A flexible real-time surface electromyography-based wheelchair control system using upper arm or neck muscles
OBJECTIVE: People with movement disabilities face difficulties in independent mobility. The main objective of this study was to develop and evaluate a real-time electro-myography (EMG) based wheelchair control framework with upper arm or neck muscles and to investigate feasibility for assistive mobility applications. METHODS: A feature optimisation framework was employed to extract the most significant features for movement recognition. The proposed model was trained and tested in both offline and real-time control. Feasibility was assessed through classification accuracy, repeatability measures, response latency and preliminary validation involving two individuals with disabilities. RESULTS: With subject-independent methodology, wheelchair activation with upper arm muscles achieved an accuracy of 95% in real time, whereas for neck muscles, it was 98.6% in able-bodied participants. For neck muscles, two participants with disabilities, namely a transhumeral amputee and a mobility-impaired participant because of poliomyelitis were evaluated and achieved an accuracy of 100%. The average system response latency for upper arm movements was found to be 430 ms for able-bodied participants, whereas for neck muscles, it was 360 ms for able-bodied participants and 400 ms for participants with disabilities. CONCLUSION: The proposed framework demonstrated the feasibility of real-time EMG-based wheelchair control in a controlled environment. However, further studies involving larger and more diverse participant cohorts are needed to evaluate its generalisability and broader clinical applicability.
Authors
- X. Little Flower (ORCID: https://orcid.org/0000-0002-4217-7272)
- M. Sasikala
- S. Poonguzhali
- Nijisha Shajil
Institutions
- SRM Institute of Science and Technology (IN)
- Anna University, Chennai (IN)
- Saraswati Dental College and Hospital (IN)
Publication Details
- Journal
- Disability and Rehabilitation Assistive Technology
- Published
- 2026-06-29
- DOI
- https://doi.org/10.1080/17483107.2026.2692490
- Primary Topic
- Gaze Tracking and Assistive Technology
- Type
- article
- Field-Weighted Citation Impact
- 0.00