VISVESVARAYA TECHNOLOGICAL UNIVERSITY

BELAGAVI – 590 018

A Project Report
on
“DESIGN AND IMPLEMENTATION OF SLEEP APNEA
DETECTION SYSTEM”

By
POORNIMA S [poornimarao831@gmail.com] 8762748483
RAHUL N [rahul.nagaraju@outlook.com] 8431063668
SANJAY K [sanjay8310761538@gmail.com] 8310761538
SUMANTH C GOWDA [gowdasumanthc@gmail.com] 9141069850

Submitted in partial fulfillment of requirement for the award of the 8th sem
degree of

BACHELOR OF ENGINEERING
in
ELECTRONICS & COMMUNICATION ENGINEERING

under the guidance of

KALAVATHI S [kalavathisec@gmail.com] 9886941974

Assistant Professor

DEPARTMENT OF ELECTRONICS AND COMMUNICATION

ENGINEERING
Sapthagiri College of Engineering,
(Affiliated to Visvesvaraya Technological University and Approved by AICTE)
NAAC Accredited with ‘A’ Grade
Accredited by NBA
ISO 9001-2015 and 14001-2015 certified Institute
Bengaluru, Karnataka 560057
2022-2023
 ABSTRACT
Respiratory dynamic monitoring is a diagnostic tool in variety of clinical settings, including
Sleep analysis, intensive care medicine, analysis of central nervous system and physiological
disorders. Sleep apnea is defined as a 10-second interruption of airflow to the lungs during
sleep. It is usually caused by either lack of neural input from the central nervous system
(central sleep apnea) or collapse of the upper airway (obstructive sleep apnea). Automation
plays an important role in our daily life. Hand gesture recognition is the most important
implementation in the automation field. Bed positioning system states that use of hand
movements to adjust the bed position is problematic. It is proposed to demonstrate a real-time
system for changing bed position via hand gestures and simple hardware components. Patients
with disabilities are becoming more common in today's culture, yet no one is available to care
for them it is not always possible due to circumstances. To minimize the demand on nursing
staff and increases patient comfort this system is designed. The system also includes a
continuous patient monitoring system that monitors various parameters such as temperature,
oxygen levels and pulse rate. If any of these parameters exceed minimum safe levels, the
device sends an alarm signal to the doctor or caregiver via SMS. Another objective of the
system is to avoid Somniloquy by bringing the patient to consciousness.
Keywords: Caregiver, Somniloquy

