Compressive-sensing-based multidimensional Doppler signal analysis for fetal activity monitoring

Fetal activity monitoring is an important part of monitoring at-risk pregnancies and labor. Fetal activity parameters (FAP) consist of fetal heart rate (FHR), fetal movements (FM) rate, fetal tone, fetal breathing (FB) and movement. FAP monitoring is to date an open challenge for mainly two reasons. First, the estimation of FAP is highly time consuming and thus cannot be used routinely. Second, part of FAP such as FM estimation is sometimes subjective (mothers are asked to count the fetal movements) and inaccurate. For this purpose, we developed a 2MHz pulsed wave ultrasound Doppler system, consisting of 12 transducers with 5 adjustable gates. The Doppler signals were sampled at 1KHz. Several recent papers have shown the accuracy of our system. However, its counterpart is the huge number of signals necessary to estimate the FAP. Specifically, each millisecond, 60 Doppler samples are acquired. In order to reduce the volume of the acquired data and to accelerate the FAP estimation rate, we propose herein to investigate the interest of compressive sensing (CS) techniques to our application.

[1]  Yonina C. Eldar,et al.  Structured Compressed Sensing: From Theory to Applications , 2011, IEEE Transactions on Signal Processing.

[2]  E.J. Candes,et al.  An Introduction To Compressive Sampling , 2008, IEEE Signal Processing Magazine.

[3]  Stephen P. Boyd,et al.  Enhancing Sparsity by Reweighted ℓ1 Minimization , 2007, 0711.1612.

[4]  Emmanuel J. Candès,et al.  Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information , 2004, IEEE Transactions on Information Theory.

[5]  D. Kouame,et al.  High resolution processing techniques for ultrasound Doppler velocimetry in the presence of colored noise. I. Nonstationary methods , 2003, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[6]  Denis Friboulet,et al.  Compressive sensing in medical ultrasound , 2012, 2012 IEEE International Ultrasonics Symposium.

[7]  Jean-Marc Girault,et al.  Robust estimation of fetal heart rate from US Doppler signals , 2010 .

[8]  Toshiyuki Shimizu,et al.  Automated Fetal Breathing Movement Detection from Infernal Small Displacement Measurement - Die automatische Ermittlung fötaler Atembewegungen durch die Messung kleiner interner Verschiebungen , 1996 .

[9]  B Karlsson,et al.  The DopFet system: a new ultrasonic Doppler system for monitoring and characterization of fetal movement. , 2000, Ultrasound in medicine & biology.

[10]  MRCOG Examination,et al.  Royal College of Obstetricians and Gynaecologists , 1952, The Journal of obstetrics and gynaecology of the British Empire.

[11]  Adrian Basarab,et al.  Frequency Domain Compressive Sampling for Ultrasound Imaging , 2012 .

[12]  N Shinozuka,et al.  Automated fetal breathing movement detection from internal small displacement measurement. , 1996, Biomedizinische Technik. Biomedical engineering.

[13]  D. Kouame,et al.  Empirical mode decomposition (EMD) for multi-gate, multi-transducer ultrasound Doppler fetal heart monitoring , 2005, Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005..

[14]  L Pourcelot,et al.  Effects of fetal and maternal breathing on the ultrasonic Doppler signal due to fetal heart movement. , 2000, European journal of ultrasound : official journal of the European Federation of Societies for Ultrasound in Medicine and Biology.

[15]  L. Platt,et al.  Antepartum fetal evaluation: development of a fetal biophysical profile. , 1980, American journal of obstetrics and gynecology.

[16]  Solange Akselrod,et al.  An estimate of fetal autonomic state by time-frequency analysis of fetal heart rate variability. , 2007, Journal of applied physiology.

[17]  Sulieman M. S. Zobly,et al.  Compressed sensing: Doppler ultrasound signal recovery by using non-uniform sampling & random sampling , 2011, NRSC 2011.

[18]  D. Kouamé,et al.  Support-vector-machines-based multidimensional signal classification for fetal activity characterization , 2011, Medical Imaging.

[19]  J. Jensen.  Estimation of Blood Velocities Using Ultrasound: A Signal Processing Approach , 1996 .

[20]  Denis Kouame,et al.  New Estimators and Guidelines for Better Use of Fetal Heart Rate Estimators with Doppler Ultrasound Devices , 2014, Comput. Math. Methods Medicine.