High-density EMG E-textile systems for the control of active prostheses.

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Wearable Sensors

Background:

• Effective myoelectric control of active prostheses relies on user-friendly electrode systems for daily application and repositioning.
• Existing electrode systems can be cumbersome, posing challenges for consistent and accurate electromyography (EMG) signal recording.

Purpose of the Study:

• To investigate the efficacy of Smart Fabric and Interactive Textile (SFIT) systems as an alternative for high-density EMG signal acquisition.
• To evaluate the performance of SFIT systems in enabling myoelectric control for prosthetic applications.

Main Methods:

• Developed a 100-electrode SFIT sleeve covering the upper and lower arm, arranged in four 5x5 grids.
• Recorded EMG signals from 3 subjects performing 9 wrist and hand tasks.
• Analyzed signals using wavelet coefficients and classified them with linear discriminant analysis.

Main Results:

• SFIT systems successfully recorded high-density EMG signals from multiple arm and hand movements.
• The classification accuracy for the nine tasks averaged 89.1 ± 1.9 %.
• Demonstrated the feasibility of SFIT for reliable muscle-machine interfacing.

Conclusions:

• SFIT systems provide a practical and effective solution for high-density EMG signal recording in myoelectric control.
• The proposed fabric-based electrode system shows significant potential for advancing active prosthesis control.
• This technology facilitates improved muscle-machine interfacing for users of active prostheses.