Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
https://doi.org/10.36561/ING.26.15
ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay
Este es un artículo de acceso abierto distribuido bajo los términos de una licencia de uso y distribución CC BY 4.0. Para ver una
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Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
https://doi.org/10.36561/ING.26.15
ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay
Este es un artículo de acceso abierto distribuido bajo los términos de una licencia de uso y distribución CC BY 4.0.
Para ver una copia de esta licencia visite https://creativecommons.org/licenses/by/4.0/
Design of a low-cost portable electrocardiograph for telemedicine application
Diseño de un electrocardiógrafo portátil de bajo coste para su aplicación en
telemedicina
Conceção de um eletrocardiógrafo portátil de baixo custo para aplicação em
telemedicina
Hólger Santillán
1
(*), Angelo Mantilla
2
, David Cárdenas
3
, Peregrina Wong
4
Recibido: 24/03/2024 Aceptado: 31/05/2024
Summary. - This paper presents the design of a portable electrocardiograph designed to provide community health
care. The AD8232 main sensor has multiple options for displaying cardiac activity. The first option uses the serial
plotter in the Arduino IDE, while the second employs LabVIEW, allowing additional observation of the patient's blood
pressure via block coding. In addition, the Arduino cloud is integrated to process the information captured by the
ESP32, enabling visualization on any device with internet access. Through this platform, it is possible to download
the studies performed in different periods (1 hour, 1 day, 7 days, and 15 days), with an efficiency percentage of 4.11%.
Keywords: Portable Electrocardiograph; Healthcare; IoT; Community; Cardiac Activity.
Resumen. - El presente trabajo presenta el diseño de un electrocardiógrafo portátil diseñado para proporcionar
asistencia médica comunitaria. Se emplea el sensor principal AD8232, con múltiples opciones de visualización de la
actividad cardíaca. La primera opción utiliza el serial plotter en el IDE de Arduino, mientras que la segunda emplea
LabVIEW, permitiendo la observación adicional de la presión arterial del paciente mediante codificación de bloques.
Además, se integra la nube de Arduino para procesar la información capturada por el ESP32, lo que posibilita la
visualización en cualquier dispositivo con acceso a internet. A través de esta plataforma, se pueden descargar los
estudios realizados en distintos lapsos de tiempo (1 hora, 1 día, 7 días y 15 días), con un porcentaje de eficacia del
4.11%.
Palabras clave: Electrocardiógrafo portátil; Asistencia Sanitaria; IoT; Comunidad; Actividad Cardiaca.
Resumo. - Este artigo apresenta o projeto de um eletrocardiógrafo portátil projetado para prestar cuidados de saúde
comunitários. O sensor principal AD8232 possui múltiplas opções para exibir a atividade cardíaca. A primeira opção
(*) Corresponding Author
1
Master en Telecomunicaciones. Universidad Politécnica Salesiana, Grupo de Investigación en Sistemas de Telecomunicaciones – GISTEL,
Universidad de las Palmas de Gran Canaria, hsantillan@ups.edu.ec holger.santillan101@alu.ulpgc.es,
ORCID iD: https://orcid.org/0000-0003-4803-7016
2
Ingeniero en Telecomunicaciones. Universidad Politécnica Salesiana, Grupo de Investigación en Sistemas de Telecomunicaciones - GISTEL,
amantillam1@est.ups.edu.ec , ORCID iD: https://orcid.org/0009-0000-2163-8714
3
Master Universitario en Tecnologías y s\Sistemas de Comunicación. Universidad Politécnica Salesiana, Grupo de Investigación en Sistemas de
Telecomunicaciones - GISTEL, dcardenasv@ups.edu.ec , ORCID iD: https://orcid.org/0000-0003-4241-9929
4
Ingeniera electrónica. Universidad Politécnica Salesiana, Grupo de Investigación en Sistemas de Telecomunicaciones – GISTEL, Universidad
de las Palmas de Gran Canaria, peregrina.wong101@alu.ulpgc.es ORCID iD: https://orcid.org/0000-0003-1290-7729
H. Santillán, A. Mantilla, D. Cárdenas, P. Wong
Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
https://doi.org/10.36561/ING.26.15
ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay 245
utiliza o plotter serial no Arduino IDE, enquanto a segunda utiliza o LabVIEW, permitindo observação adicional da
pressão arterial do paciente por meio de codificação em bloco. Além disso, a nuvem Arduino está integrada para
processar as informações captadas pelo ESP32, possibilitando a visualização em qualquer dispositivo com acesso à
internet. Através desta plataforma é possível baixar os estudos realizados em diferentes períodos (1 hora, 1 dia, 7
dias e 15 dias), com percentual de eficiência de 4,11%.
