Analysis and simulation of the neural oscillator for tremor suppression by FES

Abstract

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.