Open Computer Science 2022; 12: 227–237

Research Article

Hussain A. Jaber*, Hadeel K. Aljobouri, and Ilyas Çankaya

Design of a web laboratory interface for ECG

signal analysis using MATLAB builder NE
https://doi.org/10.1515/comp-2022-0244 Keywords: ECG simulation system, heart rate, MATLAB
received March 18, 2020; accepted May 26, 2022 builder NE, QRS complex, web-based learning
Abstract: An electrocardiogram (ECG) is a noninvasive
test, determining any defect in the heart rate or rhythm
or changes in the shape of the QRS complex is very sig-
nificant to detect cardiac arrhythmia. In this study, novel 1 Introduction
web-ECG simulation tools were proposed using MATLAB
Builder NE with WebFigure and ASP.NET platform. The Laboratories are the essential support for undergraduate
proposed web-ECG simulation tools consisted of two students and researchers with each other as well as
components. First, involved the analyses of normal real courses that lead to improving their skills in solving
ECG signals by calculating the P, Q, R, S, and T values and fixing practical problems, particularly in engineering
and detecting heart rate, while the second part related laboratories. These laboratories present experiments in
to extracting the futures of several types of abnormality evolving students’ skills which leads to promoting uni-
real ECG. For calculating the PQRST values, simple and versities which are the basis for the development of coun-
new mathematical equations are proposed in the current tries [1,2]. An electrocardiogram (ECG) is the chart and
study using MATLAB. The Web ECG is capable to plot map of the heart. The ECG records the electrical activity of
normal ECG signals and five arrhythmia cases, so the the human heart, and the acquired signal is printed on
users are able to calculate PQRST easily using the pro- paper. This record is utilized for the early diagnosis of
posed simple method. ECG simulation tools have been heart disease. The normal and typical ECG wave is com-
tested for validity and educational contributions with 62 posed of a series of positive and negative waveforms,
undergraduate and graduate students at the Al-Nahrain namely, the P wave, QRS complex, and T wave. The
University-Biomedical Engineering Department, Iraq. The ECG is the most frequently used test to assess the heart.
proposed ECG simulation tools have been designed for This record is significant because it can screen for various
academic learning to be run easily by a student using cardiac abnormalities. ECG devices are readily available
only any web browsers without the need for installing in the majority of medical facilities [3–5]. The heart rate,
MATLAB or any extra programs. The proposed tools could the rhythm of the heart, abnormality in the muscle of the
provide a laboratory course for ECG signal analysis using a heart, evidence of a previous heart attack, or the presence
few buttons, as well as increase and develop the educa- of coronary artery disease can be detected from the ECG
tional skills of students and researchers. trace [6,7].
The changes in the electrical pattern of the ECG
can offer important clues for the occurrence of syncope
 or may distinguish heart disease. Thus, clinicians and
* Corresponding author: Hussain A. Jaber, National MR Research biomedical engineers who study heart diseases should
Center (UMRAM), Bilkent University, 06800 Ankara, Turkey;
be trained in interpreting ECG signals [8–10]. Studies
Department of Engineering of Medical Instrumentation
Techniques, Kut University College, Kut, Iraq, on heart diseases have resulted in the remarkable devel-
e-mail: hussainjaber2000@ybu.edu.tr opment in the application of computer-assisted learning
Hadeel K. Aljobouri: Biomedical Engineering Department, College of (CAL) tools widely utilized in medical and biomedical
Engineering, Al-Nahrain University, Baghdad 10072, Iraq, engineering education, especially for physiological data
e-mail: hadeel_bme77@yahoo.com
analysis [11–14]. Tools for ECG interpretation and feature
Ilyas Çankaya: Electrical and Electronics Engineering Department,
Graduate School of Natural Science, Ankara Yıldırım Beyazıt
extraction are some examples of CAL tools [15–17]. Numerous
University, 06010 Ankara, Turkey, e-mail: icankaya@ybu.edu.tr academic and commercial studies on ECG interpreta-
ORCID: Hussain A. Jaber 0000-0002-4683-679X tion and feature extraction tools have been conducted.

Open Access. © 2022 Hussain A. Jaber et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution 4.0
International License.
228  Hussain A. Jaber et al.

