=Paper=
{{Paper
|id=Vol-3616/paper4
|storemode=property
|title=IoT Health Telemonitoring Application for Cardiovascular Patients
|pdfUrl=https://ceur-ws.org/Vol-3616/paper4.pdf
|volume=Vol-3616
|authors=Aicha Aggoune,Loubna Seddiki,Ahmed Rami Bouguettoucha
|dblpUrl=https://dblp.org/rec/conf/rif/AggouneSB23
}}
==IoT Health Telemonitoring Application for Cardiovascular Patients==
https://ceur-ws.org/Vol-3616/paper4.pdf
IoT health telemonitoring application for
cardiovascular patients
Aicha Aggoune1,2 , Loubna Seddiki1 and Rami Bouguettoucha1
1
Department of Computer science, University of 8th May 1945, Guelma
2
LabSTIC, University of 8th May 1945, Guelma
Abstract
The Internet of Things (IoT) is largely regarded as the most significant future technology, and the
healthcare business is increasingly focused on it. The IoT is indeed at the heart of telemedicine, which
makes it possible to facilitate the performance of remote medical procedures. We propose and develop
the TeCa system (Telemonitoring of patients with cardiovascular diseases) an IoT-based web application
which used the AD8232 ECG sensor and Arduino Uno to collect ECG data, which was subsequently kept
in a database and shared with the doctor’s caregiver. The proposed system allows a doctor to remotely
interpret the data for the medical follow-up of a patient. The TeCa system keeps its usability since it
does not require special knowledge to use it effectively.
Keywords
Telemonitoring, IoT, TeCa system, Cardiovascular patients, ECG sensors,
1. Introduction
The integration of Information and Communication Technologies (ICTs) in healthcare have
become increasingly important in recent years to enhance patient care through telehealth [1].
The innovative sensor in wearables and other commercial health products offer great potential
for real-world data collection. These technologies provide new methods of supporting and caring
for patients at home, well-known Remote patient monitoring or medical telemonitoring [2].
Cardiology is among the most significant sectors of industry since integrated sensor technologies
enable a wide range of applications, especially telemonitoring of patients’ cardiovascular health
status.
Telecardiology is diagnosing and treating of cardiac disorders such as congenital heart defects
and heart failure by a distant clinician using videoconferencing and other technology [3]. It has
improved the care of cardiac patients by increasing access to specialists not usually available in
the region and reducing wait times for necessary care.
Telecardiology seems to have the potential to renovate the mode of cardiac care given in
primary care settings [4]. Electrocardiography (ECG) is an important diagnostic tool that should
be used in primary care for the detection and therapy of cardiovascular illness and cardiac
RIF’23 : The 12th Seminary of Computer Science Research at Feminine, March 09, 2023, Constantine, Algeria
$ aggoune.aicha@univ-guelma.dz (A. Aggoune); seddikiloubna2001@gmail.com ( Loubna Seddiki);
ahmedramibouguettoucha@gmail.com (R. Bouguettoucha)
0000-0002-0877-7063 (A. Aggoune)
© 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
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arrhythmias. The Internet of things (IoT) has been used by the healthcare system to collect
ECG data and provide home monitoring to patients with heart disease [5]. Also, the Internet of
Medical Things (IoMT) is a grouping of medical equipment and applications that communicate
with healthcare systems via online computer networks [6]. Given the millions of people who
suffer from cardiovascular disease, a technology like telemonitoring will make a tremendous
impact in properly controlling this long-term ailment and lowering the cost of treatment on
a massive scale. To solve labour shortages and improve access to care, we developed a TeCa
telemonitoring application for cardiovascular patients. The TeCa system automatically examines
the patient’s medical condition especially, ECG tracing via the AD8232 sensor. The data is then
processed with an Arduino Uno and important information is recorded in a distributed database.
The paper is organized as follows: we give some important systems for telemonitoring
cardiovascular diseases in Sec. 2 and describe the TeCa modelling in Sec. 3. Section 4 shows the
setup of TeCa. Finally, we conclude the paper with Sec. 5.
2. Iot health telemonitoring applications
The COVID-19 pandemic has fueled telehealth adoption, using virtual care options for the
first time in the last three years. Several applications for remote patient monitoring have been
proposed. Cardiology remote patient monitoring is one of the most sensitive domains, which
requires more attention than others [7].
Teladoc [8] is a unit of Teladoc Health, Inc., a mission-driven enterprise that is effectively
changing the way people access and experience healthcare. This involves developing data-
driven, tailored experiences that adapt to an individual’s changing healthcare requirements.
Clinicians may simply broaden their reach by using simple software and medical-grade telehealth
equipment. Teladoc offers real-time clinical cooperation with peers worldwide to handle the
most complex care concerns.
The digital front door of Orion Health is a secure, open, and scalable platform that enables
businesses to integrate new and current patient interaction technologies into a single, user-
friendly portal [9]. It addresses the fragmented consumer experience caused by silos by providing
a consistent, easy-to-use, multi-channel interface through which all interactions, including
symptom assessment, trusted health information, electronic referrals, access to complete medical
records, virtual care, and remote monitoring, can take place.
