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基于鲁棒自适应滑模控制器的帕金森震颤康复:一项仿真研究

Rehabilitation of the Parkinson's tremor by using robust adaptive sliding mode controller: a simulation study.

作者信息

Rouhollahi Korosh, Emadi Andani Mehran, Askari Marnanii Javad, Karbassi Seyed Mahdi

机构信息

Department of Applied Mathematics, Yazd University, Yazd, Iran.

Department of Biomedical Engineering, University of Isfahan, Isfahan, Iran.

出版信息

IET Syst Biol. 2019 Apr;13(2):92-99. doi: 10.1049/iet-syb.2018.5043.

Abstract

One of the efficient methods in controlling the Parkinson's tremor is Deep Brain Stimulation (DBS) therapy. The stimulation of Basal Ganglia (BG) by DBS brings no feedback though the existence of feedback reduces the additional stimulatory signal delivered to the brain. So this study offers a new adaptive architecture of a closed-loop control system in which two areas of BG are stimulated simultaneously to decrease the following three indicators: hand tremor, the level of a delivered stimulation signal in the disease condition, and the level of a delivered stimulation signal in health condition to the disease condition. One area (STN: subthalamic nucleus) is stimulated with an adaptive sliding mode controller and the other area (GPi: Globus Pallidus internal) with partial state feedback controller. The simulation results of stimulating two areas of BG showed satisfactory performance.

摘要

控制帕金森震颤的有效方法之一是深部脑刺激(DBS)疗法。尽管存在反馈会减少传递到大脑的额外刺激信号,但DBS对基底神经节(BG)的刺激没有反馈。因此,本研究提供了一种新型自适应闭环控制系统架构,其中同时刺激BG的两个区域,以降低以下三个指标:手部震颤、疾病状态下传递的刺激信号水平以及从健康状态到疾病状态下传递的刺激信号水平。一个区域(STN:丘脑底核)用自适应滑模控制器进行刺激,另一个区域(GPi:苍白球内侧部)用部分状态反馈控制器进行刺激。对BG两个区域进行刺激的仿真结果显示出令人满意的性能。

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