McClennen et al. proposed a novel teaching tool for the ECG signal analysis, which includes feature extraction,
physicians and medical school students. The tool was and the related works. Section 3 presents an introduction
based on the creation of a web-based ECG system that to the architectural layout of the web-ECG simulation tools
connects directly with the clinical repository of a hos- and design process. Section 4 describes the contents and
pital [18]. Rodríguez et al. presented a new approach results of the proposed web-ECG simulation tools. In
using web service technology to capture, record, and Section 5, evaluation results of proposed WEB ECG tools
analyze the ECG signals in a personal digital assistant are presented. Finally, conclusions and future research
carried by a patient [19]. Nilsson et al. introduced stu- directions are drawn in Section 6.
dies on the evaluation of a web-based ECG interpreta-
tion program using a diagnostic test to allow medical
student users to assess the effect of the program on their
skills in ECG interpretation and extraction [20]. Shopov 2 Methodology and related work
et al. proposed a web-based ECG Personal Health System,
which includes a multi-tiered architecture combined The proposed web-ECG simulation tools are very compre-
with an information system to facilitate the remote exam- hensive and significant for clinicians and engineers in
ination and analysis of a physician [21]. Islam et al. research and medical students. In current work, a com-
designed software tools for ECG analysis using MATLAB prehensive, general-goal, user-friendly, graphical user
and LABVIEW programs. The tools included the genera- interface ECG signal extraction features tools, which are
tion, interpretation, extraction, calculation, and compar- easy to learn have been developed based on MATLAB
ison of different ECG signals [22]. Kırbaş and Bayılmış Builder NE
introduced a web-based remote monitoring interface using This package involved the analyses of normal and
MATLAB Builder NE with WebFigure, and this interface abnormal real ECG signals by calculating the P, Q, R, S,
was applied in medical care using a wireless body area and T values and detecting heart rate. The main contri-
sensor network [23]. Güney et al. designed a new web- bution in the presented work is the calculating of the P,
ECG simulator using MATLAB WebFigure and included Q, R, S, and T values using simple and new equations with
nine types of arrhythmias. In addition, three different MATLAB. The simple algorithm is tested on the normal
noises, namely, baseline wander, power line interference, ECG and standard arrhythmia database of the MIT-BIH
and random noise, are added to the clear ECG signal in this [28], to demonstrate the performance of the proposed algo-
simulator [24]. Granero-Molina et al. studied the implica- rithm and web-ECG simulation on real ECG data.
tion of new web simulation curricula in nursing schools
and determined the effect of web ECG simulation on stra-
tegies and learning styles [25]. AL-Ziarjawey and Çankaya
proposed a mathematical algorithm to obtain the P, Q, R, 2.1 Normal ECG analysis
S, and T values, draw these values on the ECG wave, and
detect heart rate. The proposed algorithm was materialized In this work, a new and simple proposed method is per-
by a graphical user interface (GUI) using the MATLAB plat- formed to obtain the P, Q, R, S, and T values (Figure 1).
form. The software has been devoted to education and This method is based on finding a mathematical relation-
scientific research [26]. Ogundepo and Ponnle introduced ship between the highest values (peaks and valleys) of the
a model based on the GUI with MATLAB to analyze ECG ECG waveform and time. So, the number of samples for
and detect arrhythmia using a back-propagation neural one cardiac cycle should be selected in an ECG signal first.
network. The proposed tools encompass pre-processing In the proposed method, the normal ECG signal is set
of ECG signals and feature extraction [27]. to 400 sampling during every 1 cycle (example in our
In this study, a novel web-based ECG simulation case). The different points are detected by determining
monitoring system based on MATLAB Builder NE and the following values:
ASP.NET platform is presented. The web-based ECG simu- • R point, which is the maximum amplitude in one car-
lation tools were designed and developed for educational diac cycle (400 samplings) in an ECG signal;
and scientific research rather than clinical diagnosis. A
Rpoint = max(one cardiac cycle in ECG signal) . (1)
simple mathematical algorithm for analyzing ECG signal
components is proposed to detect the P, Q, R, S, and T • Q point, which is the minimum amplitude after shifting
values for real normal and abnormal ECG cases. This paper several steps (d1) toward the left of the R point at posi-
is structured as follows. Section 2 presents a brief review of tion (R-d1);
 Web laboratory interface for ECG  229

120 R

100

80

60
Amplitude

40
T
20
P

S
-20 Q
0 50 100 150 200 250 300 350 40 0
Sampling

Q-d2 R+d3 S+d4

R-d1

Figure 1: Normal ECG with P, Q, R, S, and T values.

