Abstract
Artifacts in magnetoneurography data due to endogenous biological noise sources, like the cardiac signal, can be four orders of magnitude higher than the signal of interest. Therefore, it is important to establish effective artifact reduction methods. We propose a blind source separation algorithm using only second-order temporal correlations for cleaning biomagnetic measurements of evoked responses in the peripheral nervous system. The algorithm showed its efficiency by eliminating disturbances originating from biological and technical noise sources and successfully extracting the signal of interest. This yields a significant improvement of the neuro-magnetic source analysis.
Original language | English |
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Pages (from-to) | 75-87 |
Number of pages | 13 |
Journal | IEEE Transactions on Biomedical Engineering |
Volume | 47 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2000 |
Keywords
- Artifact reduction
- Biomagnetism
- Biomédical data processing
- Blind source separation
- Independent component analysis
- Magnetoneurography (MNG)
ASJC Scopus subject areas
- Biomedical Engineering