Rehabilitation of post stroke patients with upper extremity motor deficits is typically focused on relearning of motor abilities and functionalities requiring interaction with physiotherapists and/or rehabilitation robots. In a point-to-point movement training, the trajectories are usually arbitrarily determined without considering the motor impairment of the individual. In this paper, we used an optimal control model based on arm dynamics enabling also incorporation of muscle functioning constraints (i.e. simulation of muscle tightness) to find the optimal trajectories for planar arm reaching movements. First, we tested ability of the minimum joint torque cost function to replicate the trajectories obtained in previously published experimental trials done by neurologically intact subjects, and second, we predicted the optimal trajectories when muscle constraints were modeled. The resulting optimal trajectories show considerable similarity as compared to the experimental data, while on the other hand, the muscle constraints play a major role in determination of the optimal trajectories for stroke rehabilitation.
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In the motor system, transcranial magnetic stimulation (TMS) has proved an invaluable tool to study the organisation and interaction of the cortical motor areas. In this review I describe some of the ways in which TMS has been used to map out the major topographical features of the motor output and to test how these change in response motor learning or after peripheral (e.g. amputation) or central (e.g. stroke) injury. More recent work has shown that longer periods of repeated TMS involving several hundred to a thousand pulses can lead to lasting changes in motor cortex excitability that are thought to involve changes in the efficacy of intracortical synapses equivalent to LTP and LTP in slice preparations. These are accompanied by changes in the rate of motor learning and are presently being trialled as potential treatments to speed recovery from stroke.
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