TY - JOUR
T1 - Artifact reduction in magnetoneurography based on time-delayed second-order correlations
AU - Ziehe, Andreas
AU - Müller, Klaus Robert
AU - Nolle, Guido
AU - Mackert, Bruno Marcel
AU - Curio, Gabriel
N1 - Funding Information:
Manuscript received August 24, 1998; revised June 22, 1999. This work was supported in part by the Deutsche Forschungsgemeinschaft (DFG) under Contracts JA 379/51 and JA 379/71. The work of G. Nolte, B.-M. Mackert, and G. Curio was supported by the DFG under Grants MA 1782/1-1 and 1-2, and MA 1828/3-1. Asterisk indicates corresponding author. A. Ziehe is with GMD FIRST, 12489 Berlin, Germany. *K.-R. Müller is with GMD FIRST, Rudower Chaussee 5, 12489 Berlin, Germany (e-mail: klaus@first.gmd.de). G. Nolte, B.-M. Mackert, and G. Curio are with the Neurophysics Group, Department of Neurology, Klinikum Benjamin Franklin, 12200 Berlin, Germany. Publisher Item Identifier S 0018-9294(00)00245-7.
PY - 2000
Y1 - 2000
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 - Biomédical data processing
KW - Blind source separation
KW - Independent component analysis
KW - Magnetoneurography (MNG)
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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 -