TY - GEN
T1 - Analysis and simulation of the neural oscillator for tremor suppression by FES
AU - Wang, Shengxin
AU - Gao, Yongsheng
AU - Xiao, Feiyun
AU - Xin, Wei
AU - Zhao, Jie
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015
Y1 - 2015
N2 - Tremor with a roughly sinusoidal profile impacts the individuals' living activities. Recently, Functional Electric Stimulation (FES) was intensively applied to activate the antagonist muscles with the anti-phase stimulation patterns for compensating the tremor. Considering the similarity between the rhythmic movements and the central neural oscillator, the Matsuoka model is introduced to reciprocally modulate the stimulations intensity of the antagonistic muscles. However, the nonlinear threshold function of the Matsuoka model complicates the system and limits the analysis. In this study, the linearly approximated method is employed to develop the explicit relationship between the model parameters and the frequency/amplitude of the sustained oscillation. The simulation results demonstrate that the output of roughly approximated oscillator is in accordance with that of the original oscillator. Besides, this study brings insight on the effect of the sensory feedback on the neural oscillator. Further, the treatment of tremor with the Matsuoka model as the feed-forward controller and the kinematic signals as the feedback is feasible.
AB - Tremor with a roughly sinusoidal profile impacts the individuals' living activities. Recently, Functional Electric Stimulation (FES) was intensively applied to activate the antagonist muscles with the anti-phase stimulation patterns for compensating the tremor. Considering the similarity between the rhythmic movements and the central neural oscillator, the Matsuoka model is introduced to reciprocally modulate the stimulations intensity of the antagonistic muscles. However, the nonlinear threshold function of the Matsuoka model complicates the system and limits the analysis. In this study, the linearly approximated method is employed to develop the explicit relationship between the model parameters and the frequency/amplitude of the sustained oscillation. The simulation results demonstrate that the output of roughly approximated oscillator is in accordance with that of the original oscillator. Besides, this study brings insight on the effect of the sensory feedback on the neural oscillator. Further, the treatment of tremor with the Matsuoka model as the feed-forward controller and the kinematic signals as the feedback is feasible.
UR - https://www.scopus.com/pages/publications/84964514373
U2 - 10.1109/ROBIO.2015.7418847
DO - 10.1109/ROBIO.2015.7418847
M3 - 会议稿件
AN - SCOPUS:84964514373
T3 - 2015 IEEE International Conference on Robotics and Biomimetics, IEEE-ROBIO 2015
SP - 680
EP - 685
BT - 2015 IEEE International Conference on Robotics and Biomimetics, IEEE-ROBIO 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2015 IEEE International Conference on Robotics and Biomimetics, ROBIO 2015
Y2 - 6 December 2015 through 9 December 2015
ER -