A fuzzy logic gait event detector for fes paraplegic gait
暂无分享,去创建一个
Abstracf A system for automatic detection of the phases of gait of paraplegic subjects during Functional Electrical Stimulation (FES)-induced walking was developed. This fuzzy logic based detector is intended for on-line estimation of the patient's phase of gait, as part of a closed loop controller for improved paraplegic locomotion. The system was identified from sensor data using modified versions of fuzzy system identification algorithms. The best algorithm and fuzzy model configuration yielded a gait event detector that correctly predicted the patient's phase of gait 97% of the time using simulated noise free data and 94% of the time using experimental data. The modification of these algorithms reduced storage requirements by over 50% without a decrease in detection accuracy with noise free simulated data and with a decrease of 9% when noise ( m u . =lo% of input range) was added to all input data signals.
[1] J. Perry,et al. The mechanics of walking. A clinical interpretation. , 1967, Physical therapy.
[2] W. Pedrycz. An identification algorithm in fuzzy relational systems , 1984 .
[3] Yong-Zai Lu,et al. Fuzzy Model Identification and Self-Learning for Dynamic Systems , 1987, IEEE Transactions on Systems, Man, and Cybernetics.
[4] Witold Pedrycz. Identification in fuzzy systems , 1984, IEEE Transactions on Systems, Man, and Cybernetics.