Fetal ECG Separation Using Non-parametric ICA Algorithm


IEEE 16th Signal Processing and Communications Applications Conference, Aydın, Turkey, 20 - 22 April 2008, pp.164-167 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu.2008.4632578
  • City: Aydın
  • Country: Turkey
  • Page Numbers: pp.164-167
  • Karadeniz Technical University Affiliated: Yes


Performances of former indepedent component analysis (ICA) algorithms depend on the true probability density function of each source, but in practice these densities are unknown. To handle this problem Non-parametric and parametric ICA algorithms have been developed. In this paper it is studied the separation of maternal and fetal heart beats from electrocardiogram (ECG) recordings based on FastICA and Non-parametric ICA algorithms and differences of algorithms are investigated on ECG signal. The most important two properties of Non-parametric algorithm are it's performanse is not dependent upon prior assumptions about the source probability distribution and it is also capable of accurately and efficiently estimating unmixing matrix, and which doesn't require the selection of any tuning parameters. The simulations demonstrate that Non-parametric ICA algorithm and FastICA algorithm can accurately separate fetal and maternal ECG signals.