Palavras-chave: Eletrocardiógrafo Portátil; Assistência médica; IoT; Comunidade; Atividade Cardíaca.
1. Introduction. - The electrocardiogram is known as a non-invasive medical test that records the electrical activity
of the patient's heart. It is used to evaluate the health of the most important organ, the heart, and to detect possible
cardiovascular problems. During an electrocardiogram, electrodes are attached to the skin at different locations on the
human body, such as the chest and upper and lower extremities [1], [2].
During the pandemic or situations in which it has been difficult for patients to approach a medical center to review
the information or know the status of the study has been a limiting factor either physical, personal, or environmental
conditions and this has severely affected humanity during this health crisis [3], [4].
At present, there is a solution to this problem, which consists of the use of medical equipment capable of connecting
to the network and sending the information obtained in real time, which will be stored in a cloud and can be viewed
by anyone who requires it [5], [6].
The use of the IoT (Internet of Things) connection in medical equipment has the purpose of improving the quality of
service both to better process the studies and to provide the doctor with the facility to visualize the information to
perform an analysis anywhere on the planet. This has represented a great improvement in the field of health, allowing
Telecommunications and Medicine to work together [7], [8].
IoT communication is based on a device that acts as a transmitting antenna, in our case the ESP32, which receives the
processed signal through its ports and proceeds to send it to the Arduino cloud. This device is one of the main options
to consider when making an IoT connection due to its advantages over other components that do not have this
capability [9], [10].
In the design of this article, Arduino Uno is used as the receiver and will be the one to process the information from
the AD8232 sensor which captures the cardiac signal in analog form. The Arduino transforms the analog signal to
digital for easy reading and sends the data to the other stages of the design, sending the COM port to the LabVIEW
software which through the LINX library helps to make the connection of the system [11], [12].
At this stage the LabVIEW software provides a plus to the design since the blood pressure is displayed along with the
graph of the cardiac activity of the heart, normally in other mostly analog equipment this result is displayed every
minute, but through the formula for the prediction of blood pressure (equation 1), the prediction is obtained every 15
seconds which provides a much faster response to conventional [13], [14].
The final and most important step of this design is to send the information to the Arduino ESP32 Wi-Fi module which
is previously linked to the Arduino cloud where, through its interface, the cardiac activity can be observed in real-time
and this collection of information can be downloaded through an Excel file in comma delimited format for processing
[15], [16].
The tracing shown in Figure I is the result of a simulation performed using BTL Cardiopoint software. This software
is used as an electrocardiogram (ECG) simulator, allowing various clinical conditions and scenarios to be accurately
recreated. The graphical representation provides detailed information about the electrical activity of the heart and is
useful for medical education and cardiovascular research. This tracing, generated using the aforementioned software,
provides a valuable tool for the analysis and interpretation of cardiac activity in controlled settings. In addition, it
facilitates the practice of ECG interpretation, helping to improve the diagnostic and patient management skills of
healthcare professionals [17], [18].
H. Santillán, A. Mantilla, D. Cárdenas, P. Wong
Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
https://doi.org/10.36561/ING.26.15
ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay 246
Figure I. Simulation of an ECG using Cardiopoint software.
H. Santillán, A. Mantilla, D. Cárdenas, P. Wong
Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
https://doi.org/10.36561/ING.26.15
ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay 247
1.1 Related Work. - The authors of the article [16] mention that currently, many people die of cardiac arrest, due to
a poor check and control of the state of their cardiovascular system. They propose a solution to this problem through
their design, which is based on the realization of a cardiac activity monitor using the AD8232 sensor and an ESP32
that serves as a microprocessor and the device responsible for the connection to the cloud using Ubidots and
Thingspeak [19], [20].
The authors of the article [5] designed an ECG that focuses on making the cost as low as possible, and at the same
time they implemented a system to detect any anomaly in the outlets, in the case of any, they will send an alert message
to the doctor or the person in charge. The design has a Bluetooth connection system that covers a distance of 100
meters. It is concluded that its design is a great advance for society and a great alternative for people or entities that
need to start in the cardiovascular care of their patients because the manufacturing cost of the proposed design is
significantly lower than other models previously considered [21], [22].
