A Health Monitoring System Using IoT-Based Android Mobile Application
Abstract
Numerous types of research on healthcare monitoring systems
have been conducted for calculating heart rate, ECG, nasal/oral airflow,
temperature, light sensor, and fall detection sensor. Different researchers have
done different work in the field of health monitoring with sensor networks.
Different researchers used built-in apps, such as some used a small number
of parameters, while some other studies used more than one microcontroller
and used senders and receivers among the microcontrollers to communicate,
and outdated tools for study development. While no efficient, cheap, and
updated work is proposed in the field of sensor-based health monitoring
systems. Therefore, this study developed an android-based mobile system that
can remotely monitor electrocardiograms (ECGs), pulse oximetry, heart rate,
and body temperature. The microcontroller’s Wi-Fi device is used to manage
wireless data transport. The findings of the patient are saved on the Firebase
server for further usage in the mobile app. The performance of the proposed
device is tested on ten numbers of different patients age-wise in terms of
beats per minute (BPM), ECG, Temperature, and SpO2. This system uses
temperature, pulse, ECG, blood pressure, and eye blink sensors. This device
makes the usage of a tiny pulse sensor that has been designed to provide an
accurate and optimal readout of the pulse rate and a temperature sensor is
also included. With the help of an MCU, our system measures the pulse rate
in beats per minute (bpm), blood oxygen level temperature measurements,
and ECG readings and communicates this information to the Firebase server.
To check the performance of the proposed system first, the BPM parameter
was checked on the cardiac monitor. Then, the proposed model is tested on
different patients age-wise. The simulation result shows that the BPM reading
is not much different than the BPM of the cardiac monitor. According to
the simulation findings, the proposed model achieved the best performance
as compared to commercially available devices.