Long-term upper-extremity prosthetic control using regenerative peripheral nerve interfaces and implanted EMG electrodes.

Vu, Philip P; Vaskov, Alex K; Lee, Christina; Jillala, Ritvik R; Wallace, Dylan M; Davis, Alicia J; Kung, Theodore A; Kemp, Stephen W P et al. · J Neural Eng · 2023

basic_science · Level V

Where this comes from

Abstract

<i>Objective.</i>Extracting signals directly from the motor system poses challenges in obtaining both high amplitude and sustainable signals for upper-limb neuroprosthetic control. To translate neural interfaces into the clinical space, these interfaces must provide consistent signals and prosthetic performance.<i>Approach.</i>Previously, we have demonstrated that the Regenerative Peripheral Nerve Interface (RPNI) is a biologically stable, bioamplifier of efferent motor action potentials. Here, we assessed the signal reliability from electrodes surgically implanted in RPNIs and residual innervated muscles in humans for long-term prosthetic control.<i>Main results.</i>RPNI signal quality, measured as signal-to-noise ratio, remained greater than 15 for up to 276 and 1054 d in participant 1 (P1), and participant 2 (P2), respectively. Electromyography from both RPNIs and residual muscles was used to decode finger and grasp movements. Though signal amplitude varied between sessions, P2 maintained real-time prosthetic performance above 94% accuracy for 604 d without recalibration. Additionally, P2 completed a real-world multi-sequence coffee task with 99% accuracy for 611 d without recalibration.<i>Significance.</i>This study demonstrates the potential of RPNIs and implanted EMG electrodes as a long-term interface for enhanced prosthetic control.

Medical subject headings