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Review
. 2020 Apr 29;17(9):3093.
doi: 10.3390/ijerph17093093.

A Review of Atrial Fibrillation Detection Methods as a Service

Oliver Faust  1 , Edward J Ciaccio  2 , U Rajendra Acharya  3   4
Affiliations
Review

A Review of Atrial Fibrillation Detection Methods as a Service

Oliver Faust et al. Int J Environ Res Public Health. .

Abstract

Atrial Fibrillation (AF) is a common heart arrhythmia that often goes undetected, and even if it is detected, managing the condition may be challenging. In this paper, we review how the RR interval and Electrocardiogram (ECG) signals, incorporated into a monitoring system, can be useful to track AF events. Were such an automated system to be implemented, it could be used to help manage AF and thereby reduce patient morbidity and mortality. The main impetus behind the idea of developing a service is that a greater data volume analyzed can lead to better patient outcomes. Based on the literature review, which we present herein, we introduce the methods that can be used to detect AF efficiently and automatically via the RR interval and ECG signals. A cardiovascular disease monitoring service that incorporates one or multiple of these detection methods could extend event observation to all times, and could therefore become useful to establish any AF occurrence. The development of an automated and efficient method that monitors AF in real time would likely become a key component for meeting public health goals regarding the reduction of fatalities caused by the disease. Yet, at present, significant technological and regulatory obstacles remain, which prevent the development of any proposed system. Establishment of the scientific foundation for monitoring is important to provide effective service to patients and healthcare professionals.

Keywords: atrial fibrillation; computer-aided diagnosis; service design.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; nor in the decision to publish the results.

Figures

Figure 1
Figure 1
The first row depicts two ECG signals and the second row the corresponding RR interval traces. The two plots in the first column show NSR, and the plots in the second row show AF symptoms. The Rpeak, in the ECG plots, indicates ventricular depolarization, i.e., the time of the heart beat. The time between two heart beats, say a and b, is indicated as the RRinterval. That time duration forms the amplitude, and the time location of the second beat b is the time location of an RR interval sample. The Pwave, labeled in the NSR ECG plot, indicates atrial depolarization.
Figure 2
Figure 2
Service timeline.
Figure 3
Figure 3
Information flow from patient to cardiologist.
Figure 4
Figure 4
Taxonomy of digital biomarkers.
Figure 5
Figure 5
Taxonomy of artificial intelligence.
Figure 6
Figure 6
Technologies that underpin atrial fibrillation detection as a service.
See this image and copyright information in PMC

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