Restoring continuous finger function with temporarily paralyzed nonhuman primates using brain–machine interfaces

作者：Samuel R. Nason, Matthew J. Mender, Eric Kennedy, Joris M. Lambrecht, Kevin L. Kilgore, Srinivas Chiravuri, Nishant Ganesh Kumar, Theodore A. Kung, Matthew S. Willsey, Cynthia A. Chestek, Parag G. Patil · 发表于：Journal of Neural Engineering · 年份：2023 · DOI：10.1088/1741-2552/accf36 · 被引用次数：8 · 研究领域：EEG and Brain-Computer Interfaces、Neuroscience and Neural Engineering、Muscle activation and electromyography studies

Abstract Objective. Brain–machine interfaces (BMIs) have shown promise in extracting upper extremity movement intention from the thoughts of nonhuman primates and people with tetraplegia. Attempts to restore a user’s own hand and arm function have employed functional electrical stimulation (FES), but most work has restored discrete grasps. Little is known about how well FES can control continuous finger movements. Here, we use a low-power brain-controlled functional electrical stimulation (BCFES) system to restore continuous volitional control of finger positions to a monkey with a temporarily paralyzed hand. Approach. We delivered a nerve block to the median, radial, and ulnar nerves just proximal to the elbow to simulate finger paralysis, then used a closed-loop BMI to predict finger movements the monkey was attempting to make in two tasks. The BCFES task was one-dimensional in which all fingers moved together, and we used the BMI’s predictions to control FES of the monkey’s finger muscles. The virtual two-finger task was two-dimensional in which the index finger moved simultaneously and independently from the middle, ring, and small fingers, and we used the BMI’s predictions to control movements of virtual fingers, with no FES. Main results. In the BCFES task, the monkey improved his success rate to 83% (1.5 s median acquisition time) when using the BCFES system during temporary paralysis from 8.8% (9.5 s median acquisition time, equal to the trial timeout) when attempting...