Effects of COVID 19 on Electrocardiographic Parameters: Healthy ECGs vs COVID 19 ECGs

Abstract

The coronavirus disease (COVID-19) started in 2019 and became a pandemic by infecting many people all over the world. It is known that COVID-19 affects the heart as well as the respiratory system, and the changes it causes on the electrical activity of the heart are among the common research topics of recent studies. The electrical activity of the heart is measured by Electrocardiography (ECG). While some ECG devices give the ECG signal directly as numeric vector format, others draw the signal on paper or give results as an image. ECG images drawn on paper are usually only visually examined by the doctor, and detailed analysis is mostly attempted with low-accuracy machine learning methods. In this study, a new approach that converts ECG images drawn on paper into signals is proposed. The proposed approach was used to convert the ECG images recorded from COVID-19 and healthy people in an open source ECG image database into signals, and the obtained ECG signals were analysed in detail with signal processing methods and compared statistically between COVID-19 and healthy group and with similar studies in the literature. Results showed that, ECG characteristics were significantly changed with the COVID-19.

Keywords

• COVID-19
• Electrocardiography (ECG)
• Feature Extraction
• image-to-signal conversion