Title :
Recurrent neural network control of functional electrical stimulation systems
Author :
Yilei, Wu ; Qing, Song ; Xulei, Yang ; Li, Lan
Author_Institution :
Nanyang Technol. Univ., Singapore
Abstract :
In this paper, a recurrent neural network (RNN) controller is proposed for the application of functional electrical stimulation (FES) system, which is a fast developing technique in the area of rehabilitation engineering. With the proposed scheme, the FES system can obtain a better response speed and an improved robustness against disturbance compared to a PID controlled one. Furthermore, L2-stability of RNN training algorithm is guaranteed via input-output analysis from the nonlinear system theory. Finally based upon a musculoskeletal model, computer simulations are carried out to verify the effectiveness of the theoretical results.
Keywords :
biocontrol; neurocontrollers; neuromuscular stimulation; patient rehabilitation; recurrent neural nets; functional electrical stimulation systems; input-output analysis; musculoskeletal model; nonlinear system theory; recurrent neural network controller; recurrent neural network training algorithm; rehabilitation engineering;
Conference_Titel :
Biomedical and Pharmaceutical Engineering, 2006. ICBPE 2006. International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-981-05-79
Electronic_ISBN :
81-904262-1-4