Particle swarm optimization of periodic deep brain stimulation waveforms

Yingyuan Chen, Jiang Wang, Xile Wei, Bin Deng, Yanqiu Che

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

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 Parkinson's 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.

Original languageEnglish (US)
Title of host publicationProceedings of the 30th Chinese Control Conference, CCC 2011
Pages754-757
Number of pages4
StatePublished - Sep 27 2011
Event30th Chinese Control Conference, CCC 2011 - Yantai, China
Duration: Jul 22 2011Jul 24 2011

Publication series

NameProceedings of the 30th Chinese Control Conference, CCC 2011

Other

Other30th Chinese Control Conference, CCC 2011
CountryChina
CityYantai
Period7/22/117/24/11

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

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