optical disk, magnetic disk
Various aspects and functions may be implemented as or flash memory , among others. In operation , the processor
specialized hardware or software executing in one or more 2310 or some other controller may cause data to be read
computer systems . As depicted , the computer system 2300 from the non - transitory recording media into another
includes a processor 2310 , a memory 2312 , a bus 2314 , an 55 memory , such as the memory 2312 , that allows for faster
interface 2316 and a storage system 2318. The processor access to the information by the processor than does the
2310 , which may include one or more microprocessors or storage medium included in the storage system 2318. The
other types of controllers, can perform a series of instruc- memory may be located in the storage system 2318 and / or
tions that manipulate data . The processor 2310 may be a in the memory 2312. The processor 2310 may manipulate
well -known commercially -available processor such as an 60 the data within the memory 2312 , and then copy the data to
Intel Pentium , Intel Atom , ARM Processor, Motorola Pow- the medium associated with the storage system 2318 after
erPC , SGI MIPS , Sun UltraSPARC or Hewlett- Packard processing is completed. A variety of components may
PA -RISC processor, or may be any other type of processor manage data movement between the media and the memory
or controller as many other processors and controllers are 2312 , and the present disclosure is not limited thereto .
available . The processor 2310 may be a mobile device or 65 Further, the implementations are not limited to a particu
smart phone processor, such as an ARM Cortex processor, a lar memory system or storage system . Although the com
Qualcomm Snapdragon processor or an Apple processor. As puter system 2300 is shown by way of example as one type
 US 11,185,241 B2
43 44
of computer system upon which various aspects and func- IBM of Armonk , N.Y. However, a computer system running,
tions may be practiced , aspects are not limited to being for example, SQL Server may be able to support both
implemented on the computer system . Various aspects and aspects in accord with the implementations and databases
functions may be practiced on one or more computers for sundry applications not within the scope of the disclo
having different architectures or components than that 5 sure .
shown in the illustrative figures. For instance, the computer FIG . 24 is a diagram of an exemplary network environ
system 2300 may include specially -programmed , special- ment 2400 suitable for a distributed implementation of
purpose hardware , such as for example, an application- exemplary embodiments. The network environment 2400
specific integrated circuit ( ASIC ) tailored to perform a may include one or more servers 2402 and 2404 coupled to
particular operation disclosed herein . Another embodiment 10 one or more clients 2406 and 2408 via a communication
may perform the same function using several general- network 2410. The network interface 2212 and the network
purpose computing devices running MAC OS® System X device 2222 of the computing device 2200 enable the
with Motorola PowerPC® processors and several special- servers 2402 and 2404 to communicate with the clients 2406
ized computing devices running proprietary hardware and and 2408 via the communication network 2410. The com
operating systems . 15 munication network 2410 may include, but is not limited to ,
The computer system 2300 may include an operating the Internet, an intranet, a LAN (Local Area Network ), a
system that manages at least a portion of the hardware WAN ( Wide Area Network ), a MAN (Metropolitan Area
placements included in computer system 2300. A processor Network ), a wireless network , an optical network , and the
or controller, such as processor 2310 , may execute an like . The communication facilities provided by the commu
operating system which may be, among others, a Windows- 20 nication network 2410 are capable of supporting distributed
based operating system ( for example , Windows NT, Win- implementations of exemplary embodiments.
dows 2000/ME , Windows XP, Windows 7 , or Windows In an exemplary embodiment, the servers 2402 and 2404
Vista ) available from the Microsoft Corporation , a MAC may provide the clients 2406 and 2408 with computer
OS® System X operating system available from Apple readable and / or computer -executable components or prod
Computer, one of many Linux - based operating system dis- 25 ucts under a particular condition , such as a license agree
tributions ( for example, the Enterprise Linux operating ment. For example, the computer - readable and / or computer
system available from Red Hat Inc. ), a Solaris operating executable components or products may include those for
system available from Sun Microsystems , or a UNIX oper- providing and rendering any of the user interfaces disclosed
ating systems available from various sources . The operating herein . The clients 2406 and 2408 may provide and render
system may be a mobile device or smart phone operating 30 an exemplary graphical user interface using the computer
system , such as Windows Mobile , Android or iOS . Many readable and / or computer -executable components and prod
other operating systems may be used , and embodiments are ucts provided by the servers 2402 and 2404 .
