Why the study?
It remains unclear if T wave inversion has clinical value in the ECG diagnosis of CAD, necessitating accurate ECG analysis using a right triangle hypotenuse method for T wave detection.
Does an algorithm based on the right triangle hypotenuse accurately detect T waves in ECG datasets?
Does an algorithm based on the right triangle hypotenuse accurately detect T waves in ECG datasets?
A novel algorithm utilizing the right triangle hypotenuse system shows promise for automated and accurate T wave detection in ECG signals.
Algorithm for T-wave detection yields promising results on benchmark datasets; leaves open clinical validation in patient cohorts.
The T wave is the most important portion of the Electrocardiogram (ECG) since it detects abnormalities. Various ECG leads produce different T waves. In research, various waveform morphologies may present as an indication of benign or clinically significant injury or insult to the myocardium. The frequency of the QT interval and the shape of the electrocardiographic T-wave are both signs of abnormal ventricular repolarization, according to many scientific and clinical investigations. Furthermore, it is still unclear if T wave inversion has any clinical value in the ECG diagnosis of coronary artery disease (CAD). To obtain the accurate results of ECG of patients with CAD, this study aims to analyze the correlation using the right triangle hypotenuse for T wave detection. In this paper, we have proposed an algorithm for detecting T waves in ECG for all types of leads. We use the right triangle hypotenuse to determine T wave start and end points. Moreover, we determine the T wave upslope or downslope, as well as up or down peak value. An extensive experiment is performed on 53 datasets, including 18 databases from the MIT-BIH ST database and 35 databases from the European ST-T database with long duration, which exhibits a promising result.
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Rahman et al. (2022) studied this question.
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