Pattern recognition (PR) based strategies for the control of myoelectric upper limb prostheses are generally evaluated through offline classification accuracy, which is an admittedly useful metric, but insufficient to discuss functional performance in real time. Existing functional tests are extensive to set up and most fail to provide a challenging, objective framework to assess the strategy performance in real time.

Intrafascicular stimulation evokes precise and functional hand movements in monkeys, suggesting clinical opportunities for people with hand paralysis.

Reliably interfacing a nerve with an electrode array is one of the approaches to restore motor and sensory functions after an injury to the peripheral nerve. Accomplishing this with current technologies is challenging as the electrode-neuron interface often degrades over time and surrounding myoelectric signals contaminate the neuro-signals in awake, moving animals. The purpose of this study was to evaluate the potential of microchannel electrode implants to monitor over time and in freely moving animals, neural activity from regenerating nerves. We designed and fabricated implants with silicone rubber and elastic thin-film metallization. Each implant carries an eight-by-twelve matrix of parallel microchannels (of 120 × 110 μm² cross-section and 4 mm length) and gold thin-film electrodes embedded in the floor of ten of the microchannels. After sterilization, the soft, multi-lumen electrode implant is sutured between the stumps of the sciatic nerve. Over a period of three months and in four rats, the microchannel electrodes recorded spike activity from the regenerating sciatic nerve. Histology indicates mini-nerves formed of axons and supporting cells regenerate robustly in the implants. Analysis of the recorded spikes and gait kinematics over the ten-week period suggests firing patterns collected with the microchannel electrode implant can be associated with different phases of gait.

After spinal cord injury (SCI), sensory feedback circuits critically contribute to leg motor execution. Compelled by the importance to engage these circuits during gait rehabilitation, assistive robotics and training protocols have primarily focused on guiding leg movements to reinforce sensory feedback. Despite the importance of trunk postural dynamics on gait and balance, trunk assistance has comparatively received little attention. Typically, trunk movements are either constrained within bodyweight support systems, or manually adjusted by therapists. Here, we show that real-time control of trunk posture re-established dynamic balance amongst bilateral proprioceptive feedback circuits, and thereby restored left-right symmetry, loading and stepping consistency in rats with severe SCI. We developed a robotic system that adjusts mediolateral trunk posture during locomotion. This system uncovered robust relationships between trunk orientation and the modulation of bilateral leg kinematics and muscle activity. Computer simulations suggested that these modulations emerged from corrections in the balance between flexor- and extensor-related proprioceptive feedback. We leveraged this knowledge to engineer control policies that regulate trunk orientation and postural sway in real-time. This dynamical postural interface immediately improved stepping quality in all rats regardless of broad differences in deficits. These results emphasize the importance of trunk regulation to optimize performance during rehabilitation.

Objective. Motor neuroprostheses require the identification of stimulation protocols that effectively produce desired movements. Manual search for these protocols can be very time-consuming and often leads to suboptimal solutions, as several stimulation parameters must be personalized for each subject for a variety of target motor functions. Here, we present an algorithm that efficiently tunes peripheral intraneural stimulation protocols to elicit functionally relevant distal limb movements. Approach. We developed the algorithm using Bayesian optimization (BO) with multi-output Gaussian Processes (GPs) and defined objective functions based on coordinated muscle recruitment. We applied the algorithm offline to data acquired in rats for walking control and in monkeys for hand grasping control and compared different GP models for these two systems. We then performed a preliminary online test in a monkey to experimentally validate the functionality of our method. Main results. Offline, optimal intraneural stimulation protocols for various target motor functions were rapidly identified in both experimental scenarios. Using the model that performed best, the algorithm converged to stimuli that evoked functionally consistent movements with an average number of actions equal to 20% of the search space size in both the rat and monkey animal models. Online, the algorithm quickly guided the observations to stimuli that elicited functional hand gestures, although more selective motor outputs could have been achieved by refining the objective function used. Significance. These results demonstrate that BO can reliably and efficiently automate the tuning of peripheral neurostimulation protocols, establishing a translational framework to configure peripheral motor neuroprostheses in clinical applications. The proposed method can also potentially be applied to optimize motor functions using other stimulation modalities.