Title :
Independent component approach to the analysis of EEG and MEG recordings
Author :
Vigário, Ricardo ; Särelä, Jaakko ; Jousmiki, V. ; Hämäläinen, Matti ; Oja, Erkki
Author_Institution :
Lab. of Comput. & Inf. Sci., Helsinki Univ. of Technol., Espoo, Finland
fDate :
5/1/2000 12:00:00 AM
Abstract :
Multichannel recordings of the electromagnetic fields emerging from neural currents in the brain generate large amounts of data. Suitable feature extraction methods are, therefore, useful to facilitate the representation and interpretation of the data. Recently developed independent component analysis (ICA) has been shown to be an efficient tool for artifact identification and extraction from electroencephalographic (EEG) and magnetoencephalographic (MEG) recordings. In addition, ICA has been applied to the analysis of brain signals evoked by sensory stimuli. This paper reviews our recent results in this field.
Keywords :
auditory evoked potentials; electroencephalography; feature extraction; magnetoencephalography; medical signal processing; statistical analysis; EEG recordings; MEG recordings; artifact identification; averaged auditory evoked fields; brain; brain signals; electroencephalographic recording; electromagnetic fields; feature extraction; independent component approach; magnetoencephalographic recording; multichannel recordings; neural currents; sensory stimuli; Blind source separation; Data mining; Electroencephalography; Feature extraction; Independent component analysis; Magnetic analysis; Magnetic separation; Signal analysis; Signal processing algorithms; Source separation; Algorithms; Artifacts; Electroencephalography; Evoked Potentials, Auditory; Evoked Potentials, Somatosensory; Humans; Magnetoencephalography; Signal Processing, Computer-Assisted;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