INTRODUCTION
Sleep-disordered breathing (SDB) is an increasing common disorder, with at least half
of people over the age of 65 experiencing disturbed sleep, with a further 25% of children
experiencing SDB by adolescence. Obstructive Sleep Apnea, Central Sleep Apnea, Upper
Airway Resistance and obesity hyperventilation are the most common SDB observed and are
characterized by interrupted breathing with different causes. For example, the most common
sleep disorder, Obstructive Sleep Apnea, is caused by cessation of breathing due to obstructed
airways. Central Sleep Apnea, which is more common among heart failure patients, is caused
by impaired cardiovascular and breathing control systems. Due to an aging population as well
as to an increase in the obesity among the general population, the numbers of patients with
SDB is expected to rise significantly in the future. Consequently, sleep disordered research
and requirements for more convenient sleep monitoring devices are predicted to expand
rapidly.
One of the main goals of this project is to provide maximum convenience to the user
or patient during ECG measurements, especially for prolonged use. Wireless technology is
ability to generate interactive healthcare utilizing modern technology and telecommunication.
The telemetry system is useful in absence of direct contact between the patient and doctor-
physician. The wireless device employed for the efficient remote monitoring system, using
for real time, continuous and accurate information of patient heart condition. In this project
we will design wireless ECG sensor and display its output on computer screen wirelessly.
ECG method is developed by Willem Einthoven in 1900’s. ECG is one of the methods which
is used to measure the electrical activity of the heart. Human heart contains four chamber
namely left atrium, right atrium, left ventricle and right ventricle. In human heart blood enters
through two large veins: inferior and superior vena cava. The oxygen - poor blood is entered
into the right atrium from body through veins. This oxygen - poor blood forwarded to the right
ventricle, Right ventricle pushes this blood to lung. In the lung “Gas Exchange” Process is
done on the oxygen -poor blood. Here oxygen is added to the blood. The rich -oxygen blood
is pushed by lung to the left atrium, which forwards this blood to the left ventricle and finally
left ventricle supply rich - oxygen blood to the whole body.
In an attempt to address these issues, we present “Vital Core”, a novel IOT ready,
sleep monitoring device utilizing a new technique of cardiac and respiratory measurement
with polymer-based electro resistive band (ERB) sensors. Further, the device facilitates single
lead ECG and Accelerometer measurements. The microcontroller supports the latest
Bluetooth 5 wireless speed natively for data transfer and real-time streaming to Bluetooth
4.2/5 smart device or a dedicated Bluetooth 5 dongle. The device was tested to determine if it
is capable of capturing both cardiac and respiratory activity over the course of a night’s sleep.
Additional proof-of-concept experiments are performed to determine if the prototype device
is capable of accurately capturing respiration and cardiac activity.
However, IOT platforms for widespread sleep monitoring are not commonly used
today. While these technologies are developing rapidly, healthcare industry adaptation is
slow. Data quality, reliability and utility combined with ease-of-use of the device are limiting
factors for greater uptake of these technologies. ECG mainly works in two phases:
Depolarization and Re-polarization. Depolarization means mechanical contraction of the
heart chamber i.e., either atrium or ventricle, and Re- polarization means the mechanical
relaxation of the heart chamber.

OBJECTIVES OF THE PROJECT WORK

By considering the necessities, few objectives are proposed in the present work. The main
research objectives are listed below:

1. To Measure temperature level, oxygen saturation level and heart rate and displaying
it on LCD display in case of severity.
2. To change the bed position using hand gestures to maintain patient comfort when there
is a severity.
3. To avoid talking in sleep by producing sound when person starts murmuring in sleep.
 4. To Message the caretaker in case of severity in parameters.

METHODOLOGY

OBJECTIVE 1

To Measure temperature level, oxygen saturation level and heart rate and displaying it on
LCD display in case of severity.

METHODLOGY 1
1. Start.
2. Initialization of sensors.
3. Reading and monitoring values from sensors.
4. If heartbeat count per minute is greater than 100 or temperature greater than 30 degrees
Celsius or oxygen saturation level less than 90% display in LCD.
5. Next objective.

The below flowchart Fig 1.1 shows the steps taken to measure oxygen level, blood saturation
level and heart rate using sensor and displaying it on LCD display.

Fig 1.1: Flowchart to measure oxygen level, blood saturation level and heart rate using sensor and displaying it
on LCD display
OBJECTIVE 2
To change the bed position using hand gestures to maintain patient comfort when there is a
severity.
METHODLOGY 2
1. Start

2. Initialization of accelerometer sensor.

3. If the accelerometer value is greater than 350, position bed upwards.

4. If the accelerometer value is lesser than 300, position the bed downwards.

5. Next objective.

The below flowchart Fig 1.2 shows the steps taken to change the bed position using hand
gestures to maintain patient comfort when there is a severity.

Fig 1.2: Flowchart to change the bed position using hand gestures to maintain patient comfort when there is a
severity.
OBJECTIVE 3
To avoid talking in sleep by producing sound when person starts murmuring in sleep.

METHODLOGY 3
1. Start
2. Initialization of sound sensor.
3. Monitor patient murmuring.
4. If sound is greater than 30 decibels turn on vibrator and buzzer.
5. Next objective.

The below flowchart Fig 1.3 shows the steps taken to detect talking in sleep by producing
sound when person starts murmuring in sleep.

Fig 1.3: Flowchart to detect talking in sleep by producing sound when person starts murmuring in sleep.
OBJECTIVE 4
To Message the caretaker in case of severity in parameters.
METHODLOGY 4
1. Start
2. Initialization of sensors.
3. Check the sensor value whether it crosses the threshold.
4. If any value is greater than threshold send message to caretaker through telegram.
5. Stop.

