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 |
|---|---|
| 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 Jan 24 |
| Externally published | Yes |
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Keywords
- Artifact reduction
- Biomagnetism
- Biomedical data processing
- Blind source separation
- Independent component analysis
- Magnetoneurography (MNG)
ASJC Scopus subject areas
- Biomedical Engineering
Cite this
Artifact reduction in magnetoneurography based on time-delayed second- order correlations. / Ziehe, Andreas; Muller, Klaus; Nolte, Guido; Mackert, Bruno Marcel; Curio, Gabriel.
In: IEEE Transactions on Biomedical Engineering, Vol. 47, No. 1, 24.01.2000, p. 75-87.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Artifact reduction in magnetoneurography based on time-delayed second- order correlations
AU - Ziehe, Andreas
AU - Muller, Klaus
AU - Nolte, Guido
AU - Mackert, Bruno Marcel
AU - Curio, Gabriel
PY - 2000/1/24
Y1 - 2000/1/24
N2 - 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.
AB - 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.
KW - Artifact reduction
KW - Biomagnetism
KW - Biomedical data processing
KW - Blind source separation
KW - Independent component analysis
KW - Magnetoneurography (MNG)
UR - http://www.scopus.com/inward/record.url?scp=0033982156&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0033982156&partnerID=8YFLogxK
U2 - 10.1109/10.817622
DO - 10.1109/10.817622
M3 - Article
C2 - 10646282
AN - SCOPUS:0033982156
VL - 47
SP - 75
EP - 87
JO - IEEE Transactions on Biomedical Engineering
JF - IEEE Transactions on Biomedical Engineering
SN - 0018-9294
IS - 1
ER -