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A Closed-Loop Brain Stimulation Control System Design Based on Brain-Machine Interface for Epilepsy

Qian, Moshu, Zhang, Guanghua, Yan, Xinggang, Wang, Heyuan, Cui, Yang (2020) A Closed-Loop Brain Stimulation Control System Design Based on Brain-Machine Interface for Epilepsy. Complexity, 2020 . ISSN 1076-2787. E-ISSN 1099-0526. (doi:10.1155/2020/3136715) (KAR id:81684)

Abstract

In this study, a closed-loop brain stimulation control system scheme for epilepsy seizure abatement is designed by brain-machine interface (BMI) technique. In the controller design process, the practical parametric uncertainties involving cerebral blood flow, glucose metabolism, blood oxygen level dependence, and electromagnetic disturbances in signal control are considered. An appropriate transformation is introduced to express the system in regular form for design and analysis. Then, sufficient conditions are developed such that the sliding motion is asymptotically stable. Combining Caputo fractional order definition and neural network (NN), a finite time fractional order sliding mode (FFOSM) controller is designed to guarantee reachability of the sliding mode. The stability and reachability analysis of the closed-loop tracking control system gives the guideline of parameter selection, and simulation results based on comprehensive comparisons are carried out to demonstrate the effectiveness of proposed approach.

Item Type: Article
DOI/Identification number: 10.1155/2020/3136715
Additional information: Article ID: 3136715
Uncontrolled keywords: Brain-machine interface, epilepsy, fractional order sliding mode, neural networks
Subjects: T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Xinggang Yan
Date Deposited: 12 Jun 2020 13:24 UTC
Last Modified: 05 Nov 2024 12:47 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/81684 (The current URI for this page, for reference purposes)

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