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Despite previous studies on the restoration of tactile sensation on the fingers and the hand, there are no examples of use of the routed sensory information to finely control the prosthesis hand in complex grasp and manipulation tasks. Here it is shown that force and slippage sensations can be elicited in an amputee subject 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 eleven weeks in a young woman with hand amputation, and was shown to provide close-to-natural force and slippage sensations, paramount for significantly improving the subject’s manipulative skills with the prosthesis. Evidence is provided about the improvement of the subject’s grasping and manipulation capabilities over time, thanks to 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 to those achieved without feedback. Further, the work investigates whether the described amelioration of motor performance in dexterous tasks had as central neurophysiological correlates changes in motor cortex plasticity and whether such changes were of purely motor origin, or else the effect of a strong and persistent drive of the sensory feedback.

The efficacy of standard rehabilitative therapy for improving upper limb functions after stroke is limited; thus, alternative strategies are needed. Vagus nerve stimulation (VNS) paired with rehabilitation is a promising approach, but the invasiveness of this technique limits its clinical application. Recently, a noninvasive method to stimulate vagus nerve has been developed. The aim of the present study was to explore whether noninvasive VNS combined with robotic rehabilitation can enhance upper limb functionality in chronic stroke. Safety and efficacy of this combination have been assessed within a proof-of-principle, double-blind, semirandomized, sham-controlled trial. Fourteen patients with either ischemic or haemorrhagic chronic stroke were randomized to robot-assisted therapy associated with real or sham VNS, delivered for 10 working days. Efficacy was evaluated by change in upper extremity Fugl–Meyer score. After intervention, there were no adverse events and Fugl–Meyer scores were significantly better in the real group compared to the sham group. Our pilot study confirms that VNS is feasible in stroke patients and can produce a slight clinical improvement in association to robotic rehabilitation. Compared to traditional stimulation, noninvasive VNS seems to be safer and more tolerable. Further studies are needed to confirm the efficacy of this innovative approach.

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This paper is focused on the multimodal analysis of patient performance, carried out by means of robotic technology and wearable sensors, and aims at providing quantitative measure of biomechanical and motion planning features of arm motor control following rehabilitation. Upper-limb robotic therapy was administered to 24 community-dwelling persons with chronic stroke. Performance indices on patient motor performance were computed from data recorded with the InMotion2 robotic machine and a magneto-inertial sensor. Motor planning issues were investigated by means of techniques of motion decomposition into submovements. A linear regression analysis was carried out to study correlation with clinical scales. Robotic outcome measures showed a significant improvement of kinematic motor performance; improvement of dynamic components was more significant in resistive motion and highly correlated with MP. The analysis of motion decomposition into submovements showed an important change with recovery of submovement number, amplitude and order, tending to patterns measured in healthy subjects. Preliminary results showed that arm biomechanical functions can be objectively measured by means of the proposed set of performance indices. Correlation with MP is high, while correlation with FM is moderate. Features related to motion planning strategies can be extracted from submovement analysis.