Localization of origins of premature ventricular contraction in the whole ventricle based on machine learning and automatic beat recognition from 12-lead ECG.

Journal: Physiological measurement
Published Date:

Abstract

OBJECTIVE: The localization of origins of premature ventricular contraction (PVC) is the key factor for the success of ablation of ventricular arrhythmias. Existing methods rely heavily on manual extraction of PVC beats, which limits their application to the automatic PVC recognition from long-term data recorded by ECG monitors before and during operation. In addition, research identifying PVC sources in the whole ventricle have not been reported. The purpose of this study was to validate the feasibility of localization of origins of PVC in the whole ventricle and to explore an automatic algorithm for recognition of PVC beats based on long-term 12-lead ECG.

Authors

  • Kaiyue He
    Department of Electronic Engineering, Fudan University, Shanghai 200433, People's Republic of China. Authors contributed equally to this work.
  • Zhenning Nie
  • Gaoyan Zhong
  • Cuiwei Yang
  • Jian Sun
    Department Of Computer Science, University of Denver, 2155 E Wesley Ave, Denver, Colorado, 80210, United States of America.