The Cardiodynamicsgram Based Early Detection of Myocardial Ischemia Using the Lempel-Ziv Complexity

Background: Electrocardiogram (ECG) is a routine method for detecting myocardial ischemia in clinical practice, but more than half of ECGs are without specific ischemic changes. Cardiodynamicsgram (CDG) is an effective method to detect ischemia with non-diagnostic ECG. The Lyapunov exponent (LYE) an...

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Main Authors: Qinghua Sun, Qian Wang, Bing Ji, Weiming Wu, Weiyi Huang, Cong Wang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9260193/
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spelling doaj-3846e94fe30a473099dbd0a40e9f202b2021-03-30T03:56:51ZengIEEEIEEE Access2169-35362020-01-01820789420790410.1109/ACCESS.2020.30382109260193The Cardiodynamicsgram Based Early Detection of Myocardial Ischemia Using the Lempel-Ziv ComplexityQinghua Sun0https://orcid.org/0000-0003-3908-307XQian Wang1Bing Ji2https://orcid.org/0000-0003-1326-4120Weiming Wu3Weiyi Huang4Cong Wang5https://orcid.org/0000-0002-5601-2145School of Automation and Engineering, South China University of Technology, Guangzhou, ChinaSchool of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, ChinaCenter for Intelligent Medical Engineering, School of Control Science and Engineering, Shandong University, Jinan, ChinaCenter for Intelligent Medical Engineering, School of Control Science and Engineering, Shandong University, Jinan, ChinaGuangdong Province Hydropower Hospital, Guangzhou, ChinaCenter for Intelligent Medical Engineering, School of Control Science and Engineering, Shandong University, Jinan, ChinaBackground: Electrocardiogram (ECG) is a routine method for detecting myocardial ischemia in clinical practice, but more than half of ECGs are without specific ischemic changes. Cardiodynamicsgram (CDG) is an effective method to detect ischemia with non-diagnostic ECG. The Lyapunov exponent (LYE) and the Fourier transform coefficient are combined to characterize the spatial and temporal features of CDG. However, in some cases, the Lyapunov exponent does not accurately enough describe the degree of irregular morphology of CDG for ischemic patients. In this context, this study aims to improve the characterization of CDG using the Lempel-Ziv (LZ) complexity instead of the Lyapunov exponent. Methods: The cardiodynamics information inside ECG is extracted via deterministic learning from the ST-T segments of ECG and then the CDG is generated by plotting the extracted three-dimensional cardiodynamics information. The Lyapunov exponent and LZ complexity are calculated from CDG and coupled with the Fourier transform coefficient respectively to construct the LYE model and LZ model for detecting myocardial ischemia. Results: 393 subjects presenting non-diagnostic ECG are enrolled in the study. 312 of them are ischemic patients selected as the myocardial ischemia group, and the other 81 non-ischemic subjects are selected as the healthy control group. The average sensitivity, specificity, and accuracy of the LYE model and the LZ model are 90.7% vs 93.4%, 86.4% vs 86.8%, and 89.0% vs 90.8%, respectively. Meanwhile, the proposed method achieves better performance on the PTB database than most of the previous studies in detecting ischemia or infarction. Conclusion: The results indicate that LZ complexity can accurately characterize the cases that cannot be accurately depicted by Lyapunov exponent, and the corresponding model is more accurate for the early detection of myocardial ischemia.https://ieeexplore.ieee.org/document/9260193/CardiodynamicsgramLempel-Ziv complexitymyocardial ischemiadeterministic learning
collection DOAJ
language English
format Article
sources DOAJ
author Qinghua Sun
Qian Wang
Bing Ji
Weiming Wu
Weiyi Huang
Cong Wang
spellingShingle Qinghua Sun
Qian Wang
Bing Ji
Weiming Wu
Weiyi Huang
Cong Wang
The Cardiodynamicsgram Based Early Detection of Myocardial Ischemia Using the Lempel-Ziv Complexity
IEEE Access
Cardiodynamicsgram
Lempel-Ziv complexity
myocardial ischemia
deterministic learning
author_facet Qinghua Sun
Qian Wang
Bing Ji
Weiming Wu
Weiyi Huang
Cong Wang
author_sort Qinghua Sun
title The Cardiodynamicsgram Based Early Detection of Myocardial Ischemia Using the Lempel-Ziv Complexity
title_short The Cardiodynamicsgram Based Early Detection of Myocardial Ischemia Using the Lempel-Ziv Complexity
title_full The Cardiodynamicsgram Based Early Detection of Myocardial Ischemia Using the Lempel-Ziv Complexity
title_fullStr The Cardiodynamicsgram Based Early Detection of Myocardial Ischemia Using the Lempel-Ziv Complexity
title_full_unstemmed The Cardiodynamicsgram Based Early Detection of Myocardial Ischemia Using the Lempel-Ziv Complexity
title_sort cardiodynamicsgram based early detection of myocardial ischemia using the lempel-ziv complexity
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description Background: Electrocardiogram (ECG) is a routine method for detecting myocardial ischemia in clinical practice, but more than half of ECGs are without specific ischemic changes. Cardiodynamicsgram (CDG) is an effective method to detect ischemia with non-diagnostic ECG. The Lyapunov exponent (LYE) and the Fourier transform coefficient are combined to characterize the spatial and temporal features of CDG. However, in some cases, the Lyapunov exponent does not accurately enough describe the degree of irregular morphology of CDG for ischemic patients. In this context, this study aims to improve the characterization of CDG using the Lempel-Ziv (LZ) complexity instead of the Lyapunov exponent. Methods: The cardiodynamics information inside ECG is extracted via deterministic learning from the ST-T segments of ECG and then the CDG is generated by plotting the extracted three-dimensional cardiodynamics information. The Lyapunov exponent and LZ complexity are calculated from CDG and coupled with the Fourier transform coefficient respectively to construct the LYE model and LZ model for detecting myocardial ischemia. Results: 393 subjects presenting non-diagnostic ECG are enrolled in the study. 312 of them are ischemic patients selected as the myocardial ischemia group, and the other 81 non-ischemic subjects are selected as the healthy control group. The average sensitivity, specificity, and accuracy of the LYE model and the LZ model are 90.7% vs 93.4%, 86.4% vs 86.8%, and 89.0% vs 90.8%, respectively. Meanwhile, the proposed method achieves better performance on the PTB database than most of the previous studies in detecting ischemia or infarction. Conclusion: The results indicate that LZ complexity can accurately characterize the cases that cannot be accurately depicted by Lyapunov exponent, and the corresponding model is more accurate for the early detection of myocardial ischemia.
topic Cardiodynamicsgram
Lempel-Ziv complexity
myocardial ischemia
deterministic learning
url https://ieeexplore.ieee.org/document/9260193/
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