TY - GEN
T1 - Particle swarm optimization of periodic deep brain stimulation waveforms
AU - Chen, Yingyuan
AU - Wang, Jiang
AU - Wei, Xile
AU - Deng, Bin
AU - Che, Yanqiu
PY - 2011/9/27
Y1 - 2011/9/27
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/80053065465
UR - https://www.scopus.com/inward/citedby.url?scp=80053065465&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:80053065465
SN - 9789881725592
T3 - Proceedings of the 30th Chinese Control Conference, CCC 2011
SP - 754
EP - 757
BT - Proceedings of the 30th Chinese Control Conference, CCC 2011
T2 - 30th Chinese Control Conference, CCC 2011
Y2 - 22 July 2011 through 24 July 2011
ER -