Objective: Advancement in prosthetic limb technology requires corresponding improvements in the capability of the amputee to naturally control the device via original motor pathways while simultaneously receiving haptic feedback via sensory pathways. Recording efferent axonal activity using a peripheral neural interface (PNI) allows a good tradeoff between invasiveness and selectivity while possibly preserving the phenomenology of controlling the original limb. One such PNI, the thin-film transverse intrafascicular multichannel electrode (tfTIME), has been shown to be successful in controlling powered prosthetics. However, the tfTIME is highly susceptible to stimulation artifact; thus, using such a PNI to both record efferent motor signals while concurrently stimulating afferent sensory axons in the same nerve is problematic. The micro-channel sieve electrode could also provide a stable, selective, neural interface with larger signal-to-noise levels that are less susceptible to concurrent stimulation artifact or other external noise effects.
Approach: This study uses a computational model to compare recording levels of simulated ENGs across neural drive levels as well as basic control signals derived from the ENGs in both tfTIME and micro-channel sieve PNIs. A motor neuron pool model generated axon firing rates at a given neural drive. The time course of the corresponding extracellular currents of the myelinated motor axons were determined using core conductor axon models. Finite element models determined the contribution of the extracellular current from nodes of Ranvier on potentials recorded using each interface. Contributions from each node were combined to create the final ENG.
Main results: ENGs recorded using the micro-channel sieves were shown to have much higher amplitudes compared to ENGs recorded using the tfTIMEs. Signal amplitudes also varied less as a function of axonal placement and spike timing, resulting in more consistent signals with amplitudes determined predominantly by neural drive.
Significance: Simulation results suggest that the micro-channel sieve provides higher quality control signals over tfTIME PNIs in decoding ENGs. Coupling these results with concurrent stimulation results of the companion paper (Part B: stimulation) suggests that the micro-channel sieve is an optimal bidirectional PNI.