Multi-frequency band common spatial pattern with sparse optimization in Brain-Computer Interface
In motor imagery-based Brain Computer Interfaces (BCIs), Common Spatial Pattern (CSP) algorithm is widely used for extracting discriminative patterns from the EEG signals. However, the CSP algorithm is known to be sensitive to noise and artifacts, and its performance greatly depends on the operation...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
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2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/98790 http://hdl.handle.net/10220/13388 |
| _version_ | 1826116513326694400 |
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| author | Arvaneh, Mahnaz Guan, Cuntai Ang, Kai Keng Quek, Chai |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Arvaneh, Mahnaz Guan, Cuntai Ang, Kai Keng Quek, Chai |
| author_sort | Arvaneh, Mahnaz |
| collection | NTU |
| description | In motor imagery-based Brain Computer Interfaces (BCIs), Common Spatial Pattern (CSP) algorithm is widely used for extracting discriminative patterns from the EEG signals. However, the CSP algorithm is known to be sensitive to noise and artifacts, and its performance greatly depends on the operational frequency band. To address these issues, this paper proposes a novel Sparse Multi-Frequency Band CSP (SMFBCSP) algorithm optimized using a mutual information-based approach. Compared to the use of the cross-validation-based method which finds the regularization parameters by trial and error, the proposed mutual information-based approach directly computes the optimal regularization parameters such that the computational time is substantially reduced. The experimental results on 11 stroke patients showed that the proposed SMFBCSP significantly outperformed three existing algorithms based on CSP, sparse CSP and filter bank CSP in terms of classification accuracy. |
| first_indexed | 2024-10-01T04:12:38Z |
| format | Conference Paper |
| id | ntu-10356/98790 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:12:38Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/987902020-05-28T07:18:15Z Multi-frequency band common spatial pattern with sparse optimization in Brain-Computer Interface Arvaneh, Mahnaz Guan, Cuntai Ang, Kai Keng Quek, Chai School of Computer Engineering IEEE International Conference on Acoustics, Speech and Signal Processing (2012 : Kyoto, Japan) DRNTU::Engineering::Computer science and engineering In motor imagery-based Brain Computer Interfaces (BCIs), Common Spatial Pattern (CSP) algorithm is widely used for extracting discriminative patterns from the EEG signals. However, the CSP algorithm is known to be sensitive to noise and artifacts, and its performance greatly depends on the operational frequency band. To address these issues, this paper proposes a novel Sparse Multi-Frequency Band CSP (SMFBCSP) algorithm optimized using a mutual information-based approach. Compared to the use of the cross-validation-based method which finds the regularization parameters by trial and error, the proposed mutual information-based approach directly computes the optimal regularization parameters such that the computational time is substantially reduced. The experimental results on 11 stroke patients showed that the proposed SMFBCSP significantly outperformed three existing algorithms based on CSP, sparse CSP and filter bank CSP in terms of classification accuracy. 2013-09-09T06:32:03Z 2019-12-06T19:59:41Z 2013-09-09T06:32:03Z 2019-12-06T19:59:41Z 2012 2012 Conference Paper https://hdl.handle.net/10356/98790 http://hdl.handle.net/10220/13388 10.1109/ICASSP.2012.6288434 en © 2012 IEEE. |
| spellingShingle | DRNTU::Engineering::Computer science and engineering Arvaneh, Mahnaz Guan, Cuntai Ang, Kai Keng Quek, Chai Multi-frequency band common spatial pattern with sparse optimization in Brain-Computer Interface |
| title | Multi-frequency band common spatial pattern with sparse optimization in Brain-Computer Interface |
| title_full | Multi-frequency band common spatial pattern with sparse optimization in Brain-Computer Interface |
| title_fullStr | Multi-frequency band common spatial pattern with sparse optimization in Brain-Computer Interface |
| title_full_unstemmed | Multi-frequency band common spatial pattern with sparse optimization in Brain-Computer Interface |
| title_short | Multi-frequency band common spatial pattern with sparse optimization in Brain-Computer Interface |
| title_sort | multi frequency band common spatial pattern with sparse optimization in brain computer interface |
| topic | DRNTU::Engineering::Computer science and engineering |
| url | https://hdl.handle.net/10356/98790 http://hdl.handle.net/10220/13388 |
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