Identification of motor imagery tasks through CC LR algorithm in brain computer interface

Siuly, and Li, Yan and Wen, Peng (2013) Identification of motor imagery tasks through CC LR algorithm in brain computer interface. International Journal of Bioinformatics Research and Applications, 9 (2). pp. 156-172. ISSN 1744-5485

Abstract

This study focuses on the identification of Motor Imagery (MI) tasks for the development of Brain Computer Interface (BCI) technologies combining Cross-Correlation and Logistic Regression (CC–LR) techniques.The proposed method is tested on two benchmark data sets, IVa and IVb of BCI Competition III, and the performance is evaluated through a 3-fold
cross-validation procedure. The experimental outcomes are compared with two recently reported algorithms, R-Common Spatial Pattern (CSP) with aggregation and Clustering Technique (CT)-based Least Square Support Vector Machine (LS-SVM) and also other four algorithms using data set IVa.
The results demonstrate that our proposed method results in an improvement of at least 3.47% compared with the existing methods tested.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Copyright © 2013 Inderscience Enterprises Ltd. Published version deposited in accordance with the copyright policy of the publisher.
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 09 Jul 2013 04:35
Last Modified: 13 Jun 2016 04:53
Uncontrolled Keywords: BCI; brain computer interface; EEG; electroencephalogram; MI; motor imagery; CC; cross-correlation; LR; logistic regression; feature extraction
Fields of Research : 08 Information and Computing Sciences > 0806 Information Systems > 080602 Computer-Human Interaction
17 Psychology and Cognitive Sciences > 1702 Cognitive Sciences > 170205 Neurocognitive Patterns and Neural Networks
09 Engineering > 0903 Biomedical Engineering > 090399 Biomedical Engineering not elsewhere classified
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970110 Expanding Knowledge in Technology
Identification Number or DOI: 10.1504/IJBRA.2013.052447
URI: http://eprints.usq.edu.au/id/eprint/23428

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