Detecting muscle fatigue among community-dwelling senior adults with shape features of the probability density function of sEMG
This study investigated PDF shape features of sEMG signals during a handgrip exercise to identify muscle fatigue in older adults in community experiments. Results revealed significant changes in kurtosis upon fatigue, indicating that PDF shape features were suitable convenient detectors of muscle fatigue in community experiments. The proposed indicator, TMK, showed potential sensitivity in tracking muscle fatigue over time in community-based settings with limited computational complexity, highlighting the promise of sEMG's PDF features in detecting muscle fatigue among the elderly.
Authors
- Le Zhang (ORCID: https://orcid.org/0000-0003-1841-1986)
- Jiarui Ou (ORCID: https://orcid.org/0009-0004-6261-6588)
- Ning Jiang (ORCID: https://orcid.org/0000-0003-1579-3114)
- Na Li (ORCID: https://orcid.org/0000-0003-3810-0907)
- Haoru He (ORCID: https://orcid.org/0009-0006-7851-955X)
- Jiayuan He
Institutions
- Sichuan University (CN)
- West China Medical Center of Sichuan University (CN)
- West China Hospital of Sichuan University (CN)
Publication Details
- Journal
- Journal of NeuroEngineering and Rehabilitation
- Published
- 2024-11-04
- DOI
- https://doi.org/10.1186/s12984-024-01497-5
- Citations
- 42
- Primary Topic
- Muscle activation and electromyography studies
- Type
- article
- Field-Weighted Citation Impact
- 7.75
Funders
- National Natural Science Foundation of China
- Centre Scientifique et Technique du Bâtiment
- National Science and Technology Major Project
- Sichuan Province Science and Technology Support Program
- West China Hospital, Sichuan University