Muscle Fatigue Investigation Using sEMG Signals and a DAQ Card Data Acquisition System in LabVIEW.

The aim of this study is to implement a custom-designed data acquisition system with a DAQ card, based on the virtual instrument concept in the LabVIEW environment, to investigate and analyze muscle fatigue using surface electromyography (sEMG) signals. The experiment was conducted as a pilot case study on a healthy volunteer, where sEMG signals from the biceps brachii muscle were collected during cyclic weighted exercises. Signal registration was performed across three distinct states: no fatigue, moderate fatigue, and high fatigue. The developed measurement system enabled signal acquisition, filtering, and analysis through both online processing and post-processing. Time-domain parameters (ARV, RMS, Umax) and frequency-domain parameters (ΣPS, MNF, MDF) were determined from three series of measurements. An analysis of parameter changes was conducted both within and between the series. The results indicated that with the onset of muscle fatigue, the participant exhibited a decrease in amplitude parameters and a shift in the power spectrum toward lower frequencies. Frequency-domain parameters, particularly MNF, exhibited higher diagnostic sensitivity than amplitude parameters. The obtained results confirm the technical feasibility of the developed virtual instrument for sEMG signal analysis. Furthermore, they suggest its potential utility for objective muscle condition assessment, establishing an engineering baseline for future research.