Fabrication of a Low-Cost Real-Time Mobile ECG System for Health Monitoring

TL;DR

This paper presents a low-cost, real-time mobile ECG system using minimal electrodes and simple components, enabling easy and affordable heart monitoring without professional assistance.

Contribution

The study introduces a novel portable ECG device with only three electrodes, simplified circuitry, and Bluetooth transmission, making heart monitoring more accessible and user-friendly.

Findings

Achieved a signal-to-noise ratio of 50dB.

Successfully recorded and analyzed ECG signals from 10 subjects.

Developed a mobile application with a Pan-Tompkins based heartbeat detection algorithm.

Abstract

The electrocardiogram (ECG) signal is one of the most vital signals that can be used to investigate the performance of heart. Based on the ECG graph, we can identify different disorders and diseases. Therefore, monitoring this signal is of great importance. Many electrodes (usually 12) are employed to acquire this signal in clinics and hospitals; therefore, a nurse must install them on the body of the patient to record the signal. In this project, we built a device that can acquire the real-time ECG signal and display it on the mobile screen with the least number of electrodes (three electrodes) without requiring a nurse to install the electrodes using the simplest and cheapest type of ICs and transmitters including STM32F030F4P6 microcontroller, AD620 instrumentation amplifier, TL084 amplifier, TC7660 voltage converter, LM1117 regulator, and HC-05 Bluetooth module. Moreover, the device was designed in a way that could operate using a single 9V battery or power adaptor. First, to amplify the signal and remove a part of its noise, the ECG signal is given to the primary analog circuit. Then, in the digital section, using a microcontroller, the signal is discretized, processed, and finally transmitted to a mobile phone for final processing, information extraction, and displaying. In the mobile-written application, we developed a mathematical algorithm based on Pan-Tompkins algorithm to calculate the heartbeat rate, in which the signal peaks are determined after several processing steps using a threshold. In this regard, the ECG signals of 10 subjects were recorded and analyzed to calculate the optimum threshold. Finally, the power spectral density (PSD) and input referred noise were calculated and plotted to check the output signal quality. Based on the PSD and input referred noise amplitudes, we achieved a signal-to-noise ratio of 50dB.