Qpoint = min(ECG signal till R point) . (2)

• P point, which is the maximum amplitude after shifting

several steps (d2) toward the left of the Q point at posi-
tion (Q-d2);
Ppoint = max(ECG signal till Q point) . (3)

• S point, which is the minimum amplitude after shifting

several steps (d3) toward the right of the R point at
position (Q + d3);
Figure 2: The length of a normal ECG wave.
Spoint = min(ECG signal from R point till
(End point of one cardiac cycle in
(4)
signal analysis. In this section, various abnormal ECG sig-
an ECG signal − Start point of one
nals, namely, supraventricular arrhythmia, apnea, normal
cardiac cycle in an ECG signal). sinus rhythm, ventricular tachyarrhythmia, and intracar-
• T point, maximum amplitude after shifting several steps diac atrial fibrillation, are analyzed. Arrhythmia is
(d4) toward the right of the S point at position (Q + d4); detected, and the P, Q, R, S, and T waves are also calcu-
lated using the proposed simple method. Moreover, heart
Tpoint = max(ECG signal from S point till end point of rate in the abnormal ECGs is detected. The same mathe-
(5) matical calculations (equations (1–5)) used with normal
one cardiac cycle in an ECG signal).
ECG analysis are the same as that used in the abnormal
Figure 2 shows the length of a normal ECG wave, the ECG analysis. The difference in the application between
length of this wave is with 5,000 samplings. The length of the two analyses is in selecting the number of samples.
each cardiac cycle is about 400 sampling, so in the pro- In the normal ECG analysis, the sampling is set to 400
posed method, the length of each cardiac cycle should be during every one cycle because it is rhythm; while, in
defined first, and it can be used easily with the pre- the abnormal ECG analysis, the length of each cardiac
sented tool. cycle is different from one case to another. Also, during
the same ECG wave, each cardiac cycle is different in sam-
pling length from another because most cases are irregular
as shown in Table 1. So, the length of each cardiac cycle
2.2 Abnormal ECG analysis should be defined first as in the normal ECG, and the user/
student should enter the starting and end point of each
The second section of the proposed packages provides cardiac cycle easily with the presented tool according to
the same features as in section A for the normal ECG each abnormal case.
230  Hussain A. Jaber et al.

Table 1: Brief Summary of the Results of the Abnormal ECG signals

Name of Normal sinus rhythm Apnea-ECG Supraventricular Ventricular Intra cardiac atrial
abnormality Arrhythmia Tachyarrhythmia fibrillation
Rate 96 bpm 73 bpm 53 bpm 125 bpm 125 bpm
Rhythm Regular Regular Regular May be irregular Irregular

ecg graph with P = 19, Q = −83, P = 31, Q = −48, P = −15, Q = −27, P = −29, Q = −85, P = −432, Q = −984,
waves R = 439, S = −155, R = 294, S = −165, R = 283, S = −115, R = 1,026, S = −60, R = 7,696, S = −1,041,
characteristic T = 43 T = 47 T = −7 T = −25 T = −404

