A Closed-Loop Brain Stimulation Control System Design Based on Brain-Machine Interface for Epilepsy. (14th April 2020)

• Record Type: Journal Article
• Authors: Qian, Moshu; Zhong, Guanghua; Yan, Xinggang; Wang, Heyuan; Cui, Yang
• Other Names: Aguilar-Ibanez Carlos Academic Editor.
• Is Part Of: Complexity. Volume 2020(2020)
• Publication Date: 2020-04-14
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2020/3136715
• Languages: English
• ISSNs: 1076-2787

Abstract

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.