Control of epileptiform spikes based on nonlinear unscented Kalman filter

doi:10.1088/1674-1056/23/1/010202

Abstract A new control strategy based on nonlinear unscented Kalman filter (UKF) is proposed for a neural mass model that serves as a model for simulating real epileptiform stereo-electroencephalographic (SEEG) signals. The UKF is used as an observer to estimate the state from the noisy measurement because it has been proved to be effective for state estimation of nonlinear systems. A UKF controller is constructed via the estimated state and is illustrated to be effective for epileptiform spikes suppression of aforementioned model by numerical simulations.

Keywords: unscented Kalman filter (UKF) control epileptiform spike closed-loop control neural mass model

Received: 04 March 2013
Revised: 07 June 2013
Accepted manuscript online:

PACS:	02.30.Yy	(Control theory)
	87.19.le	(EEG and MEG)

Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 61004050 and 60125019) and the Natural Science Foundation of Scientific Research of Hebei Education Department, China (Grant No. 2009482).

Corresponding Authors: Liu Xian
E-mail: liuxian@ysu.edu.cn

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Liu Xian (刘仙), Gao Qing (高庆), Li Xiao-Li (李小俚) Control of epileptiform spikes based on nonlinear unscented Kalman filter 2014 Chin. Phys. B 23 010202

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Control of epileptiform spikes based on nonlinear unscented Kalman filter

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