Particle Swarm Optimization of Periodic Deep Brain Stimulation Waveforms

摘要：

This paper proposes a particle swarm optimization (PSO)to identify the optimal parameter set of periodic deep brain stimulation (DBS)waveforms.A computational model characterizing Parkinsons disease (PD)is introduced.In Parkinsonian state,the firing of globus pallidus in pars interna (GPi)is burstlike and synchronized.If DBS current is applied,the tonic rhythm output of GPi could restore the thalamic relay properties.Thus,we use a synchronized measure to optimize periodic DBS currents.By comparison with the grid sampling approach and the genetic algorithm,we demonstrate the effectiveness of the proposed algorithm.

作者: CHEN Yingyuan WANG Jiang WEI Xile DENG Bin CHE Yanqiu

作者单位: School of Electrical and Automation Eng.,Tianjin University,Tianjin 300072,P.R.China Tianjin Key Laboratory of Information Sensing &Intelligent Control,Tianjin University of Technology

会议类型: 国际会议

会议名称: The 30th Chinese Control Conference(第三十届中国控制会议)

会议地点: 烟台

会议语种:英文

页码: 1-4

在线出版日期: 2011-07-01（万方平台首次上网日期，不代表论文的发表时间）