A Wearable Open-Source Neuroprosthesis/Neuro-Orthosis for Restoring Hand Function.

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Neuroprosthetics

Background:

• Cervical spinal cord injuries and stroke often result in significant hand dysfunction.
• Existing assistive and rehabilitative technologies can be costly and lack customization.
• Restoring hand function is crucial for independence and quality of life.

Purpose of the Study:

• To present a wearable, open-source system integrating electromyography (EMG) and functional electrical stimulation (FES).
• To restore hand function in individuals with disabilities from cervical spinal cord injuries or stroke.
• To provide an affordable, customizable, and accessible solution for hand rehabilitation.

Main Methods:

• Developed a system capturing volitional muscle signals (EMG) to interpret movement intent.
• Utilized analyzed EMG data to trigger functional electrical stimulation (FES) of impaired muscles.
• Designed modular hardware, software, and 3D-printable components, shared via GitHub for accessibility.

Main Results:

• The system successfully translates user intent into muscle stimulation for hand movement.
• Demonstrated the system's efficacy as both an orthotic device for grasping and a therapeutic tool for rehabilitation.
• Highlighted the system's affordability, modularity, and ease of customization.

Conclusions:

• The developed EMG-FES system offers a viable, user-centered approach to restoring hand function.
• Open-source sharing of hardware, software, and designs promotes collaboration and innovation in assistive technology.
• This initiative lowers barriers to advanced rehabilitation solutions for individuals with disabilities.