PQRST wave detection on ECG signals

Objective: One way of detecting the heart disease is to determine the presence of abnormalities in PQRST interval on ECG signals. Therefore, it is expected to be used as a preliminary diagnosis of heart health and to prevent or decrease the mortality rate due to heart attack. Methods: This paper uses three main processes: data acquisition, signal preprocessing, and feature extraction. The experiment was done to eighteen subjects recorded for 2 min in a relaxed condition to obtain P wave points, QRS complexes, and T waves. Result: Based on the data obtained from the 18 subjects, the average accuracy of point P detection is 98.31%, point Q = 98.7%, point R-99.12%, point S = 86.27%, and point T-97.99%. Conclusion: The extraction of used features proved capable of detecting P waves, QRS complexes, T waves, as well as the amount of heart rate on all subjects. (C) 2021 SESPAS. Published by Elsevier Espana, S.L.U.

Automated summary

By detecting abnormalities in the PQRST interval on ECG signals, it can serve as a preliminary diagnosis of heart health. The study results indicate that the feature extraction method used has a high accuracy in detecting the heart health status of the subjects.