Chronic recording of hand prosthesis control signals via a regenerative peripheral nerve interface in a rhesus macaque

• Published in: Journal of neural engineering 2016-08, Vol.13 (4), p.046007-046007
• Main Authors: Irwin, Z T, Schroeder, K E, Vu, P P, Tat, D M, Bullard, A J, Woo, S L, Sando, I C, Urbanchek, M G, Cederna, P S, Chestek, C A
• Format: Article
• Language: English
• Subjects: Animals; Artificial Limbs - adverse effects; chronic recording; Electrodes, Implanted - adverse effects; Electromyography; Fingers - innervation; Fingers - physiology; Hand; Macaca mulatta; Movement - physiology; Muscle, Skeletal - innervation; Muscle, Skeletal - physiology; Nerve Regeneration; peripheral nerve; Peripheral Nerves - physiology; prosthesis control; Prosthesis Design; Psychomotor Performance; Signal-To-Noise Ratio
• ISSN: 1741-2560; 1741-2552
• DOI: 10.1088/1741-2560/13/4/046007

Objective. Loss of even part of the upper limb is a devastating injury. In order to fully restore natural function when lacking sufficient residual musculature, it is necessary to record directly from peripheral nerves. However, current approaches must make trade-offs between signal quality and longevity which limit their clinical potential. To address this issue, we have developed the regenerative peripheral nerve interface (RPNI) and tested its use in non-human primates. Approach. The RPNI consists of a small, autologous partial muscle graft reinnervated by a transected peripheral nerve branch. After reinnervation, the graft acts as a bioamplifier for descending motor commands in the nerve, enabling long-term recording of high signal-to-noise ratio (SNR), functionally-specific electromyographic (EMG) signals. We implanted nine RPNIs on separate branches of the median and radial nerves in two rhesus macaques who were trained to perform cued finger movements. Main results. No adverse events were noted in either monkey, and we recorded normal EMG with high SNR (>8) from the RPNIs for up to 20 months post-implantation. Using RPNI signals recorded during the behavioral task, we were able to classify each monkey's finger movements as flexion, extension, or rest with >96% accuracy. RPNI signals also enabled functional prosthetic control, allowing the monkeys to perform the same behavioral task equally well with either physical finger movements or RPNI-based movement classifications. Significance. The RPNI signal strength, stability, and longevity demonstrated here represents a promising method for controlling advanced prosthetic limbs and fully restoring natural movement.