Skip to main content

CORRECTION article

Front. Physiol., 29 November 2022
Sec. Computational Physiology and Medicine
This article is part of the Research Topic Diagnosis, Monitoring, and Treatment of Heart Rhythm: New Insights and Novel Computational Methods View all 30 articles

Corrigendum on: A life-threatening arrhythmia detection method based on pulse rate variability analysis and decision tree

  • 1School of Electrical and Automatic Engineering, Changshu Institute of Technology, Suzhou, China
  • 2School of Computer and Information Technology, Northeast Petroleum University, Daqing, China
  • 3School of Computer Science and Engineering, Changshu Institute of Technology, Suzhou, China

A Corrigendum on
A life-threatening arrhythmia detection method based on pulse rate variability analysis and decision tree by Chou L, Liu J, Gong S and Chou Y (2022). Front. Physiol. 13:1008111. doi: 10.3389/fphys.2022.1008111

In the published article, there was an error in Affiliation(s) [1]. Instead of “[Country School of Electrical and Automatic Engineering, Changshu Institute of Technology, Suzhou, China],” it should be “[School of Electrical and Automatic Engineering, Changshu Institute of Technology, Suzhou, China].”

The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Keywords: pulse rate variability, arterial blood pressure, cardiovascular diseases, life-threatening arrhythmias, decision tree, intelligent recognition

Citation: Chou L, Liu J, Gong S and Chou Y (2022) Corrigendum on: A life-threatening arrhythmia detection method based on pulse rate variability analysis and decision tree. Front. Physiol. 13:1102527. doi: 10.3389/fphys.2022.1102527

Received: 19 November 2022; Accepted: 24 November 2022;
Published: 29 November 2022.

Approved by:

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2022 Chou, Liu, Gong and Chou. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Yongxin Chou, Y3NsZ2Nob3V5eEBjc2xnLmVkdS5jbg==

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.