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.

Montagna, S., Ascari, R., Khorrami Chokami, A. (2025). Spectral Synchronicity of EMG Signals: An Application to the Erector Spinae Muscles of Sitting Violinists. In E. di Bella, V. Gioia, C. Lagazio, S. Zaccarin (a cura di), Statistics for Innovation IV SIS 2025, Short Papers, Contributed Sessions 3 (pp. 48-53). Springer [10.1007/978-3-031-96033-8_9].

Spectral Synchronicity of EMG Signals: An Application to the Erector Spinae Muscles of Sitting Violinists

Ascari, Roberto;
2025

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.
Capitolo o saggio
Clustering; EMG signals; Hierarchical Spectral Merger algorithm; spectral density
English
Statistics for Innovation IV SIS 2025, Short Papers, Contributed Sessions 3
di Bella, E; Gioia, V; Lagazio, C; Zaccarin, S
17-giu-2025
2025
9783031960321
Springer
48
53
Montagna, S., Ascari, R., Khorrami Chokami, A. (2025). Spectral Synchronicity of EMG Signals: An Application to the Erector Spinae Muscles of Sitting Violinists. In E. di Bella, V. Gioia, C. Lagazio, S. Zaccarin (a cura di), Statistics for Innovation IV SIS 2025, Short Papers, Contributed Sessions 3 (pp. 48-53). Springer [10.1007/978-3-031-96033-8_9].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/559736
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