Decoding of grasping information from neural signals recorded using peripheral intrafascicular interfaces

Area of Science:

• Neuroscience
• Biomedical Engineering
• Rehabilitation Technology

Background:

• Restoring complex hand function requires a seamless bidirectional link between the nervous system and prosthetic hands.
• Implantable interfaces, such as intrafascicular electrodes, offer a promising approach for this neural connection.
• Achieving a natural and intuitive flow of information is crucial for effective prosthetic control.

Purpose of the Study:

• To investigate the feasibility of decoding motor commands from the peripheral nervous system for prosthetic hand control.
• To evaluate the performance of thin-film longitudinal intra-fascicular electrodes in a human amputee.
• To assess the potential for a neuro-controlled hand prosthesis.

Main Methods:

• Thin-film longitudinal intra-fascicular electrodes were implanted in the median and ulnar nerves.
• A four-week trial was conducted with an amputee participant.
• Spike sorting and classification algorithms were implemented to decode motor commands.

Main Results:

• Motor information, including grip types and finger movements, was extracted with approximately 85% classification accuracy.
• The system demonstrated the user's improving ability to control motor commands over time.
• Enhanced discrimination ability of the classification algorithm indicated improved neural decoding.

Conclusions:

• The study demonstrates the potential of intrafascicular electrodes for developing neuro-controlled prosthetic hands.
• These findings open promising avenues for advanced prosthetic limb restoration.
• The research highlights the possibility of achieving intuitive and effective bidirectional communication with artificial devices.