The authors of the article [3] state that cardiovascular care awareness has now increased due to the emergence of
COVID-19, since during the pandemic period, the number of deaths due to cardiac arrest increased considerably. They
point out that the speed of detection time is crucial to avoid irreparable damage to human life.
They concluded that the design will be very useful because it can accommodate the information collected through
unique record codes that will facilitate the search of the records [23], [24].
The authors mention that about 30% of the population in rural areas of Bangladesh lives in poverty. Due to the lack
of modern medical technology in these areas, medical care and diagnostic services are limited for rural residents. As
a result, adequate medical care is inaccessible to the rural population. In this context, modern technology could be
implemented to address their health problems. For example, electrocardiogram (ECG) sensing tools connected to the
human body can be used to collect essential cardiovascular data through Internet of Things (IoT) devices [22].
The authors of the article mention that, in recent times, several researchers have explored the connection between
emotions and people's physical well-being. This research interest has intensified due to the rapid progress of computer
technology, especially in the biomedical field. In the field of engineering, there is a focus on understanding how
emotions affect the human body, which motivates researchers to conduct studies in this area. It should be noted that
this design does not have an information storage system, nor does it have the function of sending the information to
the cloud, it only focuses on the analysis and visualization during the ECG [1].
The aforementioned authors presented their devices to the world, some of them stand out in some particular quality
depending on the case. But they all fulfill their general purpose, to provide a tool for the care and prevention of
cardiovascular problems in humans, these articles were of great help in guiding which direction could focus the
analysis of this study and what other issues to innovate as evidenced in the implementation of the pressure gauge in
LabVIEW, therefore this article has great advantages to take into consideration as shown in the results section.
1.2 Arterial prediction formula implemented in LabVIEW. - The equation for blood pressure prediction (1) used
in LabVIEW is as follows:

󰇛󰇜
Where: 󰇛󰇜󰇟󰇠
󰇟󰇠
󰇟󰇠
Equation 1 is used to calculate blood pressure using radial pulse-taking techniques, whereby, if the pulse during the
first 15 seconds is continuous, the value obtained is multiplied by 4, resulting in an accurate prediction of the value
that would be obtained if the pulse were taken for a full minute. One of the great advantages of using this method is
that physicians can know in advance the blood pressure coming from the individual under study.
H. Santillán, A. Mantilla, D. Cárdenas, P. Wong
Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
https://doi.org/10.36561/ING.26.15
ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay 248
2. Method. - For the design of the electrocardiograph, first of all, the placement of the electrodes and the type of data
obtained through the AD8232 sensor are identified and coded using Arduino. The information obtained is analyzed
locally using the Serial plotter in the Arduino IDE. Then, using LabVIEW, a graphical interface is created to visualize
the electrical activity of the heart and make a blood pressure prediction, which is obtained every 15 seconds as opposed
to the manual method, which is obtained every minute. Finally, the Arduino cloud is used to open the doors to the
world of IoT, it is observed by any device with internet access and as an additional benefit, the report of the data
received is downloaded as a text file [25], [26].
The advantage of using the AD8232 sensor is its ease concerning its size, which allows it to make cases, thus
facilitating its portability with the patient. This sensor handles 3.3 volts, obtained through the Arduino, which is
powered with 5V. This also facilitates the use of portable batteries with which the portability of the prototype is
enhanced [27], [28].
It is important to mention the advantage of downloading the information containing the studies performed on each
patient in a comma delimited file that can be opened by Excel and obtain the details every second of the reading of
the data of the electrical activity of the heart, this information needs to be processed as shown below. With the
information already processed, a more in-depth analysis is performed in the cardiovascular area.
Below, in Figure II, a scheme is presented to explain more simply the stages of processing and analysis of the
prototype.
Figure II. Outline of the proposed design.
Where:
1. Placement of the electrodes on the patient.
2. Recording of electrical measurements of the heart using the AD8232 module.
3. Processing of the measurements taken by the Arduino.
4. Visualization of the cardiac activity on the monitor through Arduino and LabVIEW.
5. Sending the data of the measurements to the cloud.
6. Remote viewing of the analysis performed.
The most important materials used in the development of this design are the following:
-Arduino UNO.
-AD8232 sensor.
