Independent component analysis: fetal signal reconstruction from magnetocardiographic recordings

Independent component analysis (ICA) was used for the processing of cardiological signals obtained by means of fetal magnetocardiography (fMCG), a technique allowing the non-invasive recording of the weak magnetic field variations associated to the electrical activity of the fetal heart. Purpose of...

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Vydáno v:Computer methods and programs in biomedicine Ročník 75; číslo 2; s. 163 - 177
Hlavní autoři: Comani, Silvia, Mantini, Dante, Pennesi, Paris, Lagatta, Antonio, Cancellieri, Giovanni
Médium: Journal Article
Jazyk:angličtina
Vydáno: Ireland Elsevier Ireland Ltd 01.08.2004
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ISSN:0169-2607, 1872-7565
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Abstract Independent component analysis (ICA) was used for the processing of cardiological signals obtained by means of fetal magnetocardiography (fMCG), a technique allowing the non-invasive recording of the weak magnetic field variations associated to the electrical activity of the fetal heart. Purpose of the present work was to verify whether a computational-light ICA algorithm (FastICA), tailored to the characteristics of fMCG, could reconstruct reliable signals of the fetal cardiac activity during the last gestational trimester, when good electrophysiological traces are difficult to obtain although being extremely important for clinical diagnosis of severe fetal dysrhythmias. Several combinations of input recordings and output components were examined in order to assess the best configuration to successfully use FastICA. The reconstructed traces were compared with those obtained with deterministic techniques already used for this purpose, and they showed to be stable and reliable, unaffected by overlapped maternal and fetal beats and suitable for clinical applications.
AbstractList Independent component analysis (ICA) was used for the processing of cardiological signals obtained by means of fetal magnetocardiography (fMCG), a technique allowing the non-invasive recording of the weak magnetic field variations associated to the electrical activity of the fetal heart. Purpose of the present work was to verify whether a computational-light ICA algorithm (FastICA), tailored to the characteristics of fMCG, could reconstruct reliable signals of the fetal cardiac activity during the last gestational trimester, when good electrophysiological traces are difficult to obtain although being extremely important for clinical diagnosis of severe fetal dysrhythmias. Several combinations of input recordings and output components were examined in order to assess the best configuration to successfully use FastICA. The reconstructed traces were compared with those obtained with deterministic techniques already used for this purpose, and they showed to be stable and reliable, unaffected by overlapped maternal and fetal beats and suitable for clinical applications.
Independent component analysis (ICA) was used for the processing of cardiological signals obtained by means of fetal magnetocardiography (fMCG), a technique allowing the non-invasive recording of the weak magnetic field variations associated to the electrical activity of the fetal heart. Purpose of the present work was to verify whether a computational-light ICA algorithm (FastICA), tailored to the characteristics of fMCG, could reconstruct reliable signals of the fetal cardiac activity during the last gestational trimester, when good electrophysiological traces are difficult to obtain although being extremely important for clinical diagnosis of severe fetal dysrhythmias. Several combinations of input recordings and output components were examined in order to assess the best configuration to successfully use FastICA. The reconstructed traces were compared with those obtained with deterministic techniques already used for this purpose, and they showed to be stable and reliable, unaffected by overlapp
Author Mantini, Dante
Comani, Silvia
Cancellieri, Giovanni
Lagatta, Antonio
Pennesi, Paris
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  surname: Mantini
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  givenname: Paris
  surname: Pennesi
  fullname: Pennesi, Paris
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  givenname: Antonio
  surname: Lagatta
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  givenname: Giovanni
  surname: Cancellieri
  fullname: Cancellieri, Giovanni
  organization: Department of Electronics, Artificial Intelligence and Telecommunications, Marche Polytechnic University, Ancona, Italy
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Issue 2
Keywords Data retrieval
Independent component analysis (ICA)
Fetal magnetocardiography (fMCG)
Fetal cardiac monitoring
Fetal signal reconstruction
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References_xml – reference: S. Amari, A. Cichocki, H.H. Yang, A new learning algorithm for blind signal separation, in:G. Tesauro, D.S. Touretzky, T.K. Leen (Eds.), Advances in Neural Information Processing Systems, vol. 8, The MIT Press, Cambridge MA, 1996, pp. 757–763.
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Snippet Independent component analysis (ICA) was used for the processing of cardiological signals obtained by means of fetal magnetocardiography (fMCG), a technique...
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StartPage 163
SubjectTerms Algorithms
Data retrieval
Electrophysiology
Fetal cardiac monitoring
Fetal magnetocardiography (fMCG)
Fetal signal reconstruction
Fetus - physiology
Heart - physiology
Humans
Independent component analysis (ICA)
Title Independent component analysis: fetal signal reconstruction from magnetocardiographic recordings
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https://dx.doi.org/10.1016/j.cmpb.2003.12.005
https://www.ncbi.nlm.nih.gov/pubmed/15212859
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