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.
| Original language | English |
|---|---|
| Pages | 1975-1979 |
| Number of pages | 5 |
| Publication status | Published - 2004 Dec 1 |
| Event | SICE Annual Conference 2004 - Sapporo, Japan Duration: 2004 Aug 4 → 2004 Aug 6 |
Other
| Other | SICE Annual Conference 2004 |
|---|---|
| Country | Japan |
| City | Sapporo |
| Period | 04/8/4 → 04/8/6 |
Keywords
- Factor analysis
- ICA
- Kalman filter
- MEG
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Electrical and Electronic Engineering