MedM is an expert in Enabling Connected Health™ and a maker of award-winning remote care
software platforms and personal health monitoring applications and portals [10]. It improves
the quality of care and patient satisfaction while reducing the overall cost of healthcare. The
principal aim of this system is to drive interoperability in the healthcare ecosystem, improving
the speed of information exchange between all parties involved.
Our previous research is based on Wordnet and Wup’s measure for automatic ontology
learning from heterogeneous relational databases [11]. This approach has been validated in the
food risks domain.
Recently, T.P.T.Armand et al. [12] develop a low-cost cardiovascular patient monitoring
system (RPM) with wireless capabilities that could be used in any region of Cameroon. RPM is
accessible, cheap, and capable of capturing important factors that accurately reflect the patient’s
condition and provide alerting mechanisms. In Cameroon, the availability of such remote
monitoring applications remains a big innovation.
There have been several telecardiology encounters in the world of cardiology. The primary
goal was most likely to create a relationship with primary care using teleconsultation methods,
with varying degrees of success. Within cardiology, ECG can aid in the detection of arrhythmias,
which occur when the heart beats too slowly, too rapidly, or irregularly.
In this context, we propose a telemonitoring application for patients with cardiovascular
diseases. The application used two lead heart rate monitors via an AD8232 ECG sensor and
Arduino Uno to transfer the data from AD8232 to the system. The developed TeCA (Telemoni-
toring of patients with cardiovascular diseases) system maintains user-friendliness and offers
several tasks, such as selecting the preferred doctor, chatting with the doctor’s caregiver, using
the ECG sensor associated with an explanatory video on how to use the sensor, and delivering
the electronic prescription, which must print it out by the patient or other patient’s assistant.
In addition, about the technical side, TeCa system is a web application programmed via the
Django framework of Python programing language, which provides the possibility to extend
the system by using artificial intelligence approaches, such as deep learning for auto-detection
of anomalies, ChatBot if the doctor is not accessible, etc.
3. The Teca modeling
The aim of our work is to develop a system that helps patients to take care of their cardiac health
at a distance, providing healthcare remotely, smart equipment, and remote medical operations.
We used the Merise modelling method. In the TeCa system, there are three main actors:
• Patient: The person that will be consulted in our system. Its roles are: to check the
doctor’s list, the capability to reach the doctor’s information, chat with its cardiologist
caregiver, and measure the heart rate in real-time using an IoT device connected to the
TeCa system.
• Doctor: The cardiologist, which will remotely consult the patient (consulting manager).
Its roles are: to check the list of consulted patients and prescriptions given to them, Chat
with the patient, and the capability to reach the patient’s information.
• Admin: or website administrator ensures that a website is functioning properly. It is the
one that validates the registration of doctors.
3.1. Treatments conceptual model
The treatments conceptual model (TCM) is one of Merise’s most well-known diagrams. It enables
the study of the information system’s dynamics, i.e. the event-driven processes performed
inside the system. The TCM figure of the patient is shown in Figure. 1.
We present TCM diagram of a doctor in cardiovascular disease, who uses our TeCa system
(see Figure. 2).
Figure 1: TCM of Patient
3.2. Conceptual data model
The conceptual data model (CDM) defines what the system contains. It aims to establish entities,
their attributes, and relationships (see Figure. 3).
4. The Teca setup
The setting up of the TeCa system is performed on an AMD Quad-Core A8-7410 2.5GHz, RAM
8Gb. Python is used as a programming language with Django as a Python web framework
Figure 2: TCM of Doctor
with a high degree of abstraction that allows for the quick building of safe and stable websites.
MySQL for storing data of patient, doctor, and ECG signal in the form of CSV, which will be
used for displaying the ECG tracing.
The doctor can accept or refuse any received request (see Figure. 4).
After accepting the patient’s request, the doctor will get information about the patient (see
Figure. 5).
The patient can view the doctor’s profile and send the request as a new patient or an old
Figure 3: CDM of TeCa system
patient. The patient waits for a response from a doctor when the doctor accepts the patient has
to confirm (see Figure. 6).
The patient must give his/her doctor the ECG result by following the five steps, which are
presented in Figure.7.
At the end of the consultation and depending on the health status of the patient, the doctor
can create a prescription. The patient can easily download his prescription in pdf format (see
Figure. 8).
5. Conclusion
This article outlines the design and deployment of a cardiovascular health monitoring system.
TeCa application services with home telemonitoring, patients would be able to live freely for
a longer amount of time, lowering the expense of medical equipment and the need for extra
Figure 4: Patient request list
Figure 5: Patient information
caregiver services.
From perspectives, we are planning first to go ahead with our developed TeCa system in
order to enhance its features: Intelligent application by using machine learning algorithms to
replace the doctor with a robot and predicting heart disease, using a cloud server for storing
the huge amount of medical data.
Finally, Federated Learning (FL), as an emerging distributed intelligence paradigm, is particu-
larly attractive for smart healthcare, by coordinating multiple datasets to perform AI training
without sharing data. We will improve the TeCa system in different healthcare centres and
develop a platform for distributed intelligence, keeping data secure and private.
Figure 6: Doctors list
Figure 7: ECG setting
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Figure 8: History Page
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