Detecting Atrial Fibrillation and Atrial Flutter in Daily Life Using Photoplethysmography Data.

Linda M Eerikainen,Rik Vullings,Alberto G Bonomi,Helma M De Morree,Ronald M Aarts,Fons Schipper,Lukas R C Dekker

doi:10.1109/jbhi.2019.2950574

Abstract

Photoplethysmography (PPG) enables unobtrusive heart rate monitoring, which can be used in wrist-worn applications. Its potential for detecting atrial fibrillation (AF) has been recently presented. Besides AF, another cardiac arrhythmia increasing stroke risk and requiring treatment is atrial flutter (AFL). Currently, the knowledge about AFL detection with PPG is limited. The objective of our study was to develop a model that classifies AF, AFL, and sinus rhythm with or without premature beats from PPG and acceleration data measured at the wrist in daily life. A dataset of 40 patients was collected by measuring PPG and accelerometer data, as well as electrocardiogram as a reference, during 24-hour monitoring. The dataset was split into 75%-25% for training and testing a Random Forest (RF) model, which combines features from PPG, inter-pulse intervals (IPI), and accelerometer data, to classify AF, AFL, and other rhythms. The performance was compared to an AF detection algorithm combining traditional IPI features for determining the robustness of the accuracy in presence of AFL. The RF model classified AF/AFL/other with sensitivity and specificity of 97.6/84.5/98.1% and 98.2/99.7/92.8%, respectively. The results with the IPI-based AF classifier showed that the majority of false detections were caused by AFL. The PPG signal contains information to classify AFL in the presence of AF, sinus rhythm, or sinus rhythm with premature contractions. PPG could indicate presence of AFL, not only AF.

Highlights

A TRIAL fibrillation (AF) is a cardiac arrhythmia that has been estimated to affect approximately 3% of the adult population, the prevalence increasing at older age [1], [2]
The results are calculated with 43.6% of the data after the windows not containing a sufficient number of inter-pulse intervals (IPI) or the reference was labeled as artifact were excluded
We demonstrated that PPG and acceleration measurements at the wrist can be used to discriminate between AF, atrial flutter (AFL), and other rhythms in daily life

Summary

Introduction

A TRIAL fibrillation (AF) is a cardiac arrhythmia that has been estimated to affect approximately 3% of the adult population, the prevalence increasing at older age [1], [2]. Solutions for long-term monitoring that work in daily life are needed for detecting intermittent episodes of AF that may be missed if monitoring period is short. Another cardiac arrhythmia causing a similar stroke risk as AF, but is less common, is atrial flutter (AFL) [5], [6]. The aims in management are similar, the treatment strategies for the two arrhythmias differ. Rate control in AFL is often more difficult to achieve than in AF [4] and antiarrhythmic therapy of AF may cause AFL [5]. Knowing the type of arrhythmia causing the stroke risk is important as antiarrhythmic therapies differ

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Discussion

Conclusion