not limited to any particular operating system . Alternatively, in another exemplary embodiment, the cli
The processor and operating system together define a ents 2406 and 2408 may provide the servers 2402 and 2404
computing platform for which application programs in high- 35 with computer-readable and computer -executable compo
level programming languages may be written . These com- nents or products under a particular condition, such as a
ponent applications may be executable , intermediate ( for license agreement. For example, in an exemplary embodi
example, C # or JAVA bytecode) or interpreted code which ment, the servers 2402 and 2404 may provide and render an
communicate over a communication network ( for example, exemplary graphical user interface using the computer
the Internet) using a communication protocol ( for example , 40 readable and / or computer -executable components and prod
TCP/IP) . Similarly, functions may be implemented using an ucts provided by the clients 2406 and 2408 .
object- oriented programming language, such as SmallTalk , FIG . 25 is aa flow chart of a method 2500 according to an
JAVA , C ++ , Ada , or C # ( C -Sharp ). Other object -oriented implementation.
programming languages may also be used . Alternatively, As shown in step 2502 , the method 2500 may include
2

procedural, scripting , or logical programming languages 45 providing a strap with a sensor and a heart rate monitoring
may be used. system . The strap may be shaped and sized to fit about an
Additionally, various functions may be implemented in a appendage. For example , the strap may be any of the straps
non - programmed environment ( for example, documents described herein , including , without limitation, a bracelet.
created in HTML , XML or other format that, when viewed The heart rate monitoring system may be configured to
in a window of a browser program , render aspects of a 50 provide two or more different modes for detecting a heart
graphical- user interface or perform other functions ). Further, rate of a wearer of the strap . The modes may include the use
various embodiments may be implemented as programmed of optical detectors (e.g. , light detectors ), light emitters ,
or non -programmed placements, or any combination motion sensors, a processing module, algorithms, other
thereof. For example, a web page may be implemented using sensors, a peak detection technique, a frequency domain
HTML while aa data object called from within the web page 55 technique, variable optical characteristics, non -optical tech
may be written in C ++ . Thus, the implementations are not niques, and so on .
limited to a specific programming language and any suitable As shown in step 2504 , the method 2500 may include
programming language could also be used . detecting a signal from the sensor. The signal may be
A computer system included within an embodiment may detected by one or more sensors , which may include any of
perform functions outside the scope of the embodiment. For 60 the sensors described herein . The signal may include , with
instance , aspects of the system may be implemented using out limitation , one or more signals associated with the heart
an existing product. Aspects of the system may be imple- rate of the user, other physiological signals , an optical signal ,
mented on database management systems such as SQL signals based on movement, signals based on environmental
Server available from Microsoft of Seattle , Wash .; Oracle factors , status signals (e.g. , battery life ), historical informa
Database from Oracle of Redwood Shores, Calif .; and 65 tion , and so on .
MySQL from Sun Microsystems of Santa Clara , Calif.; or As shown in step 2506 , the method 2500 may include
integration software such as WebSphere middleware from determining a condition of the heart rate monitoring system ,
 US 11,185,241 B2
45 46
which may be based upon the signal. The condition may include the use of the algorithms discussed herein . The
include , without limitation, an accuracy of heart rate detec- method 2600 may also include generating periodic updates
tion determined using a statistical analysis to provide a to the user concerning the exercise activity. The method
confidence level in the accuracy, a power consumption, a 2600 may also include determining a qualitative assessment
battery charge level, a user activity , a location of the sensor 5 of the exercise activity and communicating the qualitative
or motion of the sensor, an environmental or contextual assessment to the user .
