Parkinsonian oscillations and their suppression by closed-loop deep brain stimulation based on fuzzy concept  

作　　者：Xi-Le Wei Yu-Lin Bai Jiang Wang Si-Yuan Chang Chen Liu 魏熙乐;白玉林;王江;常思远;刘晨(School of Electrical and Information Engineering,Tianjin University,Tianjin 300072,China)

机构地区：[1]School of Electrical and Information Engineering,Tianjin University,Tianjin 300072,China

出　　处：《Chinese Physics B》2022年第12期684-691,共8页中国物理B（英文版）

基　　金：Project supported by the National Natural Science Foundation of China(Grant Nos.62173241 and 62171312);the Natural Science Foundation of Tianjin,China(Grant Nos.20JCQNJC01160 and 19JCZDJC36500);the financial support provided by Opening Foundation of Key Laboratory of Opto-technology and Intelligent Control(Lanzhou Jiaotong University),Ministry of Education,China(Grant No.KFKT2020-01)

摘　　要：This paper provides an adaptive closed-loop strategy for suppressing the pathological oscillations of the basal ganglia based on a variable universe fuzzy algorithm.The pathological basal ganglia oscillations in the theta(4-9 Hz)and beta(12-35 Hz)frequency bands have been demonstrated to be associated with the tremor and rigidity/bradykinesia symptoms in Parkinson’s disease(PD).Although the clinical application of open-loop deep brain stimulation(DBS)is effective,the stimulation waveform with the fixed parameters cannot be self-adjusted as the disease progresses,and thus the stimulation effects go poor.To deal with this difficult problem,a variable universe fuzzy closed-loop strategy is proposed to modulate different PD states.We establish a cortico-basal ganglia-thalamocortical network model to simulate pathological oscillations and test the control effect.The results suggest that the proposed closed-loop control strategy can accommodate the variation of brain states and symptoms,which may become an alternative method to administrate the symptoms in PD.

关 键 词：deep brain stimulation Parkinson’s disease basal ganglia closed-loop control variable universe fuzzy 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置] R742.5[自动化与计算机技术—控制科学与工程]