Adaptive repetitive control of wrist tremor suppression based on functional electrical stimulation.
10.7507/1001-5515.202202008
- Author:
Zan ZHANG
1
;
Yanhong LIU
1
;
Bing CHU
2
;
Benyan HUO
1
;
David Howard OWENS
1
Author Information
1. School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, P. R. China.
2. Department of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, UK.
- Publication Type:Journal Article
- Keywords:
Adaptive repetitive control;
Functional electrical stimulation;
Parallel multiple internal models;
Series high-order internal model;
Tremor suppression
- MeSH:
Humans;
Wrist;
Tremor/therapy*;
Movement;
Computer Simulation;
Electric Stimulation
- From:
Journal of Biomedical Engineering
2023;40(4):663-675
- CountryChina
- Language:Chinese
-
Abstract:
Tremor is an involuntary and repetitive swinging movement of limb, which can be regarded as a periodic disturbance in tremor suppression system based on functional electrical stimulation (FES). Therefore, using repetitive controller to adjust the level and timing of FES applied to the corresponding muscles, so as to generate the muscle torque opposite to the tremor motion, is a feasible means of tremor suppression. At present, most repetitive control systems based on FES assume that tremor is a fixed single frequency signal, but in fact, tremor may be a multi-frequency signal and the tremor frequency also varies with time. In this paper, the tremor data of intention tremor patients are analyzed from the perspective of frequency, and an adaptive repetitive controller with internal model switching is proposed to suppress tremor signals with different frequencies. Simulation and experimental results show that the proposed adaptive repetitive controller based on parallel multiple internal models and series high-order internal model switching can suppress tremor by up to 84.98% on average, which is a significant improvement compared to the traditional single internal model repetitive controller and filter based feedback controller. Therefore, the adaptive repetitive control method based on FES proposed in this paper can effectively address the issue of wrist intention tremor in patients, and can offer valuable technical support for the rehabilitation of patients with subsequent motor dysfunction.