The below flowchart Fig 1.4 shows the steps to message the caretaker in case of severity.

Fig 1.4: Flowchart shows the steps to message the caretaker in case of severity in parameters.
 RESULTS

Fig 2.1: Parameters measured as a result

Fig 2.2: Bed positioning to maintain patient comfort

 Fig 2.3: Murmuring/sound measured as a result

Fig 2.4: Messaging the caretaker in case of severity of parameter

CONCLUSION
The proposed sleep apnea detection system is a challenging procedure that calls for careful
consideration of many variables. To diagnose episodes of sleep apnea with a high degree of
precision, the system must be able to properly collect and analyse data from various sensors.
The choice of this technique will rely on the requirements of the system. Each approach has
advantages and limits of its own. Also, the cost for the detection system is nominal on
consideration of its advantages. Hence this model encourages practicing of sleep cycle analysis
and variations that is efficient on comparison with existing technologies.
 INNOVATION IN THE PROJECT
In recent years, there have been several innovations in sleep apnea detection systems aimed at
improving diagnosis, monitoring, and treatment of this condition. Sleep apnea is a sleep
disorder characterized by pauses in breathing or shallow breaths during sleep, leading to
disrupted sleep patterns and potential health risks. Here are some innovative developments in
sleep apnea detection systems:
Portable Monitoring Devices: Traditional sleep apnea diagnosis involves an overnight stay at
a sleep center with multiple sensors attached to the patient. However, portable monitoring
devices have emerged as a convenient alternative. These devices are compact and easy to use,
allowing individuals to perform sleep studies in the comfort of their own homes. They typically
include sensors for monitoring airflow, oxygen levels, and breathing patterns.
Overall, these innovations in sleep apnea detection systems aim to make diagnosis and
monitoring more accessible, convenient, and accurate. By leveraging advanced technology
techniques, healthcare providers can improve patient care and outcomes for individuals with
sleep apnea.

FUTURE SCOPE
• Wearable technology: The development of wearable devices such as smartwatches, activity
trackers, and headbands with sensors that can detect breathing patterns and oxygen levels in
the blood during sleep is a promising area. These devices can track sleep quality and detect
sleep apnea symptoms, making it easier for patients to monitor their sleep health.
• Artificial intelligence: The use of artificial intelligence (AI) and machine learning algorithms
can improve the accuracy of sleep apnea detection systems. AI can analyze large amounts of
data collected from wearable devices and other sensors to detect patterns and identify risk
factors for sleep apnea.
• Remote monitoring: With the increasing popularity of telemedicine, there is a growing
demand for remote monitoring of sleep apnea patients. A sleep apnea detection system that can
be accessed remotely by healthcare providers and patients can improve the quality of care and
provide more efficient treatment.
• Integration with other healthcare technologies: Sleep apnea detection systems can be
integrated with other healthcare technologies such as electronic health records, medical
imaging systems, and medication management systems to provide a more comprehensive
approach to managing sleep apnea.
•Advancements in technology: The development of advanced sensors, wireless
communication, and machine learning algorithms is expected to enhance the accuracy and
reliability of sleep apnea detection systems. This will enable earlier detection and better
management of sleep apnea.
• Home-based sleep apnea detection systems: With the increasing demand for remote
monitoring and self-diagnosis, home-based sleep apnea detection systems are likely to become
more popular. These systems will enable patients to monitor their sleep patterns and detect
sleep apnea from the comfort of their homes.
• Personalization of treatment: Sleep apnea detection systems can help personalize treatment
by monitoring patients' sleep patterns and adjusting treatment plans accordingly. This will
improve treatment outcomes and reduce the risk of complications.
• In conclusion, the future scope of designing and implementing a sleep apnea detection system
is vast. Advancements in technology, home-based systems, integration with other healthcare
systems, and personalized treatment options are likely to enhance the accuracy and reliability
of sleep apnea detection systems, leading to better patient outcomes.