This chapter describes the implementation of a neural network-based predictive control system for driving a prosthetic hand. Nonlinearities associated with the electromechanical aspects of prosthetic devices present great challenges for precise control of this type of device. Model-based controllers may overcome this issue. Moreover, given the complexity of these kinds of electromechanical systems, neural network-based modeling arises as a good ft for modeling the fngers’ dynamics. The results of simulations mimicking potential situations encountered during activities of daily living demonstrate the feasibility of this technique.
CITATION STYLE
Pasluosta, C. F., & Chiu, A. W. L. (2015). Modulation of grasping force in prosthetic hands using neural network-based predictive control. Methods in Molecular Biology, 1260, 179–194. https://doi.org/10.1007/978-1-4939-2239-0_11
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