Restoring tactile sensations via neural interfaces for real-time force-and-slippage closed-loop control of bionic hands

Abstract

Despite previous studies on the restoration of tactile sensation to the fingers and the hand, there are no examples of use of the routed sensory information to finely control a prosthestic hand in complex grasp and manipulation tasks. Here, it is shown that force and slippage sensations can be elicited in an amputee by means of biologically inspired slippage detection and encoding algorithms, supported by a stick-slip model of the performed grasp. A combination of cuff and intraneural electrodes was implanted for 11 weeks in a young woman with hand amputation and was shown to provide close-to-natural force and slippage sensations, paramount for substantially improving manipulative skills with the prosthesis. Evidence is provided about the improvement of the participant's grasping and manipulation capabilities over time resulting from neural feedback. The elicited tactile sensations enabled the successful fulfillment of fine grasp and manipulation tasks with increasing complexity. Grasp performance was quantitatively assessed by means of instrumented objects and a purposely developed metrics. Closed-loop control capabilities enabled by the neural feedback were compared with those achieved without feedback. Further, the work demonstrates that the described amelioration of motor performance in dexterous tasks had as central neurophysiological correlates changes in motor cortical plasticity and that such changes were not of purely motor origin, but were the effect of a strong and persistent drive of the sensory feedback.