Applying ECG Signal Analysis for Personalized Neuromuscular Rehabilitation and Performance Enhancement

Abstract

This project investigates the application of electrocardiogram (ECG) signal analysis in personalized neuromuscular rehabilitation and performance enhancement, focusing on the biceps brachii muscle. Using an oscilloscope, ECG data were captured through three-lead placements to examine the muscle's electrical activity under varying exertion conditions. Fast Fourier Transform (FFT) analysis in MATLAB provided detailed frequency domain insights into motor unit recruitment patterns. The findings establish correlations between ECG signal variations and muscle activation levels, offering implications for optimizing rehabilitation strategies, improving muscle training protocols, and enhancing neuromuscular performance.