深度脑刺激的精确闭环去同步控制  

Accurate Close-Loop Desynchronization Control of Deep Brain Stimulation

作　　者：王江[1] 伊国胜[1] 边洪瑞[2] 韩春晓[3] 李会艳[3] 魏熙乐[1] 邓斌[1] 

机构地区：[1]天津大学电气与自动化工程学院,天津300072 [2]中国船舶重工集团公司707研究所,天津300131 [3]天津职业技术师范大学自动化与电气工程学院,天津300222

出　　处：《天津大学学报（自然科学与工程技术版）》2013年第11期969-976,共8页Journal of Tianjin University：Science and Technology

基　　金：国家自然科学基金重点资助项目(50537030);国家自然科学基金资助项目(61072012;61172009;61374182);天津市自然科学基金重点资助项目(13JCZDJC27900)

摘　　要：深度脑刺激(DBS)是治疗帕金森症和癫痫等神经疾病的有效方法之一.针对其开环控制的缺点,以MorrisLecar神经元为节点模拟病态同步神经元网络,提出了基于H∞变论域模糊的DBS闭环控制方法,实现了神经元网络的精确去同步控制.采用变论域模糊逼近神经元非线性动态和H∞抑制逼近误差,利用李雅普诺夫稳定性理论证明控制算法的稳定性并进行了仿真分析.仿真结果验证了所提方案的有效性及鲁棒性,该方法可作为由病态同步引起的神经疾病的一种潜在电刺激治疗方案.Deep brain stimulation（DBS）is one of the effective treatments of neurological diseases,such as Parkinson and Epilepsy. However,most of the methods based on DBS are open-loop algorithm. To overcome the shortcomings of the open-loop control,a close-loop DBS control algorithm based on variable universe fuzzy H∞was proposed to accurately desynchronize an abnormal synchronization neural network composed of Morris-Lecar models. Variable universe fuzzy controllers were used to approximate nonlinear dynamic of neurons and H∞controllers were added to constrain the approximation error. Stability of the proposed algorithm was also proved by Lyapunov stability theory.Simulation results show the effectiveness and robustness of the proposed algorithm. This control algorithm may provide a potential electrical stimulation therapy on neurological diseases caused by abnormal synchronization.

关 键 词：深度脑刺激 去同步 闭环控制 变论域模糊 

分 类 号：TK421[动力工程及工程热物理—动力机械及工程]