A multi-dimensional Hidden Markov Model approach to automated identification of fetal cardiac valve motion

Faezeh Marzbanrad; Ahsan H. Khandoker; Miyuki Endo; Yoshitaka Kimura; Marimuthu Palaniswami

doi:10.1109/EMBC.2014.6943978

A multi-dimensional Hidden Markov Model approach to automated identification of fetal cardiac valve motion

Faezeh Marzbanrad, Ahsan H. Khandoker, Miyuki Endo, Yoshitaka Kimura, Marimuthu Palaniswami

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

3 Citations (Scopus)

Abstract

Fetal cardiac assessment techniques are aimed to identify fetuses at risk of intrauterine compromise or death. Evaluation of the electromechanical coupling as a fundamental part of the fetal heart physiology, provides valuable information about the fetal wellbeing during pregnancy. It is based on the opening and closing time of the cardiac valves and the onset of the QRS complex of the fetal electrocardiogram (fECG). The focus of this paper is on the automated identification of the fetal cardiac valve opening and closing from Doppler Ultrasound signal and fECG as a reference. To this aim a novel combination of Emprical Mode Decomposition (EMD) and multi-dimensional Hidden Markov Models (MD-HMM) was employed which provided beat-to-beat estimation of cardiac valve event timings with improved precision (82.9%) compared to the one dimensional HMM (77.4%) and hybrid HMM-Suppeort Vector Machine (SVM) (79.8%) approaches.

Original language	English
Title of host publication	2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Editors	Jeff Duerk, Jim Ji
Place of Publication	Piscataway NJ USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	1885-1888
Number of pages	4
ISBN (Electronic)	9781424479290
ISBN (Print)	9781424479276
DOIs	https://doi.org/10.1109/EMBC.2014.6943978
Publication status	Published - 6 Nov 2014
Externally published	Yes
Event	International Conference of the IEEE Engineering in Medicine and Biology Society 2014 - Sheraton Chicago Hotel and Towers, Chicago, United States of America Duration: 26 Aug 2014 → 30 Aug 2014 Conference number: 36th https://ieeexplore-ieee-org.ezproxy.lib.monash.edu.au/xpl/conhome/6923026/proceeding (Proceedings) https://web.archive.org/web/20140331105330/http://embc.embs.org/2014/?page_id=120 (Website)

Conference

Conference	International Conference of the IEEE Engineering in Medicine and Biology Society 2014
Abbreviated title	EMBC 2014
Country/Territory	United States of America
City	Chicago
Period	26/08/14 → 30/08/14
Internet address	https://ieeexplore-ieee-org.ezproxy.lib.monash.edu.au/xpl/conhome/6923026/proceeding (Proceedings) https://web.archive.org/web/20140331105330/http://embc.embs.org/2014/?page_id=120 (Website)

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10.1109/EMBC.2014.6943978

Cite this

Marzbanrad, F., Khandoker, A. H., Endo, M., Kimura, Y., & Palaniswami, M. (2014). A multi-dimensional Hidden Markov Model approach to automated identification of fetal cardiac valve motion. In J. Duerk, & J. Ji (Eds.), 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 1885-1888). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/EMBC.2014.6943978

Marzbanrad, Faezeh ; Khandoker, Ahsan H. ; Endo, Miyuki et al. / A multi-dimensional Hidden Markov Model approach to automated identification of fetal cardiac valve motion. 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. editor / Jeff Duerk ; Jim Ji. Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2014. pp. 1885-1888

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abstract = "Fetal cardiac assessment techniques are aimed to identify fetuses at risk of intrauterine compromise or death. Evaluation of the electromechanical coupling as a fundamental part of the fetal heart physiology, provides valuable information about the fetal wellbeing during pregnancy. It is based on the opening and closing time of the cardiac valves and the onset of the QRS complex of the fetal electrocardiogram (fECG). The focus of this paper is on the automated identification of the fetal cardiac valve opening and closing from Doppler Ultrasound signal and fECG as a reference. To this aim a novel combination of Emprical Mode Decomposition (EMD) and multi-dimensional Hidden Markov Models (MD-HMM) was employed which provided beat-to-beat estimation of cardiac valve event timings with improved precision (82.9%) compared to the one dimensional HMM (77.4%) and hybrid HMM-Suppeort Vector Machine (SVM) (79.8%) approaches.",

author = "Faezeh Marzbanrad and Khandoker, {Ahsan H.} and Miyuki Endo and Yoshitaka Kimura and Marimuthu Palaniswami",

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doi = "10.1109/EMBC.2014.6943978",

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Marzbanrad, F, Khandoker, AH, Endo, M, Kimura, Y & Palaniswami, M 2014, A multi-dimensional Hidden Markov Model approach to automated identification of fetal cardiac valve motion. in J Duerk & J Ji (eds), 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, pp. 1885-1888, International Conference of the IEEE Engineering in Medicine and Biology Society 2014, Chicago, Illinois, United States of America, 26/08/14. https://doi.org/10.1109/EMBC.2014.6943978

A multi-dimensional Hidden Markov Model approach to automated identification of fetal cardiac valve motion. / Marzbanrad, Faezeh; Khandoker, Ahsan H.; Endo, Miyuki et al.
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. ed. / Jeff Duerk; Jim Ji. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 2014. p. 1885-1888.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

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AU - Khandoker, Ahsan H.

AU - Endo, Miyuki

AU - Kimura, Yoshitaka

AU - Palaniswami, Marimuthu

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AB - Fetal cardiac assessment techniques are aimed to identify fetuses at risk of intrauterine compromise or death. Evaluation of the electromechanical coupling as a fundamental part of the fetal heart physiology, provides valuable information about the fetal wellbeing during pregnancy. It is based on the opening and closing time of the cardiac valves and the onset of the QRS complex of the fetal electrocardiogram (fECG). The focus of this paper is on the automated identification of the fetal cardiac valve opening and closing from Doppler Ultrasound signal and fECG as a reference. To this aim a novel combination of Emprical Mode Decomposition (EMD) and multi-dimensional Hidden Markov Models (MD-HMM) was employed which provided beat-to-beat estimation of cardiac valve event timings with improved precision (82.9%) compared to the one dimensional HMM (77.4%) and hybrid HMM-Suppeort Vector Machine (SVM) (79.8%) approaches.

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ER -

Marzbanrad F, Khandoker AH, Endo M, Kimura Y, Palaniswami M. A multi-dimensional Hidden Markov Model approach to automated identification of fetal cardiac valve motion. In Duerk J, Ji J, editors, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. 2014. p. 1885-1888 doi: 10.1109/EMBC.2014.6943978

A multi-dimensional Hidden Markov Model approach to automated identification of fetal cardiac valve motion

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