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BRIEF RESEARCH REPORT article
Front. Hum. Neurosci.
Sec. Motor Neuroscience
Volume 19 - 2025 |
doi: 10.3389/fnhum.2025.1523358
Frequency-domain correlation analysis of upper limb muscle activity in wheelchair fencers
Provisionally accepted- Opole University of Technology, Opole, Poland
The aim of the study was to investigate neuromuscular conduction in wheelchair fencers using the EMG signal from their upper limb muscles. The recorded EMG signals were subjected to time-frequency transformations. The scalograms were determined using the continuous wavelet transform. Based on the analysis, time-frequency coherence maps were extracted to determine validation in the frequency bands: 2-16 Hz, 17-30 Hz, and 31-60 Hz. The study participants were 16 wheelchair fencers, members of the Polish Paralympic Team, in two disability categories: A and B. Results: The analysis revealed the individual time-dependent coherence between two signals for different frequencies during the work cycle of the antagonist muscles of the arm (biceps/triceps) and forearm (flexor/extensor carpi radialis). A significant difference in alpha coherence (2-16 Hz) occurred in the group of forearm muscles in the frequency band of 2-16 Hz, both for G (p=0.042) and M (p=0.031) parameters (G:A-0.08 Hz, B-0.04 Hz; M:A-0.51 and B -0.42). Some differences in gamma coherence were also found in the EMG signals of the forearm muscles in the 31-60 Hz frequency band were statistically significant (p=0.031): 0.43 in group A and 0.36 in group B.The results showed the neuromuscular conduction, where alpha coherence reflects the reticulospinal tract responsible for the excitation of the distal muscles of the wrist and hand, while gamma coherence results from cortical signals. It is related to efferent conduction and reflects corticomuscular coupling. Frequency domain coherence analysis determines the strength of intermuscular synchronization, allowing a comprehensive investigation of the neural mechanisms underlying motor recovery.
Keywords: intermuscular synchronization1, disability sports2, Wavelet analysis3, cross-correlation4, frequency bands5
Received: 05 Nov 2024; Accepted: 28 Jan 2025.
Copyright: © 2025 Błaszczyszyn, Piechota, Borysiuk, Kręcisz and Zmarzły. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Monika Błaszczyszyn, Opole University of Technology, Opole, Poland
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