Electromyography (EMG) Wireless for Rehabilitation Process

Abstract

Rehabilitation is a one of the critical processes for patients recovering from muscle-related conditions. However, current practices do not have an accurate or dependable system to track progress and parameters during recovery sessions, which automatically affects the efficiency and effectiveness of the rehabilitation process. Additionally, patients residing in rural areas face significant challenges in attending regular rehabilitation sessions at the hospitals or any rehabilitation centre, leading to lower attendance rates and potential gaps in recovery. This project focuses on developing a wireless Electromyography (EMG) system for rehabilitation purposes as it will track the patient progress. The methodology includes a main system responsible for continuous monitoring and data transmission using an ESP32 microcontroller, EMG sensors, LCD displays, and the Blynk IoT platform for real-time visualization. A sub-system is triggered when the push button is activated, initiating a 7-second measurement phase. During this phase, the system captures the highest EMG signal and its corresponding percentage, providing a detailed analysis of muscle activity. This modular approach ensures a smooth operation between real-time monitoring and targeted measurement processes. Results demonstrate the system ability to record muscle activity accurately, with Subject A (normal BMI) achieving a peak EMG value of 4095 bits and 100% contraction during testing. Signal verification showed that the recorded EMG signal pattern closely aligns with the M-wave characteristics identified in prior research, confirming its reliability and physiological relevance. The project concludes that the developed system is effective for rehabilitation applications and offers a foundation for future improvements, such as data analytics and cloud storage integration, to enhance its utility and accessibility.