3 Web-ECG simulation architecture

The design of the web-ECG simulation tools using MATLAB Start
Builder NE and ASP.NET in Microsoft Visual Studio Platform
is illustrated in Figure 3. MATLAB Platform Visual Studio Platform
First, the MATLAB codes reflecting all functions of
the proposed web-ECG simulation tools were written as Adding a reference
Writing codes in
Functions.m files. After compilation of the coding files in MATLAB platform as
component to the deployed
component that created by
MATLAB, a.NET component is created using the deploy- Functions .m files
the MATLAB Builder NE
ment tool GUI to build a.NET class. Then, all.m files are Product
added to create.dll files in Ditrib & Src folders as.NET
components. Then, web-ECG simulation tools are designed
using the ASP.NET Web Site under the Visual Studio pro- Build a .NET class &
gram platform. Then, the WebFigure control from the toolbar adding .m files for Analyzing & finalizing
creating .dll files in Ditrib the Designing of WEB-
is dragged to the website page. A reference component to & Src folders as .NET ECG Simulation Tools
the MWArray and another reference to the deployed com- Components
ponents created by MATLAB Builder NE are created.
Thereafter, a code for the website page is written using
C# in the Microsoft Visual Studio Platform. Finally, the Visual Studio Platform
webpage is tested by selecting debug and running the
program in Microsoft Visual Studio [29–32]. Create & Design WEB- Writing a code for the
ECG Simulation Tools Web Site page Using C#
Using ASP.NET Web in Microsoft Visual
Site Studio Platform

4 Web-ECG results
The results of the web-ECG simulation tools are com- Test the Web page by
posed of the following components: first, ECG analyses Adding Webfigure running it in Microsoft
Control to Web site page Visual Studio, Select
of a normal ECG trace; second, ECG analyses of abnorm- Debug, then starting
alities. First of all, a simple user registration form is built Debugging
in ASP.Net designing using C# to allow the user to reg- Web Browser Platform
ister with the website. This step helps the user to enter
and utilize the web-ECG simulation tools. The user fills up
the registration form with several details, such as user- End

name and password. The provided information is saved

in the database table connected to this site. Thus, the
user should confirm registration to access the website Figure 3: Design of web-ECG simulation tools.
 Web laboratory interface for ECG  231

in ASP.Net. The user/student can enter at any time using

only his/her username and password on the login page
(Figure 4).
The proposed web-ECG simulation tools consist of
multiple pages. The confirmed registered user can navi-
gate the pages just by clicking the name of the page. The
startup (main) page that will appear after correct login
and when the user chooses any page is shown in Figure 5.
From the startup (main) page, the user can navigate
five pages, namely, registration page, normal ECG ana-
lysis, and abnormal ECG analysis.

Figure 5: ASP.NET website startup (main) page.

4.1 Abnormal ECG analysis

The first section of the proposed package provides the This tool analyzes the ECG recordings to obtain the P, Q,
main features of the analysis of a normal ECG signal R, S, and T values and detect heart rate (Figure 7), as
from the MIT-BIH Database PhysioNet. The steps of follows:
detecting P-QRS-T and heart rate are presented in a simple 1) A full sampling of ECG signal recordings is drawn
flowchart, as shown in Figure 6. The first step is the selec- after the selection of the type of data as an a.mat,.txt,
tion of the ECG lead (I, II, or III) and the type of file or.xlsx file that matches with the lead I, II, or III.
(.mat.txt, or .xlsx file). Then, the proposed algorithm 2) Data are imported from the hard disk or over the
starts to read the ECG data and remove the low- and network and from any type of data.
high-frequency components. Then, the windowing filter 3) Selecting the “Detect R-peak & HR” button imple-
and thresholding are used to find the local maxima. ments the detection of heart rate proceedings using
Finally, an adjust filter (again windowing filter) is used
to detect R–peaks, heart rate, and P-QRS-T waves using
a simple mathematical calculation.
The first section of the proposed package provides Start
the main features of the analysis of a normal ECG signal.

ECG Data Input

Using a windowing Filter

Lead Selection (I, II, III) Thresholding

File Type Selection (.mat

file,.txt file,.xlsx file) Using Adjust Filter

Read ECG signal PQRST & Heart Rate

Detection

Remove Low Frequency End

Components

Figure 4: ASP.NET website registration page. Figure 6: Detection of P-QRS-T and heart rate.
232  Hussain A. Jaber et al.

