Literature DB >> 35401872

On disturbance rejection control of the epileptiform spikes.

Wei Wei1,2, Zhiyuan Zhang2, Nan Chen2, Min Zuo2, Tao Yu3.   

Abstract

Epilepsy is a neurological disorder resulting from a sudden development of synchronous firing in a massive group of neurons. For the particularity of the epilepsy, a neural mass model (NMM) is commonly utilized to understand and simulate the mechanism and evolution of the epilepsy. In this paper, based on a multi-coupling NMM and real EEGs of an epileptic mouse, a computational epileptic model is established to simulate the abnormal discharges of a mouse during seizures. Thus, rather than make animal experiments directly, numerical tests can be performed first. It reduces risks and helps improve the closed-loop neuromodulation. In addition, considering that no epileptic model can be utilized for neuromodulation in clinic, and even if a model exists, it still cannot describe the dynamics of the epilepsy faithfully, a scalable observer bandwidth and phase leading active disturbance rejection control (SOB-PLADRC) is proposed. Accordingly, a timelier and more accurate total disturbance estimation can be obtained by a scalable observer bandwidth and phase leading extended state observer, and an expected closed-loop neuromodulation can be realized without an accurate epileptic model. Numerical simulations based on the established model also show that the SOB-PLADRC suppresses seizures best among the PI and other active disturbance rejection approaches. More powerful disturbance rejection ability and more satisfactory closed-loop neuromodulation make the SOB-PLADRC more promising in the seizure control.
© The Author(s), under exclusive licence to Springer Nature B.V. 2021.

Entities:  

Keywords:  Active disturbance rejection control; Epilepsy; Leading phase; Neural mass model; Scalable observer bandwidth

Year:  2021        PMID: 35401872      PMCID: PMC8934905          DOI: 10.1007/s11571-021-09704-y

Source DB:  PubMed          Journal:  Cogn Neurodyn        ISSN: 1871-4080            Impact factor:   5.082


  18 in total

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Review 5.  Genetic and molecular basis of epilepsy-related cognitive dysfunction.

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Journal:  Epilepsy Behav       Date:  2020-02-03       Impact factor: 2.937

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7.  Electroencephalogram and visual evoked potential generation in a mathematical model of coupled cortical columns.

Authors:  B H Jansen; V G Rit
Journal:  Biol Cybern       Date:  1995-09       Impact factor: 2.086

Review 8.  Psychiatric complications after epilepsy surgery… but where are the psychiatrists?

Authors:  Rebecca Ellen Fasano; Andres M Kanner
Journal:  Epilepsy Behav       Date:  2019-01-15       Impact factor: 2.937

9.  UKF-based closed loop iterative learning control of epileptiform wave in a neural mass model.

Authors:  Bonan Shan; Jiang Wang; Bin Deng; Xile Wei; Haitao Yu; Huiyan Li
Journal:  Cogn Neurodyn       Date:  2014-08-20       Impact factor: 5.082

10.  Seizure Suppression Efficacy of Closed-Loop Versus Open-Loop Deep Brain Stimulation in a Rodent Model of Epilepsy.

Authors:  M Tariqus Salam; Jose Luis Perez Velazquez; Roman Genov
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2015-11-10       Impact factor: 3.802

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