title: A microcomputer FES system for wrist moving control.
abstract: A portable close-loop control FES system, whose controller is a microcomputer, was proposed in this chapter. Considering the time-varying nonlinear of the muscle system, a self-adaptive PI control strategy was used. It included a neural network identifier (NNI) and a PI controller. NNI could get the variability of muscle working condition to identify muscle model online. Parameters of PI would be optimized by the results of NNI. Some tracking experiments had been done on able-bodied volunteers and the precision were under 4%.
authors: College of Civil Aviation, Nanjing University of Aeronautics & Astronautics, Nanjing, 210016, China. caoli@nuaa.edu.cn
authors: Li
authors: L
authors: Cao
authors: Jin-Sheng
authors: JS
authors: Yang
authors: Zhi-Long
authors: ZL
authors: Geng
authors: Gang
authors: G
authors: Cao
mesh_terms: D019295:Computational Biology; D003198:Computer Simulation; D004599:Electric Stimulation Therapy / Q000295:instrumentation / Q000706:statistics & numerical data*; D004867:Equipment Design; D006801:Humans; D008838:Microcomputers; D009068:Movement / Q000502:physiology; D009142:Musculoskeletal Physiological Phenomena; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D010264:Paraplegia / Q000503:physiopathology / Q000628:therapy; D014955:Wrist Joint / Q000503:physiopathology*