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Intra- and Inter-Individual Spectral Pattern Variability of sEMG in Elbow Flexor Motor Tasks
Piotr S Wawryka1, Ludwin Molina Arias1, Grzegorz Frankowski2,3
1Department of Biocybernetics and Biomedical Engineering, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Krakow, Mickiewicza 30, 30-059 Krakow, Poland.
Abstract:
Understanding intra- and inter-individual variability in muscle activation is essential for applications in rehabilitation, ergonomics, and motor control research. Surface electromyography (sEMG) provides a non-invasive tool to study these patterns by capturing the electrical activity of muscles. This study investigated the spectral pattern variability of sEMG signals recorded from the biceps brachii and brachioradialis during repeated near-maximal isometric elbow flexion tasks with supinated and neutral forearm postures. sEMG signals from 33 healthy adults were analyzed in the frequency domain to obtain power spectra for each repetition. Intra-individual variability was quantified by comparing each repetition to a participant-specific reference spectrum, while inter-individual variability was assessed by comparing these reference spectra across participants using distance-based metrics. Statistical analyses revealed systematic posture-dependent differences, with the neutral forearm posture generally exhibiting greater spectral variability than the supinated posture, particularly in the biceps brachii. These findings highlight potential posture-related trends in neuromuscular activation; however, they should be interpreted with caution, as variability may also reflect differences in contraction intensity, fatigue, or task-specific biomechanics.
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