Abstract
A novel closed loop control framework is proposed to inhibit epileptiform wave in a neural mass model by external electric field, where the unscented Kalman filter method is used to reconstruct dynamics and estimate unmeasurable parameters of the model. Specifically speaking, the iterative learning control algorithm is introduced into the framework to optimize the control signal. In the proposed method, the control effect can be significantly improved based on the observation of the past attempts. Accordingly, the proposed method can effectively suppress the epileptiform wave as well as showing robustness to noises and uncertainties. Lastly, the simulation is carried out to illustrate the feasibility of the proposed method. Besides, this work shows potential value to design model-based feedback controllers for epilepsy treatment.
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This work is supported by National Natural Science Foundation of China (Grant Nos. 61374182 and 61172009).
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Shan, B., Wang, J., Deng, B. et al. UKF-based closed loop iterative learning control of epileptiform wave in a neural mass model. Cogn Neurodyn 9, 31–40 (2015). https://doi.org/10.1007/s11571-014-9306-0
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DOI: https://doi.org/10.1007/s11571-014-9306-0