condition ( e.g. , ambient light conditions ), a physiological As shown in step 2608 , the method 2600 may include
condition, an active condition , an inactive condition, and so detecting a recovery state . This may include automatically
on . This may include detecting a change in the condition, detecting a physical recovery state of the user. The recovery
responsively selecting a different one of the two or more 10 state may be detected through the use of one or more sensors
different modes , and storing additional continuous heart rate as described herein . The recovery state may be sent to a
data obtained using at least one of the two or more different server that, e.g. , performs step 2610 described below .
modes . As shown in step 2610 , the method 2600 may include
As shown in step 2508 , the method 2500 may include generating an assessment of the recovery state . This may
selecting one of the two or more different modes for detect- 15 include generating a quantitative assessment of the physical
ing the heart rate based on the condition . For example, based recovery state . Generating a quantitative assessment may
on the motion status of the user, the method may automati- include the use of the algorithms discussed herein . Gener
cally and selectively activate one or more light emitters to ating a quantitative assessment of the physical recovery state
determine aa heart rate of the user. The system may also or may include analyzing the physical recovery state on a
instead determine the type of sensor to use at a given time 20 remote server. The method 2600 may also include generat
based on the level of motion , skin temperature , heart rate , ing periodic updates to the user concerning the physical
and the like . Based on a combination of these factors the recover state . The method 2600 may also include determin
system may selectively choose which type of sensor to use ing a qualitative assessment of the recovery state and
in monitoring the heart rate of the user. A processor or the communicating the qualitative assessment to the user .
like may be configured to select one of the modes . For 25 As shown in step 2612 , the method 2600 may include
example , if the condition is the accuracy of heart rate analyzing the assessments, i.e. , analyzing the quantitative
detection determined using a statistical analysis to provide a assessment of the exercise activity and the quantitative
confidence level in the accuracy, the processor may be assessment of the physical recovery. The analysis may
configured to select a different one of the modes when the include the use of one or more of the algorithms described
confidence level is below a predetermined threshold . 30 herein, a statistical analysis , and so on . The analysis may
As shown in step 2510 , the method 2500 may include include the use of a remote server .
storing continuous heart rate data using one of the two or As shown in step 2614 , the method 2600 may include
more different modes . This may include communicating the generating a recommendation . This may include automati
continuous heart rate data from the strap to a remote data cally generating a recommendation on a change to an
repository. This may also or instead including storing the 35 exercise routine of the user based on the analysis performed
data locally, e.g. , on a memory included on the strap . The in step 2612. This may also or instead include determining
memory may be removable, e.g. , via a data card or the like, a qualitative assessment of the exercise activity and / or
or the memory may be permanently attached /integral with recovery state, and communicating the qualitative assess
the strap or a component thereof. The stored data (e.g. , heart ment( s ) to the user. The recommendation may be generated
rate data ) may be for the user's private use , for example , 40 on a remote server . The recommendation may be commu
when in a private setting, or the data may be shared when in nicated to the user in an electronic mail , it may be presented
a shared setting (e.g. , on a social networking site or the like ) . to the user in a web page , other communications interface,
The method 2500 may further include the use of a privacy or the like . Generating the recommendation may be based
switch operable by the user to controllably restrict commu- upon a number of cycles of exercise and rest .
nication of a portion of the data , e.g. , to the remote data 45 The method 2600 described above, or any of the methods
repository. discussed herein , may also or instead be implemented on a
FIG . 26 is aa flow chart of a method 2600 according to an computer program product including non - transitory com
implementation. puter executable code embodied in a non - transitory com
As shown in step 2602 , the method 2600 may include puter - readable medium that executes on one or more com
monitoring data from a wearable system . The wearable 50 puting devices to perform the method steps . For example ,
system may be a continuous-monitoring , physiological mea- code may be provided that performs the various steps of the
surement system worn by a user. The data may include heart methods described herein .
