Removal of Electrooculogram Artifacts from Electroencephalogram Using Canonical Correlation Analysis with Ensemble Empirical Mode Decomposition
Published 2017 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Removal of Electrooculogram Artifacts from Electroencephalogram Using Canonical Correlation Analysis with Ensemble Empirical Mode Decomposition
Authors
Keywords
Electroencephalogram (EEG), Electrooculogram (EOG), Artifacts removal, Canonical correlation analysis (CCA), Ensemble empirical mode decomposition (EEMD)
Journal
Cognitive Computation
Volume 9, Issue 5, Pages 626-633
Publisher
Springer Nature
Online
2017-06-05
DOI
10.1007/s12559-017-9478-0
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Sparse Bayesian Learning for Obtaining Sparsity of EEG Frequency Bands Based Feature Vectors in Motor Imagery Classification
- (2017) Yu Zhang et al. International Journal of Neural Systems
- Subject-based feature extraction by using fisher WPD-CSP in brain–computer interfaces
- (2016) Banghua Yang et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- Fast nonnegative tensor factorization based on accelerated proximal gradient and low-rank approximation
- (2016) Yu Zhang et al. NEUROCOMPUTING
- Group Component Analysis for Multiblock Data: Common and Individual Feature Extraction
- (2016) Guoxu Zhou et al. IEEE Transactions on Neural Networks and Learning Systems
- Artifacts-matched blind source separation and wavelet transform for multichannel EEG denoising
- (2015) Md Rakibul Mowla et al. Biomedical Signal Processing and Control
- Alternative Techniques of Neural Signal Processing in Neuroengineering
- (2015) Jordi Solé-Casals et al. Cognitive Computation
- Embedded Implementation of Second-Order Blind Identification (SOBI) for Real-Time Applications in Neuroscience
- (2014) Xun Zhang et al. Cognitive Computation
- AGGREGATION OF SPARSE LINEAR DISCRIMINANT ANALYSES FOR EVENT-RELATED POTENTIAL CLASSIFICATION IN BRAIN-COMPUTER INTERFACE
- (2013) YU ZHANG et al. International Journal of Neural Systems
- FREQUENCY RECOGNITION IN SSVEP-BASED BCI USING MULTISET CANONICAL CORRELATION ANALYSIS
- (2013) YU ZHANG et al. International Journal of Neural Systems
- Quadcopter control in three-dimensional space using a noninvasive motor imagery-based brain–computer interface
- (2013) Karl LaFleur et al. Journal of Neural Engineering
- Multivariate Synchronization Analysis of Brain Electroencephalography Signals: A Review of Two Methods
- (2013) Mahdi Jalili Cognitive Computation
- The Use of Ensemble Empirical Mode Decomposition With Canonical Correlation Analysis as a Novel Artifact Removal Technique
- (2012) Kevin T. Sweeney et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
- Classification of Motor Imagery BCI Using Multivariate Empirical Mode Decomposition
- (2012) Cheolsoo Park et al. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
- APPLICATION OF EMPIRICAL MODE DECOMPOSITION (EMD) FOR AUTOMATED DETECTION OF EPILEPSY USING EEG SIGNALS
- (2012) ROSHAN JOY MARTIS et al. International Journal of Neural Systems
- Combination of Canonical Correlation Analysis and Empirical Mode Decomposition Applied to Denoising the Labor Electrohysterogram
- (2011) M. Hassan et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
- Book Reviews: Introduction to Multivariate Statistical Analysis in ChemometricsIntroduction to Multivariate Statistical Analysis in Chemometrics. VarmuzaKurt and FilzmoserPeter. CRC Press, Boca Raton, FL, 2009. Pp: 321. Price: USD$119.95. ISBN 13 978-1-4200-5947-2.
- (2010) Steven D. Brown APPLIED SPECTROSCOPY
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now