Neuromuscular electrical stimulation (NMES) is a technique that is widely used as a tool for rehabilitation and restoration of basic functions for people suffering from upper motor neuron lesion (UMNL). Closed-loop methods have shown a potential for improving the effectiveness of NMES. In this paper, uncertainties in the muscle contraction dynamics are taken into consideration when compensating for the muscle contraction dynamics. Accounting for the muscle contraction dynamics is a challenge because of uncertainty, nonlinearity and the fact that the contraction states are not measurable. A neural-network (NN)-based controller together with a dynamic NN-based identifier is designed to enable semi-global uniformly ultimately bounded tracking of a desired limb trajectory and on-line estimation of the limb acceleration. The overall stability of the identifier-controller system is analyzed through Lyapunov methods. Simulation results are provided to illustrate the controller performance.
- Dynamic Systems and Control Division
Neuromuscular Electrical Stimulation With an Uncertain Muscle Contraction Model
Wang, Q, Dinh, H, Bellman, M, & Dixon, WE. "Neuromuscular Electrical Stimulation With an Uncertain Muscle Contraction Model." Proceedings of the ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference. Volume 2: Legged Locomotion; Mechatronic Systems; Mechatronics; Mechatronics for Aquatic Environments; MEMS Control; Model Predictive Control; Modeling and Model-Based Control of Advanced IC Engines; Modeling and Simulation; Multi-Agent and Cooperative Systems; Musculoskeletal Dynamic Systems; Nano Systems; Nonlinear Systems; Nonlinear Systems and Control; Optimal Control; Pattern Recognition and Intelligent Systems; Power and Renewable Energy Systems; Powertrain Systems. Fort Lauderdale, Florida, USA. October 17–19, 2012. pp. 519-528. ASME. https://doi.org/10.1115/DSCC2012-MOVIC2012-8847
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