Abstract
Neuroprostheses (NPs) are systems for the substitution or augmentation of missing control or sensory signals in humans with disability. The NP sends signals to the neural systems affecting both afferent and efferent neural pathways. This artificially generated neural activity directly activates motor systems, triggers spinal reflexes, and changes the overall transmission to the cortical structures, thereby modifying cortical excitability. We suggest that the artificial command and control for motor NPs must mimic the hierarchical hybrid organization of motor control that is characteristic for humans. The hierarchical organization means the following: (1) at the top level the user sends command signals to the NP by means of discrete signals, (2) the middle level control uses a finite state model of the system for spatial and time coordination between the actuators, (3) the bottom control considers the musculo-skeletal properties of the actuation systems and implements a continuous model, and (4) the feedback to the user and the NP must combine continuous and discrete signals depending on where the signals are sent to. The methods discussed in this chapter apply to NPs that assist goal-oriented movements (e.g., reaching, grasping, standing up, and sitting down) and/or cyclic movements (e.g., walking).
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