rate data, other physiological data , summary data, motion
data, fitness data , activity data , or any other data described VII . EQUIVALENTS
herein or otherwise contemplated by a skilled artisan . 55
As shown in step 2604 , the method 2600 may include It is to be appreciated that embodiments of the systems ,
detecting exercise activity . This may include automatically apparatuses and methods discussed herein are not limited in
detecting exercise activity of the user. The exercise activity application to the details of construction and the arrange
may be detected through the use of one or more sensors as ment of components set forth in the following description or
described herein. The exercise activity may be sent to a 60 illustrated in the accompanying drawings. Exemplary sys
server that, e.g. , performs step 2606 described below. tems , apparatuses and methods are capable of implementa
As shown in step 2606 , the method 2600 may include tion in other embodiments and of being practiced or of being
generating an assessment of the exercise activity. This may carried out in various ways . Examples of specific imple
include generating a quantitative assessment of the exercise mentations are provided herein for illustrative purposes only
activity. Generating a quantitative assessment of the exercise 65 and are not intended to be limiting. In particular, acts ,
activity may include analyzing the exercise activity on a elements and features discussed in connection with any one
remote server. Generating a quantitative assessment may or more embodiments are not intended to be excluded from
 US 11,185,241 B2
47 48
a similar role in any other embodiments. One or more sors or other programmable devices or processing circuitry,
aspects and embodiments disclosed herein may be imple- along with internal and / or external memory. This may also ,
mented on one or more computer systems coupled by a or instead, include one or more application specific inte
network ( e.g. , the Internet ). grated circuits , programmable gate arrays , programmable
The phraseology and terminology used herein are for the 5 array logic components, or any other device or devices that
purpose of description and should not be regarded as lim may be configured to process electronic signals. It will
iting . Any references to embodiments or elements or acts of further be appreciated that a realization of the processes or
the systems and methods herein referred to in the singular devices described above may include computer -executable
may also embrace embodiments including a plurality of code created using a structured programming language such
these elements, and any references in plural to any embodi- 10 as C , an object oriented programming language such as C ++ ,
ment or element or act herein may also embrace embodi or any other high - level or low - level programming language
ments including only a single element. The use herein of (including assembly languages, hardware description lan
terms like “ including , " " comprising,” “ having, " " contain guages , and database programming languages and technolo
ing, ” “ involving , ” and variations thereof, is meant to encom
pass the items listed thereafter and equivalents thereof as is gies ) that may be stored, compiled or interpreted to run on
one of the above devices, as well as heterogeneous combi
well as additional items . Any references front and back , left
and right, top and bottom , upper and lower, and vertical and nations of processors, processor architectures, or combina
horizontal, are intended for convenience of description , not tions of different hardware and software .
to limit the present systems and methods or their compo- Thus , in one aspect , each method described above and
nents to any one positional or spatial orientation . 20 combinations thereof may be embodied in computer execut
In describing exemplary embodiments , specific terminol- able code that, when executing on one or more computing
ogy is used for the sake of clarity. For purposes of descrip- devices, performs the steps thereof. In another aspect , the
tion, each specific term is intended to , at least , include all methods may be embodied in systems that perform the steps
technical and functional equivalents that operate in a similar thereof, and may be distributed across devices in a number
manner to accomplish a similar purpose . Additionally, in 25 of ways , or all of the functionality may be integrated into a
some instances where a particular exemplary embodiment dedicated, standalone device or other hardware. The code
includes a plurality of system elements or method steps , may be stored in a non - transitory fashion in a computer
those elements or steps may be replaced with a single memory , which may be a memory from which the program
element or step . Likewise , a single element or step may be executes ( such as random access memory associated with a
replaced with a plurality of elements or steps that serve the 30 processor), or a storage device such as a disk drive, flash
same purpose . Further, where parameters for various prop- memory or any other optical, electromagnetic, magnetic,
erties are specified herein for exemplary embodiments, those infrared or other device or combination of devices. In
parameters may be adjusted up or down by 1/ 10th , 1/ sth , another aspect , any of the systems and methods described
1/3rd , 2nd , and the like , or by rounded - off approximations above may be embodied in any suitable transmission or
thereof, unless otherwise specified. Moreover, while exem- 35 propagation medium carrying computer - executable code
plary embodiments have been shown and described with and / or any inputs or outputs from same . In another aspect ,
references to particular embodiments thereof, those of ordi- means for performing the steps associated with the processes
nary skill in the art will understand that various substitutions described above may include any of the hardware and / or
and alterations in form and details may be made therein software described above . All such permutations and com
without departing from the scope of the disclosure. Further 40 binations are intended to fall within the scope of the present
still , other aspects , functions and advantages are also within disclosure.