-ESP32.
-Cables to interconnect the devices with each other.
H. Santillán, A. Mantilla, D. Cárdenas, P. Wong
Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
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ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay 249
Figure III shows the physically assembled prototype circuit, which represents the design of a portable
electrocardiograph intended to provide medical assistance to the community. The circuit incorporates the use of the
AD8232 as the primary sensor for accurate detection of cardiac activity. In addition, it offers three options for
displaying the heart rate graph, allowing for versatile monitoring that is adaptable to the user's needs. This innovative
design seeks to provide an affordable and effective solution for cardiac monitoring in medical and community settings,
thus contributing to improving cardiovascular health and quality of life.
Figure III. Physically assembled circuit.
Figure IV shows the torso of a patient with the electrode arrangement of the prototype circuit of a portable
electrocardiograph. These electrodes, essential for accurate detection of the heart rhythm, are strategically placed
following standard medical guidelines as follows.
- Red electrode: located on the right side of the right torso on the lateral side (1).
- Yellow electrode: located on the left side of the torso at the level of the heart (2).
- Green electrode (Neutral): located under the last rib on the right side of the torso (3).
This innovative approach to electrocardiograph design reflects a significant advance in medical technologies, as it
enables effective, noninvasive cardiac rhythm monitoring in clinical and community settings. The correct arrangement
of the electrodes on the patient's torso ensures accurate and reliable measurements, which is critical for informed
medical decision-making and cardiovascular health care.
Figure IV. Placement of electrodes on the patient.
H. Santillán, A. Mantilla, D. Cárdenas, P. Wong
Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
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ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay 250
2.1 LabVIEW Block Diagram Configuration. - Next, each of the steps related to the configuration of the block
diagram used in LabVIEW, as shown in Figure V, are detailed. In this comprehensive analysis, each of the components
and connections of the diagram are addressed, explaining their function and their contribution to the overall system
operation. In addition, the design decisions made during the creation of the block diagram are described, highlighting
their relevance to the success of the project.
This detailed approach provides a thorough understanding of the configuration process in LabVIEW, allowing readers
to become familiar with the techniques used and their application in the specific context of the project. This detailed
explanation seeks to provide clarity and facilitate replication of the process by other researchers or practitioners
interested in using LabVIEW for similar projects.
Figure IV. Configure Design in LabVIEW.
2.2 Configuration LabVIEW with Arduino. - In Figure VI, we initially present the COM port block, which is in
charge of reading the information through the COM ports of our PC. This information is sent to the Linx Open. vi file,
where the baud rate is set to 9600 to ensure optimal data transmission speed to the system.
Figure VI. Arduino communication block.
After establishing communication with the Arduino, an analog reading is made, because the information processed by
the sensor is of this type. It is established that the pin of the Arduino to which the reading is being made will be the
A0, after this process the acquired data is sent to be displayed on a display, which will also trigger an LED that will
show the heartbeat obtained.
H. Santillán, A. Mantilla, D. Cárdenas, P. Wong
Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
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ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay 251
2.2 Comparator Processing. - Figure VII shows the comparator process, highlighting a gradual increment to reach
the set value. Once this requirement is met, a multiplication by zero is performed to reset the counter and return to the
initial loop. This cycle continues iteratively to ensure consistent and efficient operation of the system. The visual
representation provides a clear understanding of how the comparators are managed in the process, making it easy to
optimize and adjust parameters appropriately as needed.
Figure VII. Data Processing Block.
2.3 Audible Heartbeat Indicator. - In this section, the implementation of a horn to notify the detection of a heartbeat
by the proposed prototype is incorporated. Figure VIII clearly shows how this component is integrated into the heart
rate measurement system. The addition of the horn enables instant audible feedback, which improves usability and
user experience during cardiac monitoring. This additional functionality is critical for alerting the user to the detection
of a heartbeat and can be useful in a variety of clinical and personal care settings.
Figure VIII. Beats the sound indicator block.
2.4 Blood Pressure Prediction Programming. - In this section, there is an "Elapsed Time" which will act as the
equipment clock and allows to set the time unit in milliseconds. The coding of the pressure prediction system is located
inside the loop. The formula for the calculation of the blood pressure prediction is used, to know the cardiac pressure
data the pulsations must be taken during one minute, but with this formula, it will be able to make a prediction in only
15 seconds and show it more efficiently as shown in Figure IX.
