Classification of Cardiac Signals in Order to Diagnose Myocardial Infarction based on Extraction of Morphological Features from Spatio-Temporal Patterns of Vectorcardiogram Signals

Document Type : Original Article (s)

Authors

1 MSc Student, Department of Biomedical Engineering, School of Advanced Medical Technology, Isfahan University of Medical Sciences, Isfahan, Iran

2 Professor, Department of Biomedical Engineering, School of Advanced Medical Technology AND Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan, Iran

3 Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran

4 Assistant Professor, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran

5 Cardiologist, Echocardiography Fellowship, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran

Abstract

Background: One of the most common cardiovascular diseases (CVDs) in the world is myocardial infarction (MI). By analyzing electrocardiogram and vectorcardiography (VCG) signals, it is possible to identify and characterize heart diseases such as MI. One of the new methods of detection is the use of spatio-temporal parameters of VCG signals. This study aimed to correctly distinguish healthy signals from patients, achieve acceptable accuracy, and show the benefits of VCG and its application as a method to cover the shortcoming of electrocardiography.Methods: In this study, in addition to applying electrocardiogram signals in the time domain, spatio-temporal patterns of VCG signals were used to identify 80 patients with MI, and differentiate them from 80 healthy individuals.Findings: When combining the 12-lead electrocardiography (ECG) and the 3-lead VCG features applied to the Feedforward Neural Network classifier input, an accuracy of 91.2%, specificity of 92.6%, and specificity of 90% were obtained. The results were in higher values than when applied separately.Conclusion: The observations indicate that combined ECG and VCG methods can be effective in distinguishing MI cases from healthy cases. It is hoped that this method may be useful in the clinical evaluation and heart failure diagnosis.

Keywords

References

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Journal of Isfahan Medical School
Volume 37, Issue 548 - Serial Number 548
September and October 2020
Pages 1192-1199

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History

  • Receive Date: 20 October 2019
  • Revise Date: 27 May 2024
  • Accept Date: 06 April 2022

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