Abstract / Description of output
The aim of this pilot study was to assess the usefulness of independent component analysis (ICA) to detect cardiac artifacts and power line interferences in magnetoencephalogram (MEG) recordings. We recorded MEG signals from six subjects with, a 148-channel whole-head magnetometer (MAGNES 2500 WH, 4D Neuroimaging). Epochs of 50 s with power line noise, cardiac, and ocular artifacts were selected for analysis. We applied a statistical criterion to determine the number of sources, and a robust ICA algorithm to decompose the MEG epochs. Skewness, kurtosis, and a spectral metric were used to mark the studied artifacts. We found that the power fine interference could be easily detected by its frequency characteristics. Moreover, skewness outperformed kurtosis when identifying the cardiac artifact.
Original language | English |
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Title of host publication | 2006 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vols 1-15 |
Place of Publication | NEW YORK |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 273-276 |
Number of pages | 4 |
ISBN (Print) | 978-1-4244-0032-4 |
Publication status | Published - 2006 |
Event | 28th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society - New York, United Kingdom Duration: 30 Aug 2006 → 3 Sept 2006 |
Conference
Conference | 28th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society |
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Country/Territory | United Kingdom |
Period | 30/08/06 → 3/09/06 |
Keywords / Materials (for Non-textual outputs)
- BLIND SOURCE SEPARATION
- OCULAR ARTIFACTS
- IDENTIFICATION
- REMOVAL
- SIGNALS
- EEG
- FIELDS
- BRAIN