Chin. Phys. B ›› 2014, Vol. 23 ›› Issue (1): 10202-010202.doi: 10.1088/1674-1056/23/1/010202

• GENERAL • 上一篇    下一篇

Control of epileptiform spikes based on nonlinear unscented Kalman filter

刘仙, 高庆, 李小俚   

  1. Key Lab of Industrial Computer Control Engineering of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
  • 收稿日期:2013-03-04 修回日期:2013-06-07 出版日期:2013-11-12 发布日期:2013-11-12
  • 基金资助:
    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).

Control of epileptiform spikes based on nonlinear unscented Kalman filter

Liu Xian (刘仙), Gao Qing (高庆), Li Xiao-Li (李小俚)   

  1. Key Lab of Industrial Computer Control Engineering of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
  • Received:2013-03-04 Revised:2013-06-07 Online:2013-11-12 Published:2013-11-12
  • Contact: Liu Xian E-mail:liuxian@ysu.edu.cn
  • Supported by:
    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).

摘要: 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.

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

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.

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

中图分类号:  (Control theory)

  • 02.30.Yy
87.19.le (EEG and MEG)