Artifact reduction in magnetoneurography based on time-delayed second-order correlations

Andreas Ziehe; Klaus Robert Müller; Guido Nolle; Bruno Marcel Mackert; Gabriel Curio

doi:10.1109/10.817622

Artifact reduction in magnetoneurography based on time-delayed second-order correlations

Andreas Ziehe, Klaus Robert Müller, Guido Nolle, Bruno Marcel Mackert, Gabriel Curio

Research output: Contribution to journal › Article › peer-review

96 Citations (Scopus)

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	https://doi.org/10.1109/10.817622
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

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10.1109/10.817622

Cite this

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title = "Artifact reduction in magnetoneurography based on time-delayed second-order correlations",

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.",

keywords = "Artifact reduction, Biomagnetism, Biom{\'e}dical data processing, Blind source separation, Independent component analysis, Magnetoneurography (MNG)",

author = "Andreas Ziehe and M{\"u}ller, {Klaus Robert} and Guido Nolle and Mackert, {Bruno Marcel} and Gabriel Curio",

note = "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. M{\"u}ller 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.",

year = "2000",

doi = "10.1109/10.817622",

language = "English",

volume = "47",

pages = "75--87",

journal = "IEEE Transactions on Biomedical Engineering",

issn = "0018-9294",

publisher = "IEEE Computer Society",

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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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JO - IEEE Transactions on Biomedical Engineering

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SN - 0018-9294

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ER -

Artifact reduction in magnetoneurography based on time-delayed second-order correlations

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Keywords

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