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A Framework for Evaluating ICA Methods of Artifact Removal from Multichannel EEG [chapter]

Kevin A. Glass, Gwen A. Frishkoff, Robert M. Frank, Colin Davey, Joseph Dien, Allen D. Malony, Don M. Tucker
2004 Lecture Notes in Computer Science  
We present a method for evaluating ICA separation of artifacts from EEG (electroencephalographic) data.  ...  When a match between the blink-template and the decomposition was obtained, the contribution of the source was subtracted from the EEG.  ...  Discussion In this report we have demonstated a new method for evaluation of ICA for removal of blink activity from multichannel EEG.  ... 
doi:10.1007/978-3-540-30110-3_130 fatcat:p2exega3gzfq5n4bkx7bknszd4

A Two Stage Approach with ICA and Double Density Wavelet Transform for Artifacts Removal in Multichannel EEG Signals

Vandana Roy, Shailja Shukla
2015 International Journal of Bio-Science and Bio-Technology  
Further this paper presents a novel method with combination of ICA, information sharing and double density wavelet transform to reject the artifacts from the signal.  ...  For suppression of ocular artifact in EEG this paper proposes a component based Independent Component Analysis (ICA) model.  ...  Proposed Method A proposed novel technique used both the wavelet transfer& ICA for removal of artifacts from the given signal.  ... 
doi:10.14257/ijbsbt.2015.7.4.29 fatcat:f2uaegh4pfbixloasqsmuqpt7m

Iterative Subspace Decomposition for Ocular Artifact Removal from EEG Recordings [chapter]

Cédric Gouy-Pailler, Reza Sameni, Marco Congedo, Christian Jutten
2009 Lecture Notes in Computer Science  
In this study, we present a method to remove ocular artifacts from electroencephalographic (EEG) recordings.  ...  This method is based on the detection of the EOG activation periods from a reference EOG channel, definition of covariance matrices containing the nonstationary information of the EOG, and applying generalized  ...  In this work, we develop a similar idea based on GEVD for the automatic detection and removal of EOG artifacts from multichannel EEG recordings.  ... 
doi:10.1007/978-3-642-00599-2_53 fatcat:vtcp2qewmnabfa7bk2t6v347ea

Removal of EMG Artifacts from Multichannel EEG Signals Using Combined Singular Spectrum Analysis and Canonical Correlation Analysis

Qingze Liu, Aiping Liu, Xu Zhang, Xiang Chen, Ruobing Qian, Xun Chen
2019 Journal of Healthcare Engineering  
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  ...  Electroencephalography (EEG) signals collected from human scalps are often polluted by diverse artifacts, for instance electromyogram (EMG), electrooculogram (EOG), and electrocardiogram (ECG) artifacts  ...  As a well-known and effective BSS method, ICA is widely adopted for artifact removal from EEG since its first application in the field of brain electrical noise reduction [10, 11] .  ... 
doi:10.1155/2019/4159676 pmid:31976053 pmcid:PMC6955116 fatcat:kbxxsngalnbobin75miir2lrua

Artifact Removing From Eeg Recordings Using Independent Component Analysis with High-order Statistics

Theodor D. Popescu
2021 International Journal of Mathematical Models and Methods in Applied Sciences  
In this paper it is presented a generally applicable method for removing a wide variety of artifacts from EEG recordings based on Independent Component Analysis (ICA) with highorder statistics.  ...  Use of Principal Component Analysis (PCA) has been proposed to remove eye artifacts from multichannel EEG.  ...  Acknowledgment The author thanks the Executive Agency for Higher Education, Research, Development and Innovation Funding (UEFISCDI) and Ministry of Research and Innovation, for the support under Contract  ... 
doi:10.46300/9101.2021.15.11 fatcat:o373rlq7erfh5djhdk7hc3biim

Artifact Removing From Eeg Recordings Using Independent Component Analysis With High-order Statistics

Theodor D. Popescu
2021 North atlantic university union: International Journal of Circuits, Systems and Signal Processing  
In this paper it is presented a gener- ally applicable method for removing a wide vari- ety of artifacts from EEG recordings based on In- dependent Component Analysis (ICA) with high- order statistics.  ...  Use of Principal Com- ponent Analysis (PCA) has been proposed to re- move eye artifacts from multichannel EEG.  ...  Artifact removing from EEG recordings using ICA A.  ... 
doi:10.46300/9106.2021.15.144 fatcat:ihe3fuhaurahxpzzhnivsxddbu

Artifact reduction in multichannel pervasive EEG using hybrid WPT-ICA and WPT-EMD signal decomposition techniques

Valentina Bono, Wasifa Jamal, Saptarshi Das, Koushik Maharatna
2014 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
The signal cleaning performances of WPT-EMD and WPT-ICA algorithms have been compared using a signal-to-noise ratio (SNR)-like criterion for artifacts.  ...  In order to reduce the muscle artifacts in multi-channel pervasive Electroencephalogram (EEG) signals, we here propose and compare two hybrid algorithms by combining the concept of wavelet packet transform  ...  Although a wealth of research exists exploring possible methods of artifact separation from conventional EEG systems, most of them assume either a-priori knowledge of the source of artifacts or use simulated  ... 
doi:10.1109/icassp.2014.6854728 dblp:conf/icassp/BonoJDM14 fatcat:jsejtkuiave2potz3ctsgwausu

Effective EEG Motion Artifact Removal with KS test Blind Source Separation and Wavelet Transform

