Abstract
A nonlinear model was established in this paper for the closed-loop system simulating the non-human primates' cortical control of a computer cursor's movement in a 3D virtual reality environment. The model was developed based on artificial neural networks. Elaborately designed experiments were performed on monkeys who have chronically implanted microelectrode arrays in motor cortex areas corresponding to the arm. Monkeys were trained to control the movement of a cursor using cortical signals sampled from the electrodes. Using advanced present system identification tools, the mappings between recorded monkeys' arm movement parameters and neuronal activities in cortex areas were extracted from experimental data sets. This improved substantially the accuracy in predicting arm trajectories from recorded cortical signals than reported in the literature and other methodologies. This new algorithm contributes to the promising application of assisting paralysed people to control neuroprosthetic devices using their thoughts through recorded cortical signals.
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