Empirical mode decomposition applied for non-invasive electrohysterograhic signals denoising

Annu Int Conf IEEE Eng Med Biol Soc. 2015:2015:4134-7. doi: 10.1109/EMBC.2015.7319304.

Abstract

The electrical activity of the uterus, i.e. the electrohysterogram (EHG), is one of the most prominent tool for preterm labour. There is no standard acquisition set up and often the EHG is corrupted with different types of noise: maternal and fetal electrocardiogram (mECG, fECG), electrical activity of the skeletal muscles, movement artifacts, power line interference (PLI) etc. Moreover, some of these noises overlap in frequency domain with the EHG. Thus, simple linear filtering approaches are not adequate. In this paper the empirical mode decomposition (EMD), a simple and data driven method, is proposed for EHG denoising. The method is evaluated on simulated data having different signal to noise ratios (SNRs) obtaining promising results.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Artifacts
  • Electrocardiography / methods
  • Electromyography / methods*
  • Female
  • Fetal Monitoring / methods
  • Humans
  • Muscle, Skeletal / physiology
  • Obstetric Labor, Premature / diagnosis
  • Pregnancy
  • Signal Processing, Computer-Assisted*
  • Signal-To-Noise Ratio
  • Uterine Monitoring / methods*
  • Uterus / physiology