Denoising of the fetal heart rate signal with non-linear filtering of the wavelet transform maxima

S. Papadimitriou, D. Gatzounas, V. Papadopoulos, V. Tzigounis, A. Bezerianos

Research output: Contribution to journalArticlepeer-review

Abstract

The fetal heart rate (FHR) signal provides valuable information for fetal development and well-being. However, the FHR traces derived from present-day ultrasound cardiotocographs are not of the desired quality. The paper applies the wavelet transform (WT) in order to denoise effectively the FHR signal. The denoising procedure analyses the evolution of the WT maxima across scales. The singularities of the signal create wavelet maxima with different properties from those of the induced noise. Since it is difficult to formulate precise rules that distinguish between the wavelet maxima of the FHR signal from those of the noise we have trained a neural network for this classification task. The neural network draws out successfully the noise induced wavelet maxima. An improved FHR signal can be obtained from the coarser wavelet approximation signal component and the filtered wavelet maxima by means of the inverse dyadic wavelet transform. Also, feature extraction and processing algorithms can be defined on the denoised wavelet coefficients (instead of on the original signal).

Original languageEnglish (US)
Pages (from-to)177-192
Number of pages16
JournalInternational Journal of Medical Informatics
Volume44
Issue number3
DOIs
StatePublished - May 1997

Keywords

  • Denoising
  • Doppler ultrasound
  • Fetal heart
  • Neural networks
  • Signal-noise-ratio
  • Wavelet transforms

ASJC Scopus subject areas

  • Health Informatics

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