An Optimized Channel Selection Method Based on Multifrequency CSP-Rank for Motor Imagery-Based BCI System Article Swipe
Jian Kui Feng
,
Jing Jin
,
Ian Daly
,
Jiale Zhou
,
Yugang Niu
,
Xingyu Wang
,
Andrzej Cichocki
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1155/2019/8068357
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1155/2019/8068357
Background . Due to the redundant information contained in multichannel electroencephalogram (EEG) signals, the classification accuracy of brain-computer interface (BCI) systems may deteriorate to a large extent. Channel selection methods can help to remove task-independent electroencephalogram (EEG) signals and hence improve the performance of BCI systems. However, in different frequency bands, brain areas associated with motor imagery are not exactly the same, which will result in the inability of traditional channel selection methods to extract effective EEG features. New Method . To address the above problem, this paper proposes a novel method based on common spatial pattern- (CSP-) rank channel selection for multifrequency band EEG (CSP-R-MF). It combines the multiband signal decomposition filtering and the CSP-rank channel selection methods to select significant channels, and then linear discriminant analysis (LDA) was used to calculate the classification accuracy. Results . The results showed that our proposed CSP-R-MF method could significantly improve the average classification accuracy compared with the CSP-rank channel selection method.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1155/2019/8068357
- OA Status
- hybrid
- Cited By
- 85
- References
- 27
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2945692081
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2945692081Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1155/2019/8068357Digital Object Identifier
- Title
-
An Optimized Channel Selection Method Based on Multifrequency CSP-Rank for Motor Imagery-Based BCI SystemWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-05-13Full publication date if available
- Authors
-
Jian Kui Feng, Jing Jin, Ian Daly, Jiale Zhou, Yugang Niu, Xingyu Wang, Andrzej CichockiList of authors in order
- Landing page
-
https://doi.org/10.1155/2019/8068357Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1155/2019/8068357Direct OA link when available
- Concepts
-
Brain–computer interface, Motor imagery, Computer science, Rank (graph theory), Channel (broadcasting), Selection (genetic algorithm), Artificial intelligence, Electroencephalography, Computer vision, Psychology, Neuroscience, Mathematics, Telecommunications, CombinatoricsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
85Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 8, 2024: 14, 2023: 17, 2022: 17, 2021: 8Per-year citation counts (last 5 years)
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27Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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