The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Canonical Correlation Analysis Applied to Remove Muscle Artifacts From the Electroencephalogram
Abstract
The electroencephalogram (EEG) is often contaminated by muscle artifacts. In this paper, a new method for muscle artifact removal in EEG is presented, based on canonical correlation analysis (CCA) as a blind source separation (BSS) technique. This method is demonstrated on a synthetic data set. The method outperformed a low-pass filter with different cutoff frequencies and an independent component analysis (ICA)-based technique for muscle artifact removal. In addition, the method is applied on a real ictal EEG recording contaminated with muscle artifacts. The proposed method removed successfully the muscle artifact without altering the recorded underlying ictal activity.
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Citations
Cites
RELATIONS BETWEEN TWO SETS OF VARIATES
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A blind source separation technique using second-order statistics
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Relations Between Two Sets of Variates
Hotelling, H. (1936) · Biometrika · doi:10.2307/2333955 · Cited by 1,645
High-Order Contrasts for Independent Component Analysis
Cardoso, J.-F. (1999) · Neural Computation · doi:10.1162/089976699300016863 · Cited by 1,213
EMG contamination of EEG: spectral and topographical characteristics
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IFCN standards for digital recording of clinical EEG
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TDSEP — an efficient algorithm for blind separation using time structure
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Independent Component Analysis as a Tool to Eliminate Artifacts in EEG: A Quantitative Study
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Cited by
EEG artifact removal—state-of-the-art and guidelines
Urigüen, J. A., & Garcia-Zapirain, B. (2015) · Journal of Neural Engineering · doi:10.1088/1741-2560/12/3/031001 · Cited by 963
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Review on solving the forward problem in EEG source analysis
Hallez, H., Vanrumste, B., Grech, R., Muscat, J., De Clercq, W., Vergult, A., D'Asseler, Y., Camilleri, K. P., Fabri, S. G., Van Huffel, S., et al. (2007) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-4-46 · Cited by 527
Self-citationSignal Artifacts and Techniques for Artifacts and Noise Removal
Islam, M. K., Rastegarnia, A., & Sanei, S. (2021) · Intelligent Systems Reference Library · doi:10.1007/978-3-030-54932-9_2 · Cited by 54
Role of N-Methyl D-aspartate receptors in action-based predictive coding deficits in schizophrenia
Kort, N. S., Ford, J. M., Roach, B. J., Gunduz-Bruce, H., Krystal, J. H., Jaeger, J., Reinhart, R. M. G., & Mathalon, D. H. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2016.06.019 · Cited by 48
Metadata
- Authors
- Clercq, W. D., Vergult, A., Vanrumste, B., Van Paesschen, W., & Van Huffel, S.
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2006-11
- Volume
- 53
- Issue
- 12
- Pages
- 2583-2587
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- OpenAlex
- W2082930519
- Cited by
- 522
- References
- 14
- FWCI
- 4.30
- Type
- journal article
- Language
- en
- Open access
- closed
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- Clercq, W. D., Vergult, A., Vanrumste, B., Van Paesschen, W., & Van Huffel, S. (2006). Canonical Correlation Analysis Applied to Remove Muscle Artifacts From the Electroencephalogram. IEEE Transactions on Biomedical Engineering. https://doi.org/10.1109/tbme.2006.879459
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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