Design of robust adaptive controller and feedback error learning for rehabilitation in Parkinson's disease: a simulation study |
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| Authors: | Korosh Rouhollahi Mehran Emadi Andani Seyed Mahdi Karbassi Iman Izadi |
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| Affiliation: | 1. Department of Applied Mathematics, Yazd University, Yazd Iran ; 2. Department of Biomedical Engineering, University of Isfahan, Isfahan Iran ; 3. Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan 84156‐83111 Iran |
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| Abstract: | Deep brain stimulation (DBS) is an efficient therapy to control movement disorders of Parkinson''s tremor. Stimulation of one area of basal ganglia (BG) by DBS with no feedback is the prevalent opinion. Reduction of additional stimulatory signal delivered to the brain is the advantage of using feedback. This results in reduction of side effects caused by the excessive stimulation intensity. In fact, the stimulatory intensity of controllers is decreased proportional to reduction of hand tremor. The objective of this study is to design a new controller structure to decrease three indicators: (i) the hand tremor; (ii) the level of delivered stimulation in disease condition; and (iii) the ratio of the level of delivered stimulation in health condition to disease condition. For this purpose, the authors offer a new closed‐loop control structure to stimulate two areas of BG simultaneously. One area (STN: subthalamic nucleus) is stimulated by an adaptive controller with feedback error learning. The other area (GPi: globus pallidus internal) is stimulated by a partial state feedback (PSF) controller. Considering the three indicators, the results show that, stimulating two areas simultaneously leads to better performance compared with stimulating one area only. It is shown that both PSF and adaptive controllers are robust regarding system parameter uncertainties. In addition, a method is proposed to update the parameters of the BG model in real time. As a result, the parameters of the controllers can be updated based on the new parameters of the BG model.Inspec keywords: adaptive control, medical control systems, diseases, medical disorders, patient rehabilitation, neurophysiology, surgeryOther keywords: robust adaptive controller design, feedback error learning, Parkinson''s disease rehabilitation, deep brain stimulation, DBS, movement disorders, Parkinson''s tremor, stimulatory signal Reduction, side effects, excessive stimulation intensity, hand tremor, controller structure, closed‐loop control structure, subthalamic nucleus, adaptive controller, partial state feedback controller, robust regarding system parameter uncertainties, BG model |
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