Objective. Electrical stimulation is a blunt tool for evoking neural activity. Neurons are naturally activated asynchronously and non-uniformly, whereas stimulation drives simultaneous activity within a population of cells. These differences in activation pattern can result in unintended side effects, including muddled sensory percepts and undesirable muscle contractions. These effects can be mitigated by the placement of electrodes in close approximation to nerve fibers and careful selection of the neural interface's location. This work describes the benefits of placing electrodes within specific fascicles of peripheral nerve to form selective neural interfaces for bidirectional neuroprosthetic devices. Approach. Chronic electrodes were targeted to individual fascicles of the ulnar and median nerves in the forearm of four human subjects. During the surgical implant procedure, fascicles were dissected from each nerve, and functional testing was used to identify the relative composition of sensory and motor fibers within each. FAST-LIFE arrays, composed of longitudinal intrafascicular arrays and fascicular cuff electrodes, were implanted in each fascicle. The location, quality, and stimulation parameters associated with sensations evoked by electrical stimulation on these electrodes were characterized throughout the 90–180 d implant period. Main results. FAST-LIFE arrays enable selective and chronic electrical stimulation of individual peripheral nerve fascicles. The quality of sensations evoked by stimulation in each fascicle is predictable and distinct; subjects reported tactile and cutaneous sensations during stimulation of sensory fascicles and deeper proprioceptive sensations during stimulation of motor fascicles. Stimulation thresholds and strength-duration time constants were typically higher within sensory fascicles. Significance. Highly selective, stable neural interfaces can be created by placing electrodes within and around single fascicles of peripheral nerves. This method enables targeting electrodes to nerve fibers that innervate a specific body region or have specific functions. Fascicle-specific interfacing techniques have broad potential to maximize the therapeutic effects of electrical stimulation in many neuromodulation applications. (Clinical Trial ID NCT02994160.)
ObjectiveWhile prosthetic hands with independently actuated digits have become commercially available, state-of-the-art human-machine interfaces (HMI) only permit control over a limited set of grasp patterns, which does not enable amputees to experience sufficient improvement in their daily activities to make an active prosthesis useful.ApproachHere we present a technology platform combining fully-integrated bioelectronics, implantable intrafascicular microelectrodes and deep learning-based artificial intelligence (AI) to facilitate this missing bridge by tapping into the intricate motor control signals of peripheral nerves. The bioelectric neural interface includes an ultra-low-noise neural recording system to sense electroneurography (ENG) signals from microelectrode arrays implanted in the residual nerves, and AI models employing the recurrent neural network (RNN) architecture to decode the subject’s motor intention.Main resultsA pilot human study has been carried out on a transradial amputee. We demonstrate that the information channel established by the proposed neural interface is sufficient to provide high accuracy control of a prosthetic hand up to 15 degrees of freedom (DOF). The interface is intuitive as it directly maps complex prosthesis movements to the patient’s true intention.SignificanceOur study layouts the foundation towards not only a robust and dexterous control strategy for modern neuroprostheses at a near-natural level approaching that of the able hand, but also an intuitive conduit for connecting human minds and machines through the peripheral neural pathways.Clinical trialDExterous Hand Control Through Fascicular Targeting (DEFT). Identifier: NCT02994160.
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