Noise reduction from MEG data

Shinpei Okawa, Satoshi Honda

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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 languageEnglish
Title of host publicationProceedings of the SICE Annual Conference
Pages1975-1979
Number of pages5
Publication statusPublished - 2004
EventSICE Annual Conference 2004 - Sapporo, Japan
Duration: 2004 Aug 4 → 2004 Aug 6

Other

OtherSICE Annual Conference 2004
CountryJapan
CitySapporo
Period04/8/4 → 04/8/6

Fingerprint

Noise abatement
Factor analysis
Kalman filters
Sensors
Independent component analysis
Acoustic noise
Signal to noise ratio

Keywords

  • Factor analysis
  • ICA
  • Kalman filter
  • MEG

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Okawa, S., & Honda, S. (2004). Noise reduction from MEG data. In Proceedings of the SICE Annual Conference (pp. 1975-1979). [FAII-7-3]

Noise reduction from MEG data. / Okawa, Shinpei; Honda, Satoshi.

Proceedings of the SICE Annual Conference. 2004. p. 1975-1979 FAII-7-3.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Okawa, S & Honda, S 2004, Noise reduction from MEG data. in Proceedings of the SICE Annual Conference., FAII-7-3, pp. 1975-1979, SICE Annual Conference 2004, Sapporo, Japan, 04/8/4.
Okawa S, Honda S. Noise reduction from MEG data. In Proceedings of the SICE Annual Conference. 2004. p. 1975-1979. FAII-7-3
Okawa, Shinpei ; Honda, Satoshi. / Noise reduction from MEG data. Proceedings of the SICE Annual Conference. 2004. pp. 1975-1979
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