Analysing the intermittent activation of postural muscles is crucial for understanding central nervous system control strategies. This work focuses on postural control mechanisms in seated musicians, for whom fatigue and asymmetrical load distribution can lead to muscular problems. To that end, the Hierarchical Spectral Merger method is applied to spectra of surface electromyography signals recorded from nine violinists to identify clusters of spectrally synchronised signals. The minimum Total Variation Distance is used to determine the optimal number of clusters for each violinist. Results indicate synchronisation between the right and left muscle activations, suggesting a symmetric control pattern.

Spectral synchronicity of EMG signals: an application to the erector spinae muscles of sitting violinists

Amir Khorrami Chokami
2025-01-01

Abstract

Analysing the intermittent activation of postural muscles is crucial for understanding central nervous system control strategies. This work focuses on postural control mechanisms in seated musicians, for whom fatigue and asymmetrical load distribution can lead to muscular problems. To that end, the Hierarchical Spectral Merger method is applied to spectra of surface electromyography signals recorded from nine violinists to identify clusters of spectrally synchronised signals. The minimum Total Variation Distance is used to determine the optimal number of clusters for each violinist. Results indicate synchronisation between the right and left muscle activations, suggesting a symmetric control pattern.
2025
978-3-031-96032-1
Clustering; EMG signals; Hierarchical Spectral Merger algorithm; spectral density
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/457632
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