Stage-specific EMG feature optimization for enhanced post-stroke hand gesture recognition
Brunnstrom stage-specific feature engineering substantially improves EMG gesture-classification accuracy over both healthy-derived and non-stage-stratified patient baselines while reducing computational load. These findings support adaptive, stage-aware designs for wearable rehabilitation systems and motivate larger Low-stage cohorts and models robust to sparse or low-SNR signals.
Authors
- Omar Mansour
- Hussein Sarwat (ORCID: https://orcid.org/0000-0002-3874-3462)
- Jie Jia (ORCID: https://orcid.org/0000-0002-4516-4629)
- Xinyu Song
- Peter B. Shull (ORCID: https://orcid.org/0000-0001-8931-5743)
- Zakir Ullah (ORCID: https://orcid.org/0000-0003-3079-7105)
Institutions
- Shanghai Jiao Tong University (CN)
- Huashan Hospital (CN)
Publication Details
- Journal
- Journal of NeuroEngineering and Rehabilitation
- Published
- 2025-12-07
- DOI
- https://doi.org/10.1186/s12984-025-01807-5
- Primary Topic
- Muscle activation and electromyography studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00