Hypertrophic cardiomyopathy (HCM) and hypertensive heart disease (HHD) diagnosis using echocardiography and electrocardiography

ABSTRACT

Echocardiography and electrocardiogram (ECG) are the primary tools used by cardiologists to diagnose cardiovascular heart diseases. Contrary to the critical role of combining the echocardiography and ECG information in clinical examinations, to our knowledge, no study has considered this to classify heart diseases. Left ventricular hypertrophy (LVH) is caused by a variety of origins such as hypertrophic cardiomyopathy (HCM) and hypertensive heart disease (HHD). Differentiating HCM and HHD is challenging . We proposed an HCM and HHD patient classifier to use ECG and echocardiography information. Longitudinal strain and strain rate from echocardiography frames and amplitude and temporal features from ECG signals, are extracted. To eliminate incompetent features, Fisher’s discrimination ratio (FDR), information gain, and Relief-F weights are used. Finally, support vector machine (SVM) and K-nearest neighbours classifiers are used to classify the normal, HCM, and HHD subjects. The results on 30 subjects show that the best classification refers to SVM classifier using five selected features from ECG and echocardiography information using FDR. The precision, sensitivity, and F-measure are 97.62, 93.33 and 95.43%, respectively. According to the results, the combination of echocardiography and ECG information leads to diagnosis improvement compared to the classification based on separated information of ECG and echocardiography.

KEYWORDS:

• Echocardiography
• ecg
• hcm
• hhd
• classification

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Yasna Forghani

Yasna Forghanireceived a B.S. degree in electrical engineering from the Shahid Bahonar University of Kerman, Kerman, Iran, in 2014, an M.Sc. degree in medical engineering from Iran University of Science and Technology, Tehran, Iran, in 2018. Her research interests include medical image processing and medical signal processing.

Hamid Behnam

Hamid Behnam received the B.S. degree in electrical engineering from Iran University of Science and Technology, Tehran, Iran, in 1988, the M.S. degree in medical engineering from Sharif University of Technology, Tehran, Iran, in 1992, and the Ph.D. degree in applied electronics from Tokyo Institute of Technology, Tokyo, Japan, in 1998. Since 1998, he has been a Researcher with Iran Research Organization for Science and Technology, Tehran, Iran, and from 2004, he has been a Faculty Member with Iran University of Science and Technology (IUST), Tehran, Iran. Currently, he is an Associate Professor of Biomedical Engineering with IUST. His research interests include ultrasound in medicine, medical image processing, and medical signal processing.

Maryam Shojaeifard

Maryam Shojaeifard received a Medical degree from Yazd University of Medical Sciences, Yazd, Iran, in 2000. She was Resident of Cardiology with Rajaei Cardiovascular Medical and Research center, Iran University, Tehran, Iran, from 2003 to 2007, and completed fellowships in Echocardiography at Rajaei Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran, from 2008 to 2010. Since 2010, she has been working as a Professor of Cardiology with the Department of Echocardiography, Shaheed Rajaei Cardiovascular Medical and Research Center, Iran University. Her research interests include basic and clinical echocardiography.