深度脑刺激的精确闭环去同步控制

Accurate Close-Loop Desynchronization Control of Deep Brain Stimulation

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.