Papers

2008

Estimation of Signal and Noise Covariance using ICA for High-Resolution Cortical Dipole Imaging

2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vols 1-8
  • Junichi Hori

First page
3987
Last page
3990
Language
English
Publishing type
Research paper (international conference proceedings)
Publisher
IEEE

Suitable spatial filters were explored for inverse estimation of cortical dipole imaging from a scalp electroencephalogram. Computer simulations were used to examine the effects of incorporating statistical information of signal and noise into inverse procedures. Actually, the parametric projection filter (PPF) and parametric Wiener filter (PWF) were applied to an inhomogeneous three-sphere head model. The signal and noise covariance matrices were estimated by applying independent component analysis (ICA) to the scalp potentials. The simulation results described herein suggest that the PPF using differential noise between EEG and separated signal were equivalent to those obtained using the method with actual noise. Moreover, the PWF using separated signals has better performance than traditional inverse techniques.

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Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000262404502192&DestApp=WOS_CPL
ID information
  • ISSN : 1557-170X
  • Web of Science ID : WOS:000262404502192

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