Paper Info
Title
Employing spatially constrained ICA and wavelet denoising, for automatic removal of artifacts from multichannel EEG data
Abstract
Detecting artifacts produced in electroencephalographic (EEG) data by muscle activity, eye blinks and electrical noise, etc., is an important problem in EEG signal processing research. These artifacts must be corrected before further analysis because it renders subsequent analysis very error-prone. One solution is to reject the data segment if artifact is present during the observation interval, however, the rejected data segment could contain important information masked by the artifact. The independent component analysis (ICA) can be an effective and applicable method for EEG denoising. The goal of this paper is to propose a framework, based on ICA and wavelet denoising (WD), to improve the pre-processing of EEG signals. In particular we employ concept of the spatially constrained ICA (SCICA) to extract artifact-only independent components (ICs) from the given EEG data, use WD to remove any cerebral activity from the extracted-artifacts ICs, and finally project back the artifacts to be subtracted from EEG signals to get clean EEG data. The main advantage of the proposed approach is faster computation, as it is not necessary to identify all ICs. Computer experiments are carried out, which demonstrate effectiveness of the proposed approach in removing focal artifacts that can be well separated by SCICA.
Year
DOI
Venue
2012
10.1016/j.sigpro.2011.08.005
Signal Processing
Keywords
Field
DocType
subsequent analysis,independent component analysis,multichannel eeg data,automatic removal,eeg signal processing research,clean eeg data,employing spatially,eeg denoising,eeg data,extracted-artifacts ics,data segment,eeg signal,wavelet denoising,eeg
Noise reduction,Computer vision,Computer experiment,Data segment,Computer science,Noise (electronics),Independent component analysis,Artificial intelligence,Electroencephalography,Computation,Wavelet denoising
Journal
Volume
Issue
ISSN
92
2
0165-1684
Citations 
PageRank 
References 
42
2.81
18
Authors
3
Name
Order
Citations
PageRank
Muhammad Tahir AKHTAR112719.33
Wataru MITSUHASHI2656.72
Christopher J. James320621.93