Identification of motor imagery tasks through CC–LR algorithm in brain computer interface
Article
Article Title | Identification of motor imagery tasks through CC–LR algorithm in brain computer interface |
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ERA Journal ID | 36861 |
Article Category | Article |
Authors | Li, Yan (Author) and Wen, Peng (Author) |
Journal Title | International Journal of Bioinformatics Research and Applications |
Journal Citation | 9 (2), pp. 156-172 |
Number of Pages | 17 |
Year | 2013 |
Place of Publication | United Kingdom |
ISSN | 1744-5485 |
1744-5493 | |
Digital Object Identifier (DOI) | https://doi.org/10.1504/IJBRA.2013.052447 |
Web Address (URL) | https://www.inderscienceonline.com/doi/abs/10.1504/IJBRA.2013.052447 |
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 |
Keywords | BCI; brain computer interface; EEG; electroencephalogram; MI; motor imagery; CC; cross-correlation; LR; logistic regression; feature extraction |
ANZSRC Field of Research 2020 | 460806. Human-computer interaction |
520203. Cognitive neuroscience | |
400399. Biomedical engineering not elsewhere classified | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Centre for Systems Biology |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q1y9z/identification-of-motor-imagery-tasks-through-cc-lr-algorithm-in-brain-computer-interface
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