the scope of the disclosure. It should further be appreciated that the methods above
Embodiments disclosed herein may be combined with are provided by way of example. Absent an explicit indica
other embodiments disclosed herein in any manner consis- tion to the contrary, the disclosed steps may be modified ,
tent with at least one of the principles disclosed herein , and 45 supplemented, omitted , and / or re -ordered without departing
references to “ an embodiment,” “ one embodiment, ” “ an from the scope of this disclosure .
exemplary embodiment, " " some embodiments , " " some The method steps of the invention ( s ) described herein are
exemplary embodiments, ” “ an alternate embodiment, ” intended to include any suitable method of causing such
“ various embodiments, ” “ exemplary embodiments, ” and the method steps to be performed , consistent with the patent
like , are not necessarily mutually exclusive and are intended 50 ability of the following claims , unless a different meaning is
to indicate that a particular feature , structure , characteristic expressly provided or otherwise clear from the context. So
or functionality described may be included in at least one for example performing the step of X includes any suitable
embodiment. The appearances of such terms herein are not method for causing another party such as a remote user , a
necessarily all referring to the same embodiment . remote processing resource ( e.g. , a server or cloud com
Exemplary flowcharts are provided herein for illustrative 55 puter ) or a machine to perform the step of X. Similarly,
purposes and are non - limiting examples of methods. One of performing steps X , Y and Z may include any method of
ordinary skill in the art will recognize that exemplary directing or controlling any combination of such other
methods may include more or fewer steps than those illus- individuals or resources to perform steps X , Y and Z to
trated in the exemplary flowcharts, and that the steps in the obtain the benefit of such steps . Thus method steps of the
exemplary flowcharts may be performed in aa different order 60 implementations described herein are intended to include
than the order shown in the illustrative flowcharts . any suitable method of causing one or more other parties or
The above systems, devices, methods, processes, and the entities to perform the steps , consistent with the patentability
like may be realized in hardware, software , or any combi- of the following claims , unless a different meaning is
nation of these suitable for the control, data acquisition, and expressly provided or otherwise clear from the context. Such
data processing described herein . This includes realization 65 parties or entities need not be under the direction or control
in one or more microprocessors, microcontrollers, embed- of any other party or entity, and need not be located within
ded microcontrollers, programmable digital signal proces- a particular jurisdiction.
 US 11,185,241 B2
49 50
It will be appreciated that the methods and systems two or more different modes , and to store the continuous
described above are set forth by way of example and not of heart rate data in the memory.
limitation . Numerous variations, additions, omissions , and 11. The device of claim 10 wherein the processor is
other modifications will be apparent to one of ordinary skill further configured to communicate the continuous heart rate
in the art. In addition, the order or presentation of method 5 data to a remote data repository.
steps in the description and drawings above is not intended 12. A method comprising:
to require this order of performing the recited steps unless a providing a strap shaped and sized to fit about an append
particular order is expressly required or otherwise clear from age , the strap including a sensor with an optical detec
the context . Thus, while particular embodiments have been tor for capturing an optical signal indicative of reflected
shown and described , it will be apparent to those skilled in 10 light from aa skin of a wearer of the strap and aa heart rate
the art that various changes and modifications in form and monitoring system configured to provide two or more
details may be made therein without departing from the different modes for detecting a heart rate of a wearer of
spirit and scope of this disclosure and are intended to form the strap based on the optical signal ;
a part of the invention as defined by the following claims , detecting the optical signal from the sensor ;
which are to be interpreted in the broadest sense allowable 15
by law. determining a confidence level in an accuracy of the heart
What is claimed is : rate of the wearer using a statistical analysis of the
1. A device comprising : optical signal;
a strap shaped and sized to fit about an appendage; calculating an instantaneous heart rate for the wearer in a
a sensor coupled to the strap, the sensor including an 20 first mode using a time domain technique to process the
optical detector providing an optical signal indicative optical signal when the confidence level is above a
of reflected light from a skin of a wearer of the strap ; predetermined threshold and calculating the instanta
a heart rate monitoring system coupled to the strap and neous heart rate in second mode sing a frequency
configured to provide two or more different modes for domain technique to process the optical signal when the
detecting a heart rate of the wearer of the strap based on 25 confidence level is below the predetermined threshold ;
the optical signal; and
a memory; and storing continuous heart rate data for the wearer based on
a processor coupled to the strap and configured to mea the instantaneous heart rate .
