Electrode Selection for Noninvasive Fetal Electrocardiogram Extraction using Mutual Information Criteria

Sameni, R.;Vrins, Frédéric;Parmentier, F.;Vigneron, Vincent;Hérail, C.;et.al.
(2006) 26th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2006) — Location: CNRS (Paris/France) (8.July.2006)

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Authors
  • Sameni, R.Sharif University of Technology - Tehran
    Author
  • Vrins, Frédéricorcid-logoUCLouvain
    Author
  • Parmentier, F.UCLouvain
    Author
  • Vigneron, VincentCNRS
    Author
  • Verleysen, MichelUCLouvain
    Author
  • Hérail, C.CNRS
    Author
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Abstract
Blind source separation (BSS) techniques have revealed to be promising approaches for the noninvasive extraction of fetal cardiac signals from maternal abdominal recordings. From previous studies, it is now believed that a carefully selected array of electrodes well-placed over the abdomen of a pregnant woman contains the required ‘information’ for BSS, to extract the complete fetal components. Based on this idea, previous works have involved array recording systems and sensor selection strategies based on the Mutual Information (MI) criterion. In this paper the previous works have been extended, by considering the 3-dimensional aspects of the cardiac electrical activity. The proposed method has been tested on simulated and real maternal abdominal recordings. The results show that the new sensor selection strategy together with the MI criterion, can be effectively used to select the channels containing the most ‘information’ concerning the fetal ECG components from an array of 72 recordings. The method is hence believed to be useful for the selection of the most informative channels in online applications, considering the different fetal positions and movements.
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Sameni, R., Vrins, F., Parmentier, F., Vigneron, V., Verleysen, M., Jutten, C., Shamsollahi, M. B., & Hérail, C. (2006). Electrode Selection for Noninvasive Fetal Electrocardiogram Extraction using Mutual Information Criteria. Proceedings of MaxEnt 2006. 26th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2006), CNRS (Paris/France). https://hdl.handle.net/2078.5/254049