A transform-based feature extraction approach for motor imagery tasks classification

Baali, Hamza and Khorshidtalab, Aida and Mesbah, Mustafa and Salami, Momoh Jimoh Eyiomika (2015) A transform-based feature extraction approach for motor imagery tasks classification. IEEE Journal of Translational Engineering in Health and Medicine, 3. pp. 2100108-1. ISSN 2168-2372

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Abstract

In this paper, we present a new motor imagery classification method in the context of electroencephalography (EEG)-based brain-computer interface (BCI). This method uses a signal-dependent orthogonal transform, referred to as linear prediction singular value decomposition (LP-SVD), for feature extraction. The transform defines the mapping as the left singular vectors of the LP coefficient filter impulse response matrix. Using a logistic tree-based model classifier; the extracted features are classified into one of four motor imagery movements. The proposed approach was first benchmarked against two related state-of-the-art feature extraction approaches, namely, discrete cosine transform (DCT) and adaptive autoregressive (AAR)-based methods. By achieving an accuracy of 67.35%, the LP-SVD approach outperformed the other approaches by large margins (25% compared with DCT and 6 % compared with AAR-based methods). To further improve the discriminatory capability of the extracted features and reduce the computational complexity, we enlarged the extracted feature subset by incorporating two extra features, namely, Q- and the Hotelling's $T^{2}$ statistics of the transformed EEG and introduced a new EEG channel selection method. The performance of the EEG classification based on the expanded feature set and channel selection method was compared with that of a number of the state-of-the-art classification methods previously reported with the BCI IIIa competition data set. Our method came second with an average accuracy of 81.38%.

Item Type:	Article (Journal)
Additional Information:	2470/46812
Uncontrolled Keywords:	Brain-computer interface, channel selection, feature extraction, linear prediction, orthogonal transform
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User:	Prof Momoh-Jimoh Salami
Date Deposited:	29 Dec 2015 10:53
Last Modified:	25 Jun 2018 12:27
URI:	http://irep.iium.edu.my/id/eprint/46812

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