H. Santillán, A. Mantilla, D. Cárdenas, P. Wong
Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
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ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay 252
Figure IX. Heartbeat prediction block.
2.5 Stop Configuration. - In Figure X, you can see the section corresponding to the stop button, which is designed to
initiate the block that completes the communication between LabVIEW and Arduino. This function is crucial to ensure
proper and controlled termination of the data exchange process between the devices. The inclusion of this button
provides the user with a convenient means to stop communication quickly and safely when necessary. In addition, its
integration into the overall system interface makes it easy to access and use during the operation of the control system.
Figure VIII. Stop Configuration Block.
The code used to perform the processing through the ESP32 and its subsequent sending to the Arduino cloud is
presented below:
#include "thingProperties.h"
void setup() {
Serial.begin(9600);
delay(1500);
initProperties();
// Connect to Arduino IoT Cloud
ArduinoCloud.begin(ArduinoIoTPreferredConnection);
setDebugMessageLevel(2);
ArduinoCloud.printDebugInfo();
}
void loop() {
ArduinoCloud.update();
analogData();
}
void analogData() {
pulso_cardiaco= analogRead(34);
Serial.println(pulso_cardiaco);
delay(200);
}
H. Santillán, A. Mantilla, D. Cárdenas, P. Wong
Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
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ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay 253
2.6 Cloud Configuration. - Regarding the creation of an Arduino cloud user for real-time monitoring of a portable
electrocardiograph system, designed to provide medical assistance to the community, a specific process is followed.
This process involves the use of the AD8232 as the main sensor and provides real-time cardiac activity display options.
To create a user in the Arduino cloud, the user must provide information such as email, username, and password. This
process is shown in detail in Figure XI.
Figure XI. Account Registration on Arduino.
In addition, the appropriate boxes must be checked according to the privacy preferences and acceptance of terms.
Once these steps are completed, click "Sign Up" to finalize the Arduino cloud registration. Creating a user in the
Arduino cloud allows access to additional functionalities, such as data storage and analysis in the cloud, which
facilitates remote monitoring and efficient management of the electrocardiography system.
Once the measurement information from the portable electrocardiograph circuit has been successfully sent, users can
access it in real-time from the "Dashboard" section. To do so, they should click on the specific control panel created
for this purpose, as shown in detail in Figure XII below.
Figure XII. Accessing the Dashboard on Arduino IoT Cloud.
Real-time visualization of the data facilitates the tracking and continuous monitoring of the heart rhythm, which is
crucial for the early detection of any irregularity or medical emergency. In addition, access to this real-time
information from any location provides greater flexibility and responsiveness for medical professionals and caregivers,
enabling them to make informed decisions and provide more timely and effective medical care to patients.
2.7 Equipment Cost. - The estimated cost of the system is $74, broken down as follows: Arduino Uno $20, Arduino
AD8283 Module $19, Arduino Wifi Module $15, and other consumables totaling $20.
However, it is important to note that this cost could increase significantly if a desktop computer and the necessary
software licenses are not available. The acquisition of these additional items could add approximately $800 to the total
cost of the project, resulting in a final value of $874.
H. Santillán, A. Mantilla, D. Cárdenas, P. Wong
Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
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ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay 254
Considering the importance of cost minimization as one of the main design parameters, the idea of mass-producing
the electrocardiograph is encouraged. This not only benefits educational institutions but also private or public
companies looking for cost-effective solutions for cardiac monitoring.
Thanks to this cost-effective approach, our design can successfully compete with other similar products on the market.
In addition, by offering an easily accessible portable electrocardiograph at an affordable price, we are contributing to
improving the accessibility of medical care and cardiovascular health monitoring for a wide range of users from
interested parties.
3. Results. - Table I below compares the data collected from the proposed prototype with the data simulated in the
simulator. This analysis provides a comparative contrast between the two data sets, revealing that, on average, there
is a margin of error of 5.81%. This level of discrepancy is considered considerably low, indicating a satisfactory
correspondence between the data obtained in practice and the simulated data.
This result reinforces the validity and accuracy of the proposed prototype for heart rate measurement. Furthermore, it
suggests that the simulation model used is effective in predicting the behavior of the system under real conditions.
This finding is encouraging as it demonstrates the reliability of the prototype in practical settings, supporting its
potential application in medical and health monitoring applications.
Table I. Sensed data compared with simulation.
