DocumentCode
1624892
Title
Noise reduction from MEG data
Author
Okawa, Shinpei ; Honda, Satoshi
Author_Institution
Graduate Sch. of Sci. & Technol., Keio Univ., Yokohama, Japan
Volume
2
fYear
2004
Firstpage
1431
Abstract
A method that reduces sensor noise and artifacts from MEG data is proposed. Factor analysis and Kalman filter are employed for sensor noise reduction. Factor analysis estimates noise covariances for Kalman filter. After the sensor noise reduction, independent component analysis (ICA) is used to eliminate artifacts. Simulation studies confirmed that the signal-to-noise ratio of estimated independent component increases.
Keywords
Kalman filters; independent component analysis; magnetoencephalography; noise abatement; sensors; Kalman filter; MEG data; factor analysis; independent component analysis; magnetoencephalography; noise covariances; sensor noise reduction; signal-to-noise ratio;
fLanguage
English
Publisher
ieee
Conference_Titel
SICE 2004 Annual Conference
Conference_Location
Sapporo
Print_ISBN
4-907764-22-7
Type
conf
Filename
1491649
Link To Document