Validation of an algorithm for atrial fibrillation and flutter diagnosis

Abstract

In this work, the authors developed a methodology to evaluate an algorithm (AAFF) for atrial fibrillation (AF) and flutter (AFL) detection and discrimination. Atrial electrical activity in pathologies such as AF and AFL are difficult to characterize quantitatively. The diagnoses provided by AAFF were compared to those established by 8 clinicians at different expertise levels in cardiology, and the MIT-BIH database annotations. The concordance between diagnoses supplied by a pair of experts was studied with the measure of distances between their diagnoses. The methods used to compute distances were: Euclidean distance, Mahalanobis distance and City-block distance. Using the resulting matrices of distances between experts, cluster analyses were carried out to classify AAFF among human experts. The results show that differences between diagnoses made by AAFF and those made by some specialists were smaller than differences between some specialists themselves.