• Title, Summary, Keyword: MCG topography

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Magnetocardiogram Topography with Automatic Artifact Correction using Principal Component Analysis and Artificial Neural Network

  • Ahn C.B.;Kim T.H.;Park H.C.;Oh S.J.
    • Journal of Biomedical Engineering Research
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    • v.27 no.2
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    • pp.59-63
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    • 2006
  • Magnetocardiogram (MCG) topography is a useful diagnostic technique that employs multi-channel magnetocardiograms. Measurement of artifact-free MCG signals is essenctial to obtain MCG topography or map for a diagnosis of human heart. Principal component analysis (PCA) combined with an artificial neural network (ANN) is proposed to remove a pulse-type artifact in the MCG signals. The algorithm is composed of a PCA module which decomposes the obtained signal into its principal components, followed by an ANN module for the classification of the components automatically. In the experiments with volunteer subjects, 97% of the decisions that were made by the ANN were identical to those by the human experts. Using the proposed technique, the MCG topography was successfully obtained without the artifact.