Automated assessment of upper limb spasticity in stroke patients with fusion of multichannel surface electromyography features
Compared with single-channel and single-feature models, the k-NN model, which uses multichannel sEMG features, has superior accuracy in spasticity assessments and is a reliable tool for objective evaluation. This approach holds promise for enhancing rehabilitation strategies by enabling precise and data-driven efficacy assessments, ultimately improving patient outcomes.
Authors
- Yaobin Long (ORCID: https://orcid.org/0000-0001-9093-0399)
- Li Tian (ORCID: https://orcid.org/0000-0002-6022-2137)
- Xin Li (ORCID: https://orcid.org/0000-0002-2977-5075)
- Xu Zhang (ORCID: https://orcid.org/0000-0002-1533-4340)
- Lin Chen (ORCID: https://orcid.org/0000-0002-1005-1202)
- Shengliang Shi
- Feiyu Nong
Institutions
- Guangxi University (CN)
- Guangxi Medical University (CN)
- Tianjin Nankai Hospital (CN)
- First Affiliated Hospital of GuangXi Medical University (CN)
- The Second Nanning People's Hospital (CN)
- Tianjin Medical University (CN)
Publication Details
- Journal
- Journal of Rehabilitation Medicine
- Published
- 2025-08-28
- DOI
- https://doi.org/10.2340/jrm.v57.43745
- Citations
- 1
- Primary Topic
- Botulinum Toxin and Related Neurological Disorders
- Type
- article
- Field-Weighted Citation Impact
- 1.39
Funders
- Natural Science Foundation of Guangxi Province
- Guangxi Medical University