Inverse ECG modeling with spatiotemporal regularization for the characterization of myocardial infarctions

Bing Yao, Rui Zhu, Hui Yang

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

Abstract

Myocardial infarctions (MIs) pose a significant risk to human health. Accurate identification and characterization of MI's are essential for the effective medical treatment. Traditional methods such as the standard 12-lead ECG identify MIs with the electrocardiogram (ECG) recorded on the body surface, which consider little about anatomical details of the human body. These methods are limited in the ability to map back the actual electrical activities of the heart and further characterize MIs. Inverse ECG (iECG) methods were proposed to trace the distribution of electric potentials on the heart surface and characterize MIs. However, these methods do not account for the spatiotemporal behaviors of the potential distributions, because the electric potentials are distributed in the complex geometry and varying dynamically over time. In this paper, a novel iECG model with spatiotemporal regularization is developed to image and characterize MIs. We solve the iECG problem with the method of spatiotemporal regularization and reconstruct electric potentials on the heart surface. Furthermore, we group the estimated heart potentials into healthy and infarct clusters with a wavelet-clustering method. Experimental results show that the proposed method effectively solves the iECG problem and better characterizes MIs compared with existing methods.

Original languageEnglish (US)
Title of host publication2018 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages120-123
Number of pages4
Volume2018-January
ISBN (Electronic)9781538624050
DOIs
StatePublished - Apr 6 2018
Event2018 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2018 - Las Vegas, United States
Duration: Mar 4 2018Mar 7 2018

Other

Other2018 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2018
CountryUnited States
CityLas Vegas
Period3/4/183/7/18

Fingerprint

Electrocardiography
Myocardial Infarction
Electric potential
Aptitude
Lead
Human Body
Health
Cluster Analysis
Geometry

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Biomedical Engineering
  • Health Informatics

Cite this

Yao, B., Zhu, R., & Yang, H. (2018). Inverse ECG modeling with spatiotemporal regularization for the characterization of myocardial infarctions. In 2018 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2018 (Vol. 2018-January, pp. 120-123). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BHI.2018.8333384
Yao, Bing ; Zhu, Rui ; Yang, Hui. / Inverse ECG modeling with spatiotemporal regularization for the characterization of myocardial infarctions. 2018 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2018. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. pp. 120-123
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Yao, B, Zhu, R & Yang, H 2018, Inverse ECG modeling with spatiotemporal regularization for the characterization of myocardial infarctions. in 2018 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2018. vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 120-123, 2018 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2018, Las Vegas, United States, 3/4/18. https://doi.org/10.1109/BHI.2018.8333384

Inverse ECG modeling with spatiotemporal regularization for the characterization of myocardial infarctions. / Yao, Bing; Zhu, Rui; Yang, Hui.

2018 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2018. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. p. 120-123.

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

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Yao B, Zhu R, Yang H. Inverse ECG modeling with spatiotemporal regularization for the characterization of myocardial infarctions. In 2018 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2018. Vol. 2018-January. Institute of Electrical and Electronics Engineers Inc. 2018. p. 120-123 https://doi.org/10.1109/BHI.2018.8333384