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Change point detection of EEG signals based on particle swarm optimization

Mohamed Saaid, M. F. and Wan Abas, W. A. B. and Aroff, H. and Mokhtar, N. and Ibrahim, Zuwairie (2011) Change point detection of EEG signals based on particle swarm optimization. In: 5th Kuala Lumpur International Conference on Biomedical Engineering 2011: (BIOMED 2011) 20-23 June 2011, Kuala Lumpur, Malaysia. IFMBE Proceedings . Springer Berlin Heidelberg, Germany, pp. 484-487. ISBN 978-364221728-9

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Official URL: http://dx.doi.org/10.1007/978-3-642-21729-6_122

Abstract

This paper proposes a change point detection for electroencephalograms (EEG) signal application based on Particle Swarm Optimization (PSO). As EEG signal is well known consider as non-stationary in nature, we model the signal by using the sinusoidal-Heaviside function, which are capable to represent the change of the behavior of the signal. The parameter of the model with the change point location can be tuned by finding the minimum value of sum squared error. It was showed that the minimum value of sum squared error in the parameter tuning give the exact location of change point. The proposed method is applied to the human EEG during an eye moving task.

Item Type:Book Section
Uncontrolled Keywords:change point detection, EEG, non-stationary, particle swarm optimization, sinusoidal
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:28927
Deposited By: Liza Porijo
Deposited On:04 Dec 2012 04:53
Last Modified:04 Dec 2012 04:53

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