Why the study?
Paper ECG images are typically examined visually or analyzed with low-accuracy machine learning, prompting a new method to convert ECG images into signals to study COVID-19 effects on cardiac electrical activity.
Does COVID-19 infection significantly alter ECG characteristics compared to healthy individuals when analyzed using a novel paper-to-signal conversion approach?
Does COVID-19 infection significantly alter ECG characteristics compared to healthy individuals when analyzed using a novel paper-to-signal conversion approach?
A novel paper-to-signal conversion approach demonstrates that COVID-19 significantly alters ECG characteristics compared to healthy individuals.
ECG differences in COVID-19 suggest possible cardiac involvement; leaves open prospective validation before any clinical application.
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.
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Yanık et al. (2024) studied this question.
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