As was carried out in the analysis presented in Table I above, a scenario study was performed with 53 additional
patients under similar test conditions. The results obtained were averaged and contrasted with the simulated data, thus
calculating the error of the proposed prototype.
The purpose of this scenario was to analyze the level of discrepancy present in the measurement of the electrical
activity of the heart. Table II, which contains the information collected from these 53 additional patients, is presented
below.
Sensed data (R) mV
Simulated data (S) mV
% error
1210
1180
2,5
1120
1215
7,8
1300
1195
8,8
1120
1205
7,1
1520
1180
11,9
1210
1165
3,9
1180
1195
1,3
1163
1185
1,9
1012
1170
13,5
1201
1190
0,9
1321
1160
13,9
1210
1195
1,3
1150
1175
2,1
1310
1180
11,0
1180
1205
2,1
1050
1195
12,1
1210
1180
2,5
1186
1200
1,2
1283
1215
5,6
1112
1195
6,9
1090
1200
9,2
1123
1175
4,4
1168
1190
1,8
Average error %
5,813
H. Santillán, A. Mantilla, D. Cárdenas, P. Wong
Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
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ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay 255
Table II shows three columns with information, the first column is the average value of the patient's 2-hour ECG
study, and the second column contains the average value of a simulated ECG with the patient's data (age, weight,
height, etc.) using Cardiopoint software, and the third column corresponds to the average value of the two columns
mentioned above [29], [30].
% error
Patient 1
5.81
Patient 2
8,10
Patient 3
9,01
Patient 4
5,63
Patient 5
5,54
Patient 6
4,75
Patient 7
4,70
Patient 8
4,37
Patient 9
5,31
Patient 10
2,36
Patient 11
5,60
Patient 12
4,73
Patient 13
6,44
Patient 14
8,83
Patient 15
8,48
Patient 16
9,46
Patient 17
8,11
Patient 18
6,31
Patient 19
4,70
Patient 20
4,23
Patient 21
4,95
Patient 22
2,70
Patient 23
4,17
Patient 24
3,62
Patient 25
4,43
Patient 26
4,93
Patient 27
7,29
Patient 28
4,02
Patient 29
5,07
Patient 30
3,81
Patient 31
3,50
Patient 32
4,83
Patient 33
2,77
Patient 34
1,97
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Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
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ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay 256
Patient 35
3,00
Patient 36
1,97
Patient 37
1,97
Patient 38
1,91
Patient 39
1,65
Patient 40
1,67
Patient 41
2,87
Patient 42
1,75
Patient 43
1,77
Patient 44
1,91
Patient 45
2,05
Patient 46
2,81
Patient 47
2,21
Patient 48
1,45
Patient 49
1,04
Patient 50
1,44
Patient 51
1,60
Patient 52
3,37
Patient 53
2,57
Average
4,11
Table II. Table of results from conducted studies.
This extended analysis provides a more comprehensive evaluation of the prototype's accuracy and reliability in a
variety of clinical scenarios. The results obtained will help to further validate the clinical utility of the proposed device
and provide valuable information for future improvements and refinements of the system.
Table III presents the average value obtained from each of the studies performed. These data were collected over 2
hours using the proposed prototype for cardiac measurement of the Patients in the test scenarios. Subsequently, this
set of values is downloaded from the cloud in .csv format for further processing.
Patient 1
Patient 2
Patient 3
Patient 4
Patient 5
Patient 6
Patient 7
Patient 8
Patient 9
Patient 10
H. Santillán, A. Mantilla, D. Cárdenas, P. Wong
Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
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Patient 11
Patient 12
Patient 13
Patient 14
Patient 15
Patient 16
Patient 17
Patient 18
Patient 19
Patient 20
Patient 21
Patient 22
Patient 23
Patient 24
Patient 25
Patient 26
Patient 27
Patient 28
Patient 29
Patient 30
Patient 31
Patient 32
Patient 33
Patient 34
Patient 35
Patient 36
Patient 37
Patient 38
Patient 39
Patient 40
Patient 41
Patient 42
Patient 43
Patient 44
Patient 45
Patient 46
Patient 47
Patient 48
H. Santillán, A. Mantilla, D. Cárdenas, P. Wong
Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
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ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay 258
Patient 49
Patient 50
Patient 51
Patient 52
Patient 53
Averages
Table III. Summary of simulations.
