NDLI: On Estimating the Signal Subspace Dimension of High-Density Multichannel Magnetoencephalogram Measurements

Content Provider	IEEE Xplore Digital Library
Author	Hesse, C.W.
Copyright Year	2007
Description	Author affiliation: F.C. Donders Centre for Cognitive Neuroimaging, Nijmegen (Hesse, C.W.)
Abstract	Accurate estimates of the dimension and an (orthogonal) basis of the signal subspace of noise corrupted multichannel measurements are essential for accurate identification and extraction of any signals of interest within that subspace. For most biomedical signals comprising very large numbers of channels, including the magnetoencephalogram (MEG), the ";true"; number of underlying signals -although ultimately unknown - is unlikely to be of the same order as the number of measurements, and has to be estimated from the available data. This work examines several second-order statistical approaches to signal subspace (dimension) estimation with respect to their underlying assumptions and their performance in high- dimensional measurement spaces using 151-channel MEG data. The purpose is to identify which of these methods might be most appropriate for modeling the signal subspace structure of high-density MEG data recorded under controlled conditions, and what are the practical consequences with regard to the subsequent application of biophysical modeling and statistical source separation techniques.
Starting Page	6227
Ending Page	6230
File Size	828653
Page Count	4
File Format	PDF
ISBN	9781424407873
ISSN	1557170X
DOI	10.1109/IEMBS.2007.4353778
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-22
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Signal processing Electroencephalography Biomedical measurements Magnetic field measurement Magnetic separation Noise measurement Sensor arrays Signal analysis Extraterrestrial measurements Brain modeling
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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