A flexible real-time surface electromyography-based wheelchair control system using upper arm or neck muscles.

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Assistive Technology

Background:

• Independent mobility is a significant challenge for individuals with movement disabilities.
• Existing assistive technologies may have limitations in providing intuitive and responsive control.

Purpose of the Study:

• To develop and evaluate a real-time electro-myography (EMG) based wheelchair control framework.
• To utilize upper arm or neck muscles for wheelchair operation.
• To investigate the feasibility of this system for assistive mobility applications.

Main Methods:

• A feature optimization framework was used for movement recognition.
• The model was trained and tested in both offline and real-time scenarios.
• Feasibility was assessed via classification accuracy, repeatability, response latency, and validation with two individuals with disabilities.

Main Results:

• Subject-independent wheelchair control using upper arm muscles achieved 95% real-time accuracy.
• Neck muscle control reached 98.6% accuracy in able-bodied participants and 100% in two participants with disabilities.
• System response latency was 430ms (upper arm) and 360-400ms (neck muscles).

Conclusions:

• The developed framework shows feasibility for real-time EMG-based wheelchair control in controlled settings.
• Further research with larger, diverse cohorts is necessary to confirm generalizability and clinical applicability.