A novel method for real-time atrial fibrillation detection in electrocardiograms using multiple parameters

Ann Noninvasive Electrocardiol. 2014 May;19(3):217-25. doi: 10.1111/anec.12111. Epub 2013 Nov 20.


Background: Automatic detection of atrial fibrillation (AF) in electrocardiograms (ECGs) is beneficial for AF diagnosis, therapy, and management. In this article, a novel method of AF detection is introduced. Most current methods only utilize the RR interval as a critical parameter to detect AF; thus, these methods commonly confuse AF with other arrhythmias.

Methods: We used the average number of f waves in a TQ interval as a characteristic parameter in our robust, real-time AF detection method. Three types of clinical ECG data, including ECGs from normal, AF, and non-AF arrhythmia subjects, were downloaded from multiple open access databases to validate the proposed method.

Results: The experimental results suggested that the method could distinguish between AF and normal ECGs with accuracy, sensitivity, and positive predictive values (PPVs) of 93.67%, 94.13%, and 98.69%, respectively. These values are comparable to those of related methods. The method was also able to distinguish between AF and non-AF arrhythmias and had performance indexes (accuracy 94.62%, sensitivity 94.13%, and PPVs 97.67%) that were considerably better than those of other methods.

Conclusions: Our proposed method has prospects as a practical tool enabling clinical diagnosis, treatment, and monitoring of AF.

Keywords: accuracy; atrial fibrillation; detection; electrocardiogram (ECG); real-time.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Atrial Fibrillation / diagnosis*
  • Atrial Fibrillation / physiopathology*
  • Computer Systems
  • Databases, Factual
  • Electrocardiography / methods*
  • Humans
  • Predictive Value of Tests
  • Reproducibility of Results
  • Sensitivity and Specificity