Arduino-Based Myoelectric Control: Towards Longitudinal Study of Prosthesis Use

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Human-Computer Interaction

Background:

• Improving upper-limb prosthesis control algorithms and components requires understanding real-world usage.
• Current research often lacks community-based prosthesis use studies due to cost, battery limitations, and poor generalization.
• Home-based prosthetic applications face challenges in implementation and user support.

Purpose of the Study:

• To design a cost-effective Arduino-based myoelectric control system for upper-limb prostheses suitable for home studies.
• To prioritize robustness, user-friendly control adjustments, and user support in the system's design.
• To evaluate the system's robustness and implement real-time control algorithms for prosthetic applications.

Main Methods:

• Developed a cost-effective Arduino-based myoelectric control system incorporating wearable electromyogram (EMG) sensors.
• Focused design considerations on robustness, user-friendly adjustments, and user support for home-based applications.
• Implemented and tested three control algorithms: direct control, abstract control, and linear discriminant analysis (LDA) classification.

Main Results:

• The developed system is Arduino-based, cost-effective, and utilizes wearable EMG sensors.
• Design emphasized robustness and user-friendliness for home-based prosthetic use.
• System robustness was evaluated through continuous laboratory operation, and a real-time abstract decoder implementation was demonstrated.

Conclusions:

• The proposed system offers a viable, cost-effective solution for myoelectric upper-limb prosthesis control in home settings.
• The design prioritizes practical considerations for long-term user engagement and improved prosthetic functionality.
• Further research can leverage this system for enhanced prosthetic control algorithms and real-world application studies.