Enhanced Motor Imagery-Based Eeg Classification Using A Discriminative Graph Fourier Subspace
(2022) 19th IEEE International Symposium on Biomedical Imaging, ISBI 2022 In Proceedings - International Symposium on Biomedical Imaging 2022-March.- Abstract
Dealing with irregular domains, graph signal processing (GSP) has attracted much attention especially in brain imaging analysis. Motor imagery tasks are extensively utilized in brain-computer interface (BCI) systems that perform classification using features extracted from Electroencephalogram signals. In this paper, a GSP-based approach is presented for two-class motor imagery tasks classification. The proposed method exploits simultaneous diagonalization of two matrices that quantify the covariance structure of graph spectral representation of data from each class, providing a discriminative subspace where distinctive features are extracted from the data. The performance of the proposed method was evaluated on Dataset IVa from BCI... (More)
Dealing with irregular domains, graph signal processing (GSP) has attracted much attention especially in brain imaging analysis. Motor imagery tasks are extensively utilized in brain-computer interface (BCI) systems that perform classification using features extracted from Electroencephalogram signals. In this paper, a GSP-based approach is presented for two-class motor imagery tasks classification. The proposed method exploits simultaneous diagonalization of two matrices that quantify the covariance structure of graph spectral representation of data from each class, providing a discriminative subspace where distinctive features are extracted from the data. The performance of the proposed method was evaluated on Dataset IVa from BCI Competition III. Experimental results show that the proposed method outperforms two state-of-the-art alternative methods.
(Less)
- author
- Miri, Maliheh ; Abootalebi, Vahid and Behjat, Hamid LU
- organization
- publishing date
- 2022
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- classification, EEG, graph signal processing, simultaneous diagonalization
- host publication
- ISBI 2022 - Proceedings : 2022 IEEE International Symposium on Biomedical Imaging - 2022 IEEE International Symposium on Biomedical Imaging
- series title
- Proceedings - International Symposium on Biomedical Imaging
- volume
- 2022-March
- article number
- 21760580
- publisher
- IEEE Computer Society
- conference name
- 19th IEEE International Symposium on Biomedical Imaging, ISBI 2022
- conference location
- Kolkata, India
- conference dates
- 2022-03-28 - 2022-03-31
- external identifiers
-
- scopus:85129590716
- ISSN
- 1945-7928
- 1945-8452
- ISBN
- 978-1-6654-2924-5
- 978-1-6654-2923-8
- DOI
- 10.1109/ISBI52829.2022.9761611
- language
- English
- LU publication?
- yes
- id
- 6f2f7993-f7ab-4e3f-a041-d286bad681a4
- date added to LUP
- 2022-07-08 10:20:38
- date last changed
- 2024-04-18 11:30:44
@inproceedings{6f2f7993-f7ab-4e3f-a041-d286bad681a4, abstract = {{<p>Dealing with irregular domains, graph signal processing (GSP) has attracted much attention especially in brain imaging analysis. Motor imagery tasks are extensively utilized in brain-computer interface (BCI) systems that perform classification using features extracted from Electroencephalogram signals. In this paper, a GSP-based approach is presented for two-class motor imagery tasks classification. The proposed method exploits simultaneous diagonalization of two matrices that quantify the covariance structure of graph spectral representation of data from each class, providing a discriminative subspace where distinctive features are extracted from the data. The performance of the proposed method was evaluated on Dataset IVa from BCI Competition III. Experimental results show that the proposed method outperforms two state-of-the-art alternative methods.</p>}}, author = {{Miri, Maliheh and Abootalebi, Vahid and Behjat, Hamid}}, booktitle = {{ISBI 2022 - Proceedings : 2022 IEEE International Symposium on Biomedical Imaging}}, isbn = {{978-1-6654-2924-5}}, issn = {{1945-7928}}, keywords = {{classification; EEG; graph signal processing; simultaneous diagonalization}}, language = {{eng}}, publisher = {{IEEE Computer Society}}, series = {{Proceedings - International Symposium on Biomedical Imaging}}, title = {{Enhanced Motor Imagery-Based Eeg Classification Using A Discriminative Graph Fourier Subspace}}, url = {{http://dx.doi.org/10.1109/ISBI52829.2022.9761611}}, doi = {{10.1109/ISBI52829.2022.9761611}}, volume = {{2022-March}}, year = {{2022}}, }