sure a confidence level in an accuracy of a heart rate of
the wearer of the strap using a statistical analysis of the 30 nicatingThethemethod
13. of claim 12 further comprising commu
optical signal, the processor further configured to cal remote data repository . heart rate data from the strap to a
continuous
culate an instantaneous heart rate for the wearer in a 14. The method of claim 12 further comprising, detecting
first mode using a time domain technique to process the a change in the confidence level , responsively selecting a
optical signal when the confidence level is above a
predetermined threshold and to calculate the instanta- 35 different one of the two or more different modes, and storing
neous heart rate in a second mode using a frequency additional continuous heart rate data obtained using the
domain technique to process the optical signal when the different one of the two or more different modes .
confidence level is below the predetermined threshold . is associatedmethod
15. The of claim 12 wherein the confidence level
with an RR interval in the heart rate .
2. The device of claim 1 wherein the different modes
include at least one mode using light emitted from a light 40 16. The method of claim 12 wherein the time domain
source on the strap and detected by the optical detector. technique includes a peak detection algorithm that evaluates
3. The device of claim 2 wherein the different modes the instantaneous heart rate based on time domain peaks in
include one or more modes using variable optical charac- the optical signal.
teristics of the light source including at least one of a 17. The method of claim 12 wherein the predetermined
brightness of the light source , a duty cycle of the light 45 threshold is an adaptive threshold .
source , and a color of the light source . 18. The method of claim 17 wherein the adaptive thresh
4. The device of claim 1 further comprising an accessory old is determined based on previous confidence levels in the
removably and replaceably coupled to the device , the acces- accuracy of the heart rate .
sory including an power source configured to charge a 19. A computer program product for operating a wearable
battery of the device without a wired coupling to other 50 physical monitoring system including a sensor with an
power sources. optical detector for capturing an optical signal indicative of
5. The device of claim 1 wherein the different modes reflected light from a skin of a wearer of the wearable
include at least one non -optical mode . physical monitoring system , wherein the computer program
6. The device of claim 1 wherein the confidence level is product comprises non - transitory computer executable code
associated with an RR interval in the heart rate . 55 embodied in a computer readable medium that, when
7. The device of claim 1 wherein the time domain executing on the wearable physical monitoring system ,
technique includes a peak detection algorithm that evaluates performs the steps of:
the instantaneous heart rate based on time domain peaks in detecting the optical signal from the optical detector of the
the optical signal. sensor;
8. The device of claim 1 wherein the predetermined 60 determining a confidence level in an accuracy of the heart
threshold is an adaptive threshold . rate of the wearer using a statistical analysis of the
9. The device of claim 8 wherein the adaptive threshold is optical signal;
determined based on previous confidence levels in the calculating an instantaneous heart rate for the wearer in a
accuracy of the heart rate . first mode using a time domain technique to process the
10. The device of claim 1 wherein the processor is further 65 optical signal when the confidence level is above a
configured to operate the heart rate monitoring system to predetermined threshold and calculating the instanta
obtain continuous heart rate data using a selected one of the neous heart rate in a second mode using a frequency
 US 11,185,241 B2
51 52
domain technique to process the optical signal when the
confidence level is below the predetermined threshold ;
and
storing continuous heart rate data using the one of the two
or more different modes for detecting the heart rate . 5
20. The computer program product of claim 19 wherein
the confidence level is associated with an RR interval in the
heart rate .
*