Removal of EMG Artifacts from Multichannel EEG Signals Using Combined Singular Spectrum Analysis and Canonical Correlation Analysis
Joint Authors
Zhang, Xu
Liu, Qingze
Chen, Xiang
Qian, Ruobing
Liu, Aiping
Chen, Xun
Source
Journal of Healthcare Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-12-31
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Electroencephalography (EEG) signals collected from human scalps are often polluted by diverse artifacts, for instance electromyogram (EMG), electrooculogram (EOG), and electrocardiogram (ECG) artifacts.
Muscle artifacts are particularly difficult to eliminate among all kinds of artifacts due to their complexity.
At present, several researchers have proved the superiority of combining single-channel decomposition algorithms with blind source separation (BSS) to make multichannel EEG recordings free from EMG contamination.
In our study, we come up with a novel and valid method to accomplish muscle artifact removal from EEG by using the combination of singular spectrum analysis (SSA) and canonical correlation analysis (CCA), which is named as SSA-CCA.
Unlike the traditional single-channel decomposition methods, for example, ensemble empirical mode decomposition (EEMD), SSA algorithm is a technique based on principles of multivariate statistics.
Our proposed approach can take advantage of SSA as well as cross-channel information.
The performance of SSA-CCA is evaluated on semisimulated and real data.
The results demonstrate that this method outperforms the state-of-the-art technique, EEMD-CCA, and the classic technique, CCA, under multichannel circumstances.
American Psychological Association (APA)
Liu, Qingze& Liu, Aiping& Zhang, Xu& Chen, Xiang& Qian, Ruobing& Chen, Xun. 2019. Removal of EMG Artifacts from Multichannel EEG Signals Using Combined Singular Spectrum Analysis and Canonical Correlation Analysis. Journal of Healthcare Engineering،Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1175183
Modern Language Association (MLA)
Liu, Qingze…[et al.]. Removal of EMG Artifacts from Multichannel EEG Signals Using Combined Singular Spectrum Analysis and Canonical Correlation Analysis. Journal of Healthcare Engineering No. 2019 (2019), pp.1-13.
https://search.emarefa.net/detail/BIM-1175183
American Medical Association (AMA)
Liu, Qingze& Liu, Aiping& Zhang, Xu& Chen, Xiang& Qian, Ruobing& Chen, Xun. Removal of EMG Artifacts from Multichannel EEG Signals Using Combined Singular Spectrum Analysis and Canonical Correlation Analysis. Journal of Healthcare Engineering. 2019. Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1175183
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1175183