Title :
Noise reduction from MEG data
Author :
Okawa, Shinpei ; Honda, Satoshi
Author_Institution :
Graduate Sch. of Sci. & Technol., Keio Univ., Yokohama, Japan
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;
Conference_Titel :
SICE 2004 Annual Conference
Conference_Location :
Sapporo
Print_ISBN :
4-907764-22-7
