Sistema de Eletromiografia Adaptado - SEMA

Abstract

Surface Electromyography has established itself as an important tool for studying muscle activity, with applications in areas such as rehabilitation, the development of assistive devices, Human-Machine Interfaces for the control of active orthoses and prostheses, motion-based control systems, and augmented reality. In this context, the present work introduces the development of a system for the acquisition, processing, and analysis of surface electromyography signals. The proposed system consists of two independent channels, featuring an instrumentation amplifier with a calculated gain of 300 times, high-pass and low-pass filters with cutoff frequencies set between 5 Hz and 500 Hz, and an ESP32 microcontroller, which processes the captured signals and makes them available for download through an HTTP server. Additionally, a MATLAB graphical interface enables the analysis of the acquired signals, implementing functions such as Root Mean Square (RMS) and Mean Absolute Value (MAV), moving average and median filter, linear envelope, mean and median frequencies, frequency indices, numerical and cumulative integration, autocorrelation, amplitude normalization, zero-padding, and digital filtering. The tests conducted showed an amplification gain of 302 times the input signal and filtering between 4.45 Hz and 460.23 Hz, with data collection performed through four biceps contractions over a 10-second interval. The results demonstrate the system's feasibility for neuromuscular activity studies. The system enables advanced analyses, such as identifying the temporal and spectral patterns of EMG signals, standing out for its affordable cost, ease of use, and integration of hardware and software.