Noise reduction from MEG data
Shinpei Okawa, Satoshi Honda · Society of Instrument and Control Engineers of Japan · 2004
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.