Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Sep 21, 2018
Open Peer Review Period: Sep 25, 2018 - Nov 11, 2018
Date Accepted: Dec 30, 2018
(closed for review but you can still tweet)
Smartphone-based use of the photoplethysmography technique to detect atrial fibrillation in primary care: a diagnostic accuracy study of the FibriCheck application
ABSTRACT
Background:
Current guidelines of the European Society of Cardiology recommend opportunistic screening in people aged ≥65 years by pulse palpation and, if irregular, a 12-lead electrocardiogram (ECG). However, evolving technology may offer new opportunities to allow a better penetrance of screening in the general population at relatively low cost and with minimal logistic efforts, which may further lower the threshold for screening. Smartphones may offer an interesting modality to aid AF diagnosis, as their use has exponentially increased in recent years and is continuing to grow.
Objective:
This study tested the diagnostic accuracy of the FibriCheck AF algorithm for the detection of atrial fibrillation (AF) based on smartphone photoplethysmography (PPG) and single-lead electrocardiography (ECG) signals.
Methods:
A convenience sample of patients, aged 65 and older, with and without a known history of AF, was recruited from 17 primary care facilities. Patients with an active pacemaker rhythm were excluded. A PPG signal was obtained with the backside camera of an iPhone 5S. Simultaneously, a single‑lead ECG was registered using a dermal patch with a wireless connection to the same smartphone. PPG and single-lead ECG signals were analysed using the FibriCheck AF algorithm. At the same time, a 12‑lead ECG was obtained and interpreted off-line by independent cardiologists to determine the presence of AF.
Results:
A total of 102/223 subjects (46%) were in AF. PPG signal quality was sufficient for analysis in 93%, and single‑lead ECG quality was sufficient in 94% of the participants. After removing insufficient quality measurements, the sensitivity and specificity were 96% (95% CI 89-99%) and 97% (95% CI 91-99%) for the PPG signal versus 95% (95% CI 88-98%) and 97% (95% CI 91-99%) for the single‑lead ECG, respectively. False-positive results were mainly due to premature ectopic beats. In 196 subjects where the signal quality of both techniques was adequate, PPG and single‑lead ECG yielded a similar diagnosis in 192 subjects (98%).
Conclusions:
The FibriCheck AF algorithm had a very good sensitivity and specificity to detect AF based on both the smartphone PPG and the single-lead ECG signals in a primary care convenience sample.
Citation
Per the author's request the PDF is not available.
Copyright
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