Long-Term Performance of Utah Slanted Electrode Arrays and Intramuscular Electromyographic Leads Implanted Chronically in Human Arm Nerves and Muscles

Abstract

ObjectiveWe explore the long-term performance and stability of seven percutanous Utah Slanted Electrode Arrays (USEAs) and intramuscular recording leads (iEMGs) implanted chronically in the residual arm nerves and muscles of three human amputees as a means to permanently restore sensorimotor function after upper-limb. ApproachWe quantify the number of functional recording and functional stimulating electrodes over time. We also calculate the signal-to-noise ratio of USEA and iEMG recordings and quantify the stimulation amplitude necessary to evoke detectable sensory percepts. Furthermore, we quantify the consistency of the sensory modality, receptive field location, and receptive field size of USEA-evoked percepts. Main ResultsIn the most recent subject, involving USEAs with technical improvements, neural recordings persisted for 502 days (entire implant duration) and the number of functional recording electrodes for one USEA increased over time. However, for six out of seven USEAs the number of functional recording electrodes decreased within the first two months after implantation. The signal-to-noise ratio of neural recordings and electromyographic recordings stayed relatively consistent over time. Sensory percepts were consistently evoked over the span of 14 months, were not significantly different in size, and highlighted the nerves fascicular organization. The percentage of percepts with consistent modality or consistent receptive field location between sessions (~1 month apart) varied between 0-86.2% and 9.1-100%, respectively. Stimulation thresholds and electrode impedances increased initially but then remained relatively stable over time. SignificanceThis work demonstrates improved performance of USEAs, and provides a basis for comparing the longevity and stability of USEAs to that of other neural interfaces. Although USEAs provide a rich repertoire of neural recordings and sensory percepts, performance still generally declines over time. Future work should leverage the results presented here to further improve USEA design or to develop adaptive algorithms that can maintain a high level of performance.