Time-frequency characterization of tri-axial accelerometer data for fetal movement detection

M. S. Khlif*, B. Boashash, S. Layeghy, T. Ben-Jabeur, M. Mesbah, C. East, P. Colditz

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)

Abstract

Monitoring fetal wellbeing is a significant problem in modern obstetrics. Clinicians have become increasingly aware of the link between fetal activity and its well-being. Using data acquired by accelerometry sensors, we use TFDs such as the spectrogram and modified B distribution (MBD) to characterize fetal movements in the time-frequency (TF) domain. This paper reports a fetal activity detection method based on the root-mean-square (RMS) of time series and evaluates its performance against real-time ultrasound imaging, taken as the gold standard. The evaluation showed better performance with the RMS-based detector as compared to maternal perception. The evaluation also showed that the detector performance is age-dependent and that fetal movement is characterized by different TF morphology. Time-frequency distributions (TFDs) with better resolution such as MBD are investigated for TF-based techniques for the detection of fetal movements.

Original languageEnglish
Title of host publicationIEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2011
Pages466-471
Number of pages6
DOIs
Publication statusPublished - 2011
Event11th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2011 - Bilbao, Spain
Duration: Dec 14 2011Dec 17 2011

Publication series

NameIEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2011

Other

Other11th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2011
Country/TerritorySpain
CityBilbao
Period12/14/1112/17/11

Keywords

  • Accelerometer
  • Spectrogram
  • detection
  • fetal movement
  • modified B distribution
  • quadratic TFDs
  • time-frequency analysis

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

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