The collected data are subjected to a conversion process using the table hosted in Table IV. This table is used to
subtract 1800 from the value extracted from the .csv file, followed by a multiplication by 1.8 conversion necessary to
express it in millivolts.
This method allows us to obtain a standard measure of cardiac activity, thus providing a clearer picture of the reliability
of the proposed design. The calculation of the average of these samples is essential to assess the consistency of the
data obtained and to ensure the accuracy of the device as a whole.
In addition, the presentation of these effectively processed data facilitates communication with the professionals
responsible for the diagnosis and analysis of the cardiac studies performed.
Conversion factors
Obtained data
Data – 1800
x1.8 (mV)
2500
700
1260
2400
600
1080
2450
650
1170
2491
691
1243,8
2501
701
1261,8
2486
686
1234,8
2512
712
1281,6
2502
702
1263,6
2415
615
1107
Table IV. Conversion table.
The integration of the Arduino cloud with the help of the ESP32 allows the establishment of an IoT connection that
makes it possible to view the data collected by the heart rate monitoring prototype from any location. This solution
offers the advantage of accessing the information received at predefined time intervals, such as hourly, daily, weekly,
and fortnightly.
Additionally, the facility is provided to download this data into a comma-delimited Excel (.csv) file, as shown in
Figure XIII. This ability to remotely view and download data in Excel format offers additional flexibility in the
analysis and management of the information obtained from cardiac monitoring, which is especially useful for medical
professionals and research teams.
H. Santillán, A. Mantilla, D. Cárdenas, P. Wong
Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
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ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay 259
Figure IXIII. Real-time visualization of collected data.
The graphs generated locally using the Arduino serial plotter are presented below. These plots visually display the
data collected by the heart rate monitoring prototype and are detailed in Figure XIV. The graphical representation of
this data provides a clear and detailed visualization of the heart rate over time, making it easy to identify patterns and
anomalies in the Patient's cardiac activity. These graphs provide an invaluable tool for the analysis and interpretation
of the results obtained, both for healthcare professionals and researchers in the field of cardiology.
Figure XIV. Graphs were obtained using the Arduino Serial Plotter.
Figure XV shows the measurements collected over one hour in the system, obtained from the data recorded by the
heart rate monitoring prototype and linked to the IoT platform. This visual representation provides a detailed snapshot
of the heart rate over a specific period, allowing an accurate assessment of the Patient's cardiac activity over that
interval.
These measurements provide valuable information about heart rate variability and can help identify potential
irregularities or patterns of interest for clinical analysis. Analysis of these measurements can provide meaningful
insights for the assessment of the Patient's cardiovascular health and contribute to informed medical decision-making.
H. Santillán, A. Mantilla, D. Cárdenas, P. Wong
Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
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ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay 260
Figure XIV. Displaying measurements in real time over a 1-hour period.
4. Discussion. - The authors of the article [16], made a design of a remote monitoring of heartbeat and ECG signal
using the SP32 with which they obtained graphs using the Arduino serial plotter.
The results obtained for comparison are determined by analyzing the graphs obtained, it is considered that the metric
used in that design is performed every 60 seconds (1 minute), unlike our design in which every 15 seconds a prediction
is made which allows obtaining a much faster and reliable measurement.
The authors performed an electrocardiogram that hosts the information in the cloud through MySQL which allows it
to manage display screens much more friendly to the end user, thus allowing the characteristic ease and accessibility,
in that aspect presents an improvement with the design presented in this article, a clear particularity that can be polished
and added in subsequent works to enhance the present design.
Something notorious in the article is the lack of a margin of error study of the values obtained by the AD8232, which
is necessary to evaluate the reliability of the data presented [3].
In [5] made a similar design to the one presented in this thesis, although they use the same sensors, they do not
contemplate obtaining the blood pressure, they only focus on obtaining the ECG graphs, they use the Ubidots cloud
to visualize the information sent by the ESP32. In addition, they make a comparison between the different forms of
connection either by Bluetooth, wifi, or ZigBee but do not present a comparison of the quality of the transmitted data,
which marks a notable difference compared to the present article.
The development of this design provides a very accurate analysis of the electrical activity of the heart, facilitating the
study and analysis of cardiovascular patterns in patients. A great advantage compared to the design of the researchers
in the article [16] is the improvement and implementation of the predictive analysis of blood pressure no longer every
60 seconds but every 15 seconds, providing an advantage for the prediction of possible tachycardias or bradycardias,
which can be correctly detected by health professionals, providing a very valuable tool for those who use this design.