Figure 7: Web-ECG simulation tools to analyze normal ECG signals.

a windowing filter twice to find the local maxima of 4.2 Abnormal ECG analysis
the R-peak after removal of the low-frequency com-
ponents. Then, the filter size is adjusted. The other section of the WEB-ECG Simulation tools packages
4) The user can save the graph in any of three types of provides the same features as the previous section. The main
files (.fig, .png or .bmp) when the “Export & save different features in this part are the ECG abnormality ana-
Graph” button is clicked. lysis. This analysis includes (supraventricular arrhythmia,
5) The user can save data as .txt, .mat, or .xlsx file. apnea, normal sinus rhythm, ventricular tachyarrhythmia,
6) The program can save different types of images (figures). and intracardiac atrial fibrillation) which analyzes the
7) The program can also save different types of data. abnormalities of ECG recordings. The objective of this ana-
8) Clicking the “Get Analysis Data” button will run ECG lysis is to detect arrhythmia and calculate P, Q, R, S, and
data analysis to calculate the P, Q, R, S, and T values. T waves; as well as to detect the heart rate of ECG
The number of samples for one cardiac cycle in an abnormalities. Therefore, Table 1 and Figure 8 provide
ECG signal of the P-QRS-T waves should be set to 400 all abnormal ECG signals and a summary of the results
samples. of these abnormalities.
9) The user can save the graph displayed at the bottom Table 1 lists the data from several abnormal ECG sig-
in any of the three types of files (.fig, .png, or .bmp) nals from the MIT-BIH Database Arrhythmia PhysioNet.
when this button is clicked. The first case is normal sinus rhythm, in which the heart-
10) The user can print out each figure. beat is normal at 96 bpm (between 60 and 100 bpm). The
11) Different types of images are available. rhythm is healthy with a normal and regular heartbeat.
12) The user can select whether to print all or specific The shape of this case shows three clear deflection waves,
samples. namely, P, QRS, and T.
13) The range of sampling data is entered. The second signal shows an apnea ECG, which may
14) The “POP-UP” menu is used to select steps to detect be misinterpreted as normal because of the regular rhythm
R-peaks and heart rate. and normal heart rate of 73 bpm (between 60 and 100).
15) The type of data (.mat, txt, and xlsx) is selected. The shape of the wave also embodies the three deflections.
16) The user selects data for any lead of the ECG that the The third case is supraventricular arrhythmia, which shows
user wants to be drawn. an abnormality in the timing or pattern of the heartbeat.
 Web laboratory interface for ECG  233

Figure 8: Third main page of the proposed web-ECG simulation tools for analyzing abnormal ECG signals.

Arrhythmias lead to very rapid, very low, or irregular heart- designed to rank the WEB ECG system with eleven ques-
beat. In supraventricular arrhythmia, the heartbeat is very tions, by using a scale of five points (excellent = 5, very
low at 53 bpm. The fourth case is ventricular tachyar- good = 4, good = 3, fair = 2, and very poor = 1). The
rhythmia, which shows irregular rhythm and very rapid evaluation form is filled out by students after using the
heartbeat at 125 bpm (over 120 bpm). The fifth case is intra- WEB ECG system tools and submitted to the serve under
cardiac atrial fibrillation. This condition is activated in the the ASP.NET platform.
atria which leads to an irregular rhythm. The heartbeat is The information of evaluation is saved in the data-
very rapid at 125 bpm (over 120 bpm). base table connected to this site, then authors can ana-
lyze these data to convert them into a statistical report
(bar graph) (Figure 10) that reflects how the students are
evaluated by this system. The statistical report is benefi-
5 WEB-ECG assessment cial in examining the skills gained by students after uti-
lizing the WEB ECG system as well as providing feedback
Web ECG simulation tools have been tested for validity information about the extent of WEB ECG success and
and educational contributions, by considering these tools meets the requirements of distance learning. The results
as a supplement for medical practitioners or biomedical of the statistical report are shown in Figure 10. The ques-
engineers and as an efficacious educational tool for tions in the evaluation form can be classified into five
learning and analyzing ECG. Web ECG system is evaluated sets. The first four questions are concerning in the facil-
at the Al-Nahrain University in which nearly 62 students in itating the education success as well as learning how
biomedical engineering in both undergraduate and grad- to calculate heart rate and P, Q, R, S, and T values with
uate studies participated to assess the WEB-ECG system WEB ECG tools. There are at least 81% of students were
in terms of educational contributions and validity. WEB said that the WEB ECG system has a positive response
ECG system tools were designed with an automatic evalua- regarding the ease of using this system. The second set
tion form (Figure 9) on the main page of this system in includes questions (five, six, seven, and eight) that are
which several questions are presented about the efficiency related to ease of use as well as to purpose to get feedback
and flexibility of this system. The evaluation form was on the use of the WEB ECG system, and most of the
234  Hussain A. Jaber et al.

