Use of RPNIs and Implanted Electrodes for Prosthetic Wrist and Multi-Grip Hand Control during Functional Tasks: A Case Study.

Abstract

Surface electromyography (sEMG) pattern recognition prosthetic systems are unintuitive and cannot control many movements reliably due to electrode shifting and limited residual muscle signals. Intramuscular electrodes and regenerative peripheral nerve interfaces (RPNIs) can improve signal quality and provide additional control signals for controlling more degrees of freedom, including wrist rotation. This case study compared functional, biomechanical, and cognitive outcomes between control approaches incorporating active wrist rotation using sEMG and implanted intramuscular EMG (imEMG) signals from RPNIs and residual muscles. We also explored whether combining the EMG sources for wrist rotation could provide further advantages due to the lack of available implanted wrist rotation signals. One female with unilateral transradial amputation completed functional assessments using a myoelectric prosthesis with five control approaches. Pattern recognition classifiers were trained to decode sEMG and/or imEMG from residual muscles and RPNIs into functional grips with or without wrist rotation. The participant improved performance of the Clothespin Relocation Test and Coffee Task when using imEMG compared to sEMG, regardless of whether wrist rotation was enabled. Adding wrist rotation only modestly reduced trunk compensations ($\Delta$2-7$^{\circ }$). imEMG with wrist had substantially lower cognitive workload than sEMG ($\Delta$58 pts). A combined classifier was associated with improved performance and the lowest cognitive workload (0 pts). In this participant, EMG from implanted electrodes in RPNIs supported the control of multiple grips and active wrist rotation to achieve better functional performance than with sEMG, without added cognitive burden. These findings highlight the potential of implanted intramuscular EMG signals from RPNIs and residual muscles for improving prosthetic control during daily tasks.