Multidimensional Mechanomyographic Assessment of Post-Loading Responses in the Forearm Flexor–Pronator Muscles

Mechanomyography (MMG) records mechanical vibrations generated by active muscle contraction and may provide a simple field-applicable method for detecting post-loading muscle responses. This study aimed to characterize post-loading changes in multidimensional and time–frequency MMG features of the forearm flexor–pronator muscles after a repetitive gripping exercise. Eight healthy volunteers were assessed bilaterally, yielding 16 forearms for exploratory analysis. MMG signals were recorded before loading, immediately after loading, and 24 h after loading from the volar forearm region overlying the superficial flexor–pronator muscle group, anatomically corresponding to the flexor digitorum superficialis. The loading task consisted of repeated gripping using a 30 kg grip trainer. Multiple MMG trials at each time point were averaged within each subject-arm unit. Time-domain, envelope-based, spectral, band-power, wavelet-energy, and exploratory spectrogram-derived band-power features were extracted using a reproducible Python 3.12 pipeline (Google Colaboratory environment). Changes across time points were assessed using Friedman tests, followed by Wilcoxon signed-rank tests with a multiplicity adjustment. After the false discovery rate correction, 11 of 23 conventional MMG features showed significant time effects. These features were concentrated in amplitude- and energy-related domains, including RMS, envelope, peak-to-peak amplitude, signal energy, and wavelet energy. They decreased immediately after loading and increased at 24 h. An exploratory spectrogram analysis showed similar temporal changes in the absolute band power across predefined frequency bands, whereas the relative band-power distribution remained stable. These findings suggest that a multidimensional MMG feature analysis can detect post-loading changes in the superficial forearm flexor–pronator region after a repetitive gripping exercise.

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Journal
Applied Sciences
Published
2026-07-23
DOI
https://doi.org/10.3390/app16157379
Primary Topic
Muscle activation and electromyography studies
Type
article
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article

Multidimensional Mechanomyographic Assessment of Post-Loading Responses in the Forearm Flexor–Pronator Muscles

Yutaka Mifune, Kanto Nagai, Issei Shinohara, Kohei Yamaura et al.
Applied Sciences
Muscle activation and electromyography studies
article

Multidimensional Mechanomyographic Assessment of Post-Loading Responses in the Forearm Flexor–Pronator Muscles

Yutaka Mifune, Kanto Nagai, Issei Shinohara, Kohei Yamaura, Ryohei Nako, Shinya Hayashi, Takanobu Higashi, Shunsaku Takigami, Ryosuke Kuroda, Atsuyuki Inui, Shin Osawa, Yutaka Ehara, Ryota Wakamatsu, Daiji Nakabayashi, Tomohiro Date
article en

Abstract

Mechanomyography (MMG) records mechanical vibrations generated by active muscle contraction and may provide a simple field-applicable method for detecting post-loading muscle responses. This study aimed to characterize post-loading changes in multidimensional and time–frequency MMG features of the forearm flexor–pronator muscles after a repetitive gripping exercise. Eight healthy volunteers were assessed bilaterally, yielding 16 forearms for exploratory analysis. MMG signals were recorded before loading, immediately after loading, and 24 h after loading from the volar forearm region overlying the superficial flexor–pronator muscle group, anatomically corresponding to the flexor digitorum superficialis. The loading task consisted of repeated gripping using a 30 kg grip trainer. Multiple MMG trials at each time point were averaged within each subject-arm unit. Time-domain, envelope-based, spectral, band-power, wavelet-energy, and exploratory spectrogram-derived band-power features were extracted using a reproducible Python 3.12 pipeline (Google Colaboratory environment). Changes across time points were assessed using Friedman tests, followed by Wilcoxon signed-rank tests with a multiplicity adjustment. After the false discovery rate correction, 11 of 23 conventional MMG features showed significant time effects. These features were concentrated in amplitude- and energy-related domains, including RMS, envelope, peak-to-peak amplitude, signal energy, and wavelet energy. They decreased immediately after loading and increased at 24 h. An exploratory spectrogram analysis showed similar temporal changes in the absolute band power across predefined frequency bands, whereas the relative band-power distribution remained stable. These findings suggest that a multidimensional MMG feature analysis can detect post-loading changes in the superficial forearm flexor–pronator region after a repetitive gripping exercise.

Applied SciencesVol. 16(15)
Kobe University (JP)
Openalex Percentile: Top 16%
Muscle activation and electromyography studies
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