--In this study we present detection algorithms of characteristic points of the QRS and T waves based on the continuous wavelet transform (CWT) with splines. This technique can handle any integer scale and the analysis is not restricted to scales that are powers of two, which allows to use a wide range of scales and to more efficiently reduce noise and artifacts. Evaluation of the QRS detection algorithm performance has been done in eight ECG data files of the MIT-BIH database, and the accuracy has been of 99.5 %. Evaluation of the detection algorithms of the QRS wave onset and offsets of QRS and T waves has been done in the CSE multi-lead measurement database, and the measurements were within the tolerance limits for deviations with respect of the manual measurements determined by the CSE experts. Therefore, the proposed algorithms to detect characteristic points of the QRS and T waves based on this technique allow the evaluation of the CWT in more scales, are robust to noise and artifacts and have the accuracy of a human expert.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.