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Classification of Multichannel EEG Signal by Linear Discriminant Analysis

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Progress in Systems Engineering

Abstract

Motor imagery (MI) related Electroencephalogram (EEG) signal classification is one of the main challenge in designing a brain computer interface (BCI) system. Linear Discriminant Analysis (LDA) has a very low computational requirement which makes it suitable for online BCI system. This paper proposes an advanced and simple classification technique for MI related BCI system. Initially the signal is extracted for different features. The LDA classifier has been used to propose technique to design an MI based BCI. For contrastive comparison other classification techniques have been evaluated by classification accuracy and Cohen’s kappa.

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Acknowledgment

This research has been supported by the Ministry of Higher Education of Malaysia through the Exploratory Research Grant Scheme ERGS12-026-0026.

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Correspondence to Mohammad Rubaiyat Hasan .

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Hasan, M.R., Ibrahimy, M.I., Motakabber, S.M.A., Shahid, S. (2015). Classification of Multichannel EEG Signal by Linear Discriminant Analysis. In: Selvaraj, H., Zydek, D., Chmaj, G. (eds) Progress in Systems Engineering. Advances in Intelligent Systems and Computing, vol 366. Springer, Cham. https://doi.org/10.1007/978-3-319-08422-0_42

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  • DOI: https://doi.org/10.1007/978-3-319-08422-0_42

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08421-3

  • Online ISBN: 978-3-319-08422-0

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