Vandana Roy, Shailja Shukla
2016 International Journal of Bio-Science and Bio-Technology  
Artifacts frequently corrupt biomedical signal recording and processing, therefore, removal of these artifacts from physiological signals is an essential step.  ...  In this research work an enhanced empirical approach to model the artifacts of EEG signal are described.  ...  Proposed Architecture for EEG Artifacts Removal in Single Channel Signal First [ [7] ] proposed the ICA and EEMD in combined form for separation of source and artifacts from the input signal in a given  ... 
doi:10.14257/ijbsbt.2016.8.5.13 fatcat:fzuublechbcq7lxldou7pdf4he

Temporally constrained ica: an application to artifact rejection in electromagnetic brain signal analysis

C.J. James, O.J. Gibson
2003 IEEE Transactions on Biomedical Engineering  
brain signals of interest can range from observations of seizure activity in ictal EEG recordings, to visual evoked fields (VEFs) in MEG recordings of normal subjects.  ...  the EEG data.  ...  Lowe for his useful comments in the preparation of this paper, the Wellcome Trust Laboratory for MEG Studies at Aston University for the MEG data and the Montreal Neurological Institute and Hospital for  ... 
doi:10.1109/tbme.2003.816076 pmid:12943278 fatcat:w2lonknmknfrrajgcso6iukm4a

A Preliminary Study of Muscular Artifact Cancellation in Single-Channel EEG

Xun Chen, Aiping Liu, Hu Peng, Rabab Ward
2014 Sensors  
For the conventional case, where the EEG recordings are obtained simultaneously over many EEG channels, there exists a considerable range of methods for removing muscular artifacts.  ...  The proposed method is shown to significantly outperform all other methods. It can successfully remove muscular artifacts without altering the underlying EEG activity.  ...  McKeown and his research group for their assistance in the preparation and examination of the clinical data.  ... 
doi:10.3390/s141018370 pmid:25275348 pmcid:PMC4239950 fatcat:ilikvpmsdjaxboacupyp7qro4y

Embedding Decomposition for Artifacts Removal in EEG Signals [article]

Junjie Yu, Chenyi Li, Kexin Lou, Chen Wei, Quanying Liu
2022 arXiv   pre-print
The proposed method is tested with a semi-synthetic EEG dataset and a real task-related EEG dataset, suggesting that DeepSeparator outperforms the conventional models in both EOG and EMG artifact removal  ...  Electroencephalogram (EEG) recordings are often contaminated with artifacts. Various methods have been developed to eliminate or weaken the influence of artifacts.  ...  ACKNOWLEDGEMENT We thank the anonymous reviewers for the insightful suggestions, and Mr. Haoming Zhang for his EEGdenoiseNET.  ... 
arXiv:2112.00989v2 fatcat:3abdeyq4yncchi33vre43tgp3u

A Methodology for Validating Artifact Removal Techniques for Physiological Signals

K. T. Sweeney, H. Ayaz, T. E. Ward, M. Izzetoglu, S. F. McLoone, B. Onaral
2012 IEEE Transactions on Information Technology in Biomedicine  
Artifact removal from physiological signals is an essential component of the biosignal processing pipeline.  ...  A number of commonly implemented artifact removal techniques were evaluated using the described methodology to validate the proposed novel test platform.  ...  A technique must, therefore, be implemented to generate a multichannel signal from a single-channel recording to allow for the use of the ICA algorithm.  ... 
doi:10.1109/titb.2012.2207400 pmid:22801522 fatcat:5qrpfon6yvdyvf5qzwgv6mvhm4

Compressed Sensing for Energy-Efficient Wireless Telemonitoring: Challenges and Opportunities [article]

Zhilin Zhang, Bhaskar D. Rao, Tzyy-Ping Jung
2014 arXiv   pre-print
The proposed algorithm was used for compressed sensing of multichannel electroencephalographic (EEG) signals for estimating vehicle drivers' drowsiness.  ...  As a lossy compression framework, compressed sensing has drawn much attention in wireless telemonitoring of biosignals due to its ability to reduce energy consumption and make possible the design of low-power  ...  For example, to remove movement artifacts in EEG signals, independent component analysis (ICA) [18] is generally used.  ... 
arXiv:1311.3995v2 fatcat:34mbukx3mre4de5ktrv2sxgen4

Hybrid EEG—Eye Tracker: Automatic Identification and Removal of Eye Movement and Blink Artifacts from Electroencephalographic Signal

Malik Mannan, Shinjung Kim, Myung Jeong, M. Kamran
2016 Sensors  
In this paper, we proposed an automatic framework based on independent component analysis (ICA) and system identification to identify and remove ocular artifacts from EEG data by using hybrid EEG and eye  ...  The comparison with the two state-of-the-art techniques namely ADJUST based ICA and REGICA reveals the significant improved performance of the proposed algorithm for removing eye movement and blink artifacts  ...  Finally, the proposed algorithm was tested on a standard EEG dataset to determine its utility for removal of ocular artifacts from EEG.  ... 
doi:10.3390/s16020241 pmid:26907276 pmcid:PMC4801617 fatcat:ej7zmr5lvjh4rngalapokrquey

Automatic Identification of Artifact-Related Independent Components for Artifact Removal in EEG Recordings

Yuan Zou, Viswam Nathan, Roozbeh Jafari
2016 IEEE journal of biomedical and health informatics  
Researchers often clean EEG recordings with assistance from independent component analysis (ICA), since it can decompose EEG recordings into a number of artifact-related and event-related potential (ERP  ...  Qualitative evaluation of the reconstructed EEG signals demonstrates that our proposed method can effectively enhance the signal quality, especially the quality of ERPs, even for those that barely display  ...  ICA is a statistical tool that decomposes a multichannel EEG recording into a set of independent components (ICs), which represent a statistical estimate of the maximally independent source signals [8  ... 
doi:10.1109/jbhi.2014.2370646 pmid:25415992 pmcid:PMC5309922 fatcat:hq26gnq4brelbhwjrpfncemrzu
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