Removing muscle and eye artifacts using blind source separation techniques in ictal EEG source imaging.
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Summary
The results show that BSS-CCA and SCICA can be applied to remove artifacts, but the results should be interpreted with care, because the results of the source estimation can be misleading due to excessive noise or modeling errors.
- Type
- article
- Published
- 2009-07-01
- Cited by
- 44
- References
- 29
- OpenAlex
- https://openalex.org/W2080373262
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:20532252
Keywords
Ictal-Interictal SPECT Analysis by SPM, Ictal, Blind signal separation, Electroencephalography, Computer science
References
- Statistical Parametric Mapping: The Analysis of Functional Brain Images
- Partial signal space projection for artefact removal in MEG measurements: a theoretical analysis.
- 3D source localization of interictal spikes in epilepsy patients with MRI lesions
- Removal of eye blinking artifact from the electro-encephalogram, incorporating a new constrained blind source separation algorithm
- Ictal SPECT in neocortical epilepsies: clinical usefulness and factors affecting the pattern of hyperperfusion
- Electroencephalography: Basic Principles, Clinical Applications and Related Fields
- Electromagnetic brain mapping
- EMG contamination of EEG: spectral and topographical characteristics.
- The use of SPECT and PET in routine clinical practice in epilepsy
- Relations Between Two Sets of Variates
- Dipole modelling of eye activity and its application to the removal of eye artefacts from the EEG and MEG.
- A finite difference method with reciprocity used to incorporate anisotropy in electroencephalogram dipole source localization
- Subtraction ictal SPECT co‐registered to MRI improves clinical usefulness of SPECT in localizing the surgical seizure focus
- Ictal Source Localization in Presurgical Patients With Refractory Epilepsy
- Continuous Source Imaging of Scalp Ictal Rhythms in Temporal Lobe Epilepsy
- Removing electroencephalographic artifacts by blind source separation.
- EEG source localization in focal epilepsy: Where are we now?
- Canonical Correlation Analysis Applied to Remove Muscle Artifacts From the Electroencephalogram
- Source localization using recursively applied and projected (RAP) MUSIC
- Can dipole modelling be improved by removing muscular and ocular artifacts from ictal scalp EEG?
Cited by
- Mobile EEG on the bike: disentangling attentional and physical contributions to auditory attention tasks
- Automatic high-frequency oscillation detection from tripolar concentric ring electrode scalp recording
- A method of underdetermined blind source separation in time-domain
- Multi-Class Motor Imagery EEG Decoding for Brain-Computer Interfaces
- ONLINE REMOVAL OF EYE BLINK ARTIFACT FROM SCALP EEG USING CANONICAL CORRELATION ANALYSIS BASED METHOD
- Artifact reduction in multichannel pervasive EEG using hybrid WPT-ICA and WPT-EMD signal decomposition techniques
- Dual Adaptive Filtering by Optimal Projection Applied to Filter Muscle Artifacts on EEG and Comparative Study
- Denoising of Ictal EEG Data Using Semi-Blind Source Separation Methods Based on Time-Frequency Priors
- Removal of EOG and EMG artifacts from EEG using combination of functional link neural network and adaptive neural fuzzy inference system
- Block term decomposition for modelling epileptic seizures
- Classification of EEG Signals Produced by RGB Colour Stimuli
- High-Frequency Oscillations Recorded on the Scalp of Patients With Epilepsy Using Tripolar Concentric Ring Electrodes
- Removal of muscle artifact from EEG data: comparison between stochastic (ICA and CCA) and deterministic (EMD and wavelet-based) approaches
- Removing Muscle Artifacts From EEG Data: Multichannel or Single-Channel Techniques?
- Influence of anisotropic conductivities in EEG source estimation in patients with epilepsy
- Hybrid Wavelet and EMD/ICA Approach for Artifact Suppression in Pervasive EEG
- A Wavelet-Based Artifact Reduction From Scalp EEG for Epileptic Seizure Detection
- Methods for artifact detection and removal from scalp EEG: A review
- Ictal EEG signal denoising by combination of a Semi-Blind Source Separation method and Multiscale PCA
- Independent Vector Analysis Applied to Remove Muscle Artifacts in EEG Data
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