Title :
Optimization of indoor FES-cycling exercise assisted by a flywheel mechanism using genetic algorithm
Author :
Abdulla, S.C. ; Tokhi, M.O.
Author_Institution :
Dept. of Autom. Control & Syst. Eng., Univ. of Sheffield, Sheffield, UK
Abstract :
This paper presents an approach of parameter optimization of fuzzy logic control (FLC), assist mechanism and stimulation phases of functional electrical stimulation (FES)-cycling using genetic algorithm. The cycling exercise is introduced for rehabilitation of lower limbs by stimulating the quadriceps muscle of each leg by FES with the aid of a flywheel and electrical clutch assist mechanism. FLC is used to regulate the stimulation intensity on the muscles. Also, FLC is used to control the engagement of the flywheel, with the crank of the bicycle, to provide the required assistance. Genetic algorithm is used to optimize the FES-cycling with the objective function of minimizing the mean square error in cadence. In view of good results, it is concluded that the GA is effective in optimizing the performance of FES-cycling. Also, with the assistance of a flywheel and electrical clutch mechanism, it is possible to obtain cycling cadence close to the desired by stimulating single muscle only.
Keywords :
flywheels; fuzzy control; genetic algorithms; patient rehabilitation; FLC; crank; electrical clutch assist mechanism; flywheel mechanism; functional electrical stimulation; fuzzy logic control; genetic algorithm; indoor FES-cycling exercise; parameter optimization; Flywheels; Genetic algorithms; Muscles; Neuromuscular stimulation; Optimization; Sociology; Statistics;
Conference_Titel :
Intelligent Control (ISIC), 2014 IEEE International Symposium on
Conference_Location :
Juan Les Pins
DOI :
10.1109/ISIC.2014.6967635