Automated Estimation of Fetal Cardiac Timing Events From Doppler Ultrasound Signal Using Hybrid Models
Faezeh Marzbanrad, Yoshitaka Kimura, Kiyoe Funamoto, Rika Sugibayashi, Miyuki Endo, Takuya Ito, Marimuthu Palaniswami, Ahsan H Khandoker
IEEE Journal of Biomedical and Health Informatics | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | Published : 2014
In this paper, a new noninvasive method is proposed for automated estimation of fetal cardiac intervals from Doppler Ultrasound (DUS) signal. This method is based on a novel combination of empirical mode decomposition (EMD) and hybrid support vector machines-hidden Markov models (SVM/HMM). EMD was used for feature extraction by decomposing the DUS signal into different components (IMFs), one of which is linked to the cardiac valve motions, i.e. opening (o) and closing (c) of the Aortic (A) and Mitral (M) valves. The noninvasive fetal electrocardiogram (fECG) was used as a reference for the segmentation of the IMF into cardiac cycles. The hybrid SVM/HMM was then applied to identify the cardia..View full abstract
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Awarded by Australian Research Council
This work was supported by an Australian Research Council Linkage Grant (LP100200184) with Tohoku University and Atom Medical Corporation in Japan.