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

Authors :
Irwin ZT
Schroeder KE
Vu PP
Tat DM
Bullard AJ
Woo SL
Sando IC
Urbanchek MG
Cederna PS
Chestek CA
Source :
Journal of neural engineering [J Neural Eng] 2016 Aug; Vol. 13 (4), pp. 046007. Date of Electronic Publication: 2016 Jun 01.
Publication Year :
2016

Abstract

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.<br />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.<br />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.<br />Significance: The RPNI signal strength, stability, and longevity demonstrated here represents a promising method for controlling advanced prosthetic limbs and fully restoring natural movement.

Details

Language :
English
ISSN :
1741-2552
Volume :
13
Issue :
4
Database :
MEDLINE
Journal :
Journal of neural engineering
Publication Type :
Academic Journal
Accession number :
27247270
Full Text :
https://doi.org/10.1088/1741-2560/13/4/046007