Passive detection of accelerometer-recorded fetal movements using a time–frequency signal processing approach

Boashash, B., Khlif, M. S., Ben-Jabeur, T., East, Christine E. and Colditz, P. B. (2013) Passive detection of accelerometer-recorded fetal movements using a time–frequency signal processing approach. Digital Signal Processing, 25 1: 134-155. doi:10.1016/j.dsp.2013.10.002

Author Boashash, B.
Khlif, M. S.
Ben-Jabeur, T.
East, Christine E.
Colditz, P. B.
Title Passive detection of accelerometer-recorded fetal movements using a time–frequency signal processing approach
Journal name Digital Signal Processing   Check publisher's open access policy
ISSN 1051-2004
Publication date 2013-10-09
Year available 2013
Sub-type Article (original research)
DOI 10.1016/j.dsp.2013.10.002
Open Access Status
Volume 25
Issue 1
Start page 134
End page 155
Total pages 22
Place of publication Maryland Heights, MO, United States
Publisher Academic Press
Language eng
Subject 1711 Signal Processing
2208 Electrical and Electronic Engineering
Abstract This paper describes a multi-sensor fetal movement (FetMov) detection system based on a time–frequency (TF) signal processing approach. Fetal motor activity is clinically useful as a core aspect of fetal screening for well-being to reduce the current high incidence of fetal deaths in the world. FetMov are present in early gestation but become more complex and sustained as the fetus progresses through gestation. A decrease in FetMov is an important element to consider for the detection of fetal compromise. Current methods of FetMov detection include maternal perception, which is known to be inaccurate, and ultrasound imaging which is intrusive and costly. An alternative passive method for the detection of FetMov uses solid-state accelerometers, which are safe and inexpensive. This paper describes a digital signal processing (DSP) based experimental approach to the detection of FetMov from recorded accelerometer signals. The paper provides an overview of the significant measurement and signal processing challenges, followed by an approach that uses quadratic time–frequency distributions (TFDs) to appropriately deal with the non-stationary nature of the signals. The paper then describes a proof-of-concept with a solution consisting of a detection method that includes (1) a new experimental set-up, (2) an improved data acquisition procedure, and (3) a TF approach for the detection of FetMov including TF matching pursuit (TFMP) decomposition and TF matched filter (TFMF) based on high-resolution quadratic TFDs. Detailed suggestions for further refinement are provided with preliminary results to establish feasibility, and considerations for application to clinical practice are reviewed.
Keyword Accelerometer
Matched filter
Matching pursuit
Time–frequency analysis
Newborn health outcomes
Q-Index Code C1
Q-Index Status Confirmed Code
Grant ID NPRP 096262243
Institutional Status UQ
Additional Notes Published online ahead of print 9 October 2013.

Document type: Journal Article
Sub-type: Article (original research)
Collections: UQ Centre for Clinical Research Publications
Official 2014 Collection
School of Medicine Publications
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Citation counts: TR Web of Science Citation Count  Cited 9 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 14 times in Scopus Article | Citations
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Created: Wed, 11 Dec 2013, 21:46:30 EST by Vicki Percival on behalf of School of Nursing, Midwifery and Social Work