The following Table V compares the related works, showing the strengths of each one of them, and showing which
one’s present improvements compared to others. It is concluded that the proposed design, despite the 4.11% error rate,
offers a wider range of characteristics compared to other designs, reducing the error rate may be the objective to be
achieved in future research from already established bases.
ECG Cloud ABPM
Census info % Error
Proposed ✓ ✓ ✓
✓
4.11
Art. [16] ✓ ✓ ✓
✓
X
Art. [5] ✓ ✓ X
✓
X
Art. [3] ✓ ✓ X
X
X
H. Santillán, A. Mantilla, D. Cárdenas, P. Wong
Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
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ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay 261
Art. [22] ✓ ✓ ✓
X
0.41
Art. [1] ✓ X X
X
X
Table V. Comparison table of related items
The design of the portable electrocardiograph system outlined in this paper presents several notable advantages.
Firstly, the system offers detailed blood pressure information, enhancing the comprehensive assessment of a patient's
cardiovascular health. Additionally, it features a visual indicator that records each detected heartbeat, facilitating
precise monitoring of cardiac activity.
A standout feature of the system is its capability to transmit collected information to the cloud. This functionality
allows users to access data from any internet-connected device, providing increased flexibility and accessibility in
monitoring heart health. Furthermore, the system offers the option to download information as an XML file,
streamlining further processing for analysis and storage purposes.
Measured values, such as an Average ECG (R) of 1202.83 mV and simulated Average ECG (S) values of 1190.71
mV, reveal a margin of error of 4.11%. Despite this small margin, the prototype demonstrates acceptable reliability in
measuring cardiac activity. These results underscore the effectiveness and practicality of the developed portable
electrocardiograph system, underscoring its potential for integration into clinical and community settings.
5. Conclusions. - After a thorough evaluation of the performance of the portable electrocardiograph designed to
provide community healthcare, 1-3 hour study scenarios were conducted to verify the reliability of the information
captured and transmitted through our cloud platform. During this process, a margin of error of 4.11% was observed.
However, the presence of a certain level of noise was detected in the measurements shared with the Arduino cloud,
suggesting that this interference could explain part of the error and the slight distortion in the received signal. These
findings highlight areas of improvement for future research, where techniques could be implemented to mitigate the
noise and thereby improve the quality of the transmitted signal.
The design of the portable electrocardiograph system makes a valuable contribution to community medical
knowledge, opening the door for further exploration in this field through additional research. This design lays the
foundation for the future development of devices aimed at improving the quality of life of both students and society
in general, representing a significant advance for human welfare. In this sense, the ability to provide quality medical
care at the community level is strengthened with the implementation of this innovative technology.
Furthermore, it is important to highlight that the successful implementation of this portable electrocardiograph in
community settings could have a significant impact on the early detection of cardiac problems and the prevention of
serious complications. By facilitating more accessible and continuous monitoring of patients' cardiac health, it could
improve preventive medical care and reduce the burden on healthcare systems, especially in remote or underserved
areas. This would not only benefit individuals at risk for heart disease but would also contribute to health promotion
and overall community well-being. Ultimately, the portable electrocardiograph represents not only a technological
advance in the medical field, but also a vital tool for improving quality of life and public health at the community
level.
H. Santillán, A. Mantilla, D. Cárdenas, P. Wong
Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
https://doi.org/10.36561/ING.26.15
ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay 262
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H. Santillán, A. Mantilla, D. Cárdenas, P. Wong
Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 244-264
https://doi.org/10.36561/ING.26.15
ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay 264
Nota contribución de los autores:
1. Concepción y diseño del estudio
2. Adquisición de datos
3. Análisis de datos
4. Discusión de los resultados
5. Redacción del manuscrito
6. Aprobación de la versión final del manuscrito
HS ha contribuido en: 1, 2, 3, 4, 5 y 6.
AM ha contribuido en: 1, 2, 3, 4, 5 y 6.
DC ha contribuido en: 1, 2, 3, 4, 5 y 6.
PW ha contribuido en: 1, 2, 3, 4, 5 y 6.
Nota de aceptación: Este artículo fue aprobado por los editores de la revista Dr. Rafael Sotelo y Mag. Ing. Fernando
A. Hernández Gobertti.