Gaussian Elimination-Based Novel Canonical Correlation Analysis Method for EEG Motion Artifact Removal
Joint Authors
Shukla, Piyush Kumar
Roy, Vandana
Shukla, Shailja
Rawat, Paresh
Source
Journal of Healthcare Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-08
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
The motion generated at the capturing time of electro-encephalography (EEG) signal leads to the artifacts, which may reduce the quality of obtained information.
Existing artifact removal methods use canonical correlation analysis (CCA) for removing artifacts along with ensemble empirical mode decomposition (EEMD) and wavelet transform (WT).
A new approach is proposed to further analyse and improve the filtering performance and reduce the filter computation time under highly noisy environment.
This new approach of CCA is based on Gaussian elimination method which is used for calculating the correlation coefficients using backslash operation and is designed for EEG signal motion artifact removal.
Gaussian elimination is used for solving linear equation to calculate Eigen values which reduces the computation cost of the CCA method.
This novel proposed method is tested against currently available artifact removal techniques using EEMD-CCA and wavelet transform.
The performance is tested on synthetic and real EEG signal data.
The proposed artifact removal technique is evaluated using efficiency matrices such as del signal to noise ratio (DSNR), lambda (λ), root mean square error (RMSE), elapsed time, and ROC parameters.
The results indicate suitablity of the proposed algorithm for use as a supplement to algorithms currently in use.
American Psychological Association (APA)
Roy, Vandana& Shukla, Shailja& Shukla, Piyush Kumar& Rawat, Paresh. 2017. Gaussian Elimination-Based Novel Canonical Correlation Analysis Method for EEG Motion Artifact Removal. Journal of Healthcare Engineering،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1181449
Modern Language Association (MLA)
Roy, Vandana…[et al.]. Gaussian Elimination-Based Novel Canonical Correlation Analysis Method for EEG Motion Artifact Removal. Journal of Healthcare Engineering No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1181449
American Medical Association (AMA)
Roy, Vandana& Shukla, Shailja& Shukla, Piyush Kumar& Rawat, Paresh. Gaussian Elimination-Based Novel Canonical Correlation Analysis Method for EEG Motion Artifact Removal. Journal of Healthcare Engineering. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1181449
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1181449