Figure 9: Evaluation form.

Excellent very good good fair poor

70

60
Evaluaon Percentage(%)

50

40

30

20

10

0
Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q 10 Q 11
Evaluaon Quesons

Figure 10: Evaluation results.

 Web laboratory interface for ECG  235

students were believed that the WEB ECG system is very and the main contribution to this work is the implemen-
useful and very easy to use as well as user-friendly tools, tation of a new and simple proposed method to obtain
as a result, the average is increased to 85%. The third set values of P, Q, R, S, and T. This method is based on
has only the ninth question, related to the response time finding a mathematical relationship between the highest
of WEB ECG simulation tools. There are at least 80% of values (peaks and valleys) of the ECG waveform and time.
students who said that the WEB ECG system has a nega- In the presented tool, the clinicians are capable to
tive response regarding the time response of using this import data (any type of ECG signal) from any place
system, because students have to wait for around in (inside the computer, outside computers like hard disk
sometimes more than one minute for getting the result or any storage as well as from internet website). However,
because of the connection between the student (client) the equipment utilized in these laboratories are still so
and server need some time, so the average is decreased costly, so the suggested WEB ECG tools in current work
to 42%. are presented as cheap educational interface way as well
The fourth set has only the tenth question that is as user-friendly tools for students and researchers. This
related to the overall success and score of WEB ECG; tools package enables the opening of a new approach for
the majority of students, nearly 83%, have believed the researchers and undergraduate and graduate students
WEB ECG system is very acceptable and successful. The about how they can use ECG signals and be familiar
fifth set has only the eleventh question, which relates to with other biosignals in the future by using similar tools
whether the structure of the WEB ECG system is adap- for processing and extracting features of it. As a result,
table and appropriate for designing a different web-based the aim of designing WEB ECG tools is to improve the
on different biomedicine fields. There are 80% of stu- learning of students and understanding of how can find
dents who have thought that the structure of WEB ECG some features extraction of ECG.
is suitable to design and perform another WEB system for
another application course in the biomedical field for
improving the practical skills of students.
7 Conclusion and future works
The proposed current work is very necessary and has
6 Discussion vital significance, especially in countries that suffer
from a lack of financial resources which lead to raising
Laboratories are the essential support for undergraduate the criterion of the education level profession. It should
students and researchers with each other as well as courses promote sharing medical consultation in the field of
that lead to improving their skills in solving and fixing cardiology between medical centers in different gover-
practical problems, particularly in engineering laboratories. norates inside the country and also between centers in
These laboratories present experiments in evolving stu- other countries.
dents’ skills which leads to promoting universities which The presented simulation tools are essential for aca-
are the basis for the development of countries. demic instruction by clinicians, engineers, and researchers,
There are different literature that introduced a descrip- as well as for the training of medical students. This package
tion of the development of the ECG simulator on various is beneficial as a supplement for medical practitioners and
platforms, but still, all the presented work was limited to a as an efficacious educational tool for learning and analyzing
specific type and number of ECG signal cases. Software ECGs. The proposed web-ECG simulation tools can be uti-
tool using MATLAB and LABVIEW programs has been lized to train clinicians and engineers working in fields
introduced for analyzing different ECG signals [22]. A related to the study of heart disease. The proposed web-
web-based using MATLAB Builder NE with WebFigure ECG simulation tool package is a simple and authoritative
was applied in medical care using a wireless body area method to detect the P, Q, R, S, and T values of normal and
sensor network [23]. Another web-ECG simulator using abnormal ECG cases.
MATLAB WebFigure has been introduced to deal with Therefore, the package provides the following main
nine types of arrhythmias and three different noises [24]. features:
The presented ECG software package is designed to 1) Detection of R-peaks and measurement of the heart
extract features for any shape of ECG signal and classify rate in real normal and abnormal ECG signals.
the ECG signals for detecting arrhythmia according to the 2) Detection of P, Q, R, S, and T values in real normal and
analyzed signals. Actually, our tool has many structures, abnormal ECG signals.
236  Hussain A. Jaber et al.

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