Real-world validation of smartphone-based photoplethysmography for rate and rhythm monitoring in atrial fibrillation

Author:

Gruwez Henri123ORCID,Ezzat Daniel3ORCID,Van Puyvelde Tim2ORCID,Dhont Sebastiaan13ORCID,Meekers Evelyne123ORCID,Bruckers Liesbeth4ORCID,Wouters Femke3ORCID,Kellens Michiel3ORCID,Van Herendael Hugo1ORCID,Rivero-Ayerza Maximo1ORCID,Nuyens Dieter1ORCID,Haemers Peter2ORCID,Pison Laurent13ORCID

Affiliation:

1. Department of Cardiology, Ziekenhuis Oost-Limburg , Synaps Park 1, 3600 Genk , Belgium

2. Department of Cardiovascular Sciences , KU Leuven, Leuven , Belgium

3. Limburg Clinical Research Center, Faculty of Medicine and Life Sciences, Hasselt University, Martelarenlaan 42, 3500   Hasselt , Belgium

4. Research Institute Center for Statistics (CENSTAT), Hasselt University , Hasselt , Belgium

Abstract

Abstract Aims Photoplethysmography- (PPG) based smartphone applications facilitate heart rate and rhythm monitoring in patients with paroxysmal and persistent atrial fibrillation (AF). Despite an endorsement from the European Heart Rhythm Association, validation studies in this setting are lacking. Therefore, we evaluated the accuracy of PPG-derived heart rate and rhythm classification in subjects with an established diagnosis of AF in unsupervised real-world conditions. Methods and results Fifty consecutive patients were enrolled, 4 weeks before undergoing AF ablation. Patients used a handheld single-lead electrocardiography (ECG) device and a fingertip PPG smartphone application to record 3907 heart rhythm measurements twice daily during 8 weeks. The ECG was performed immediately before and after each PPG recording and was given a diagnosis by the majority of three blinded cardiologists. A consistent ECG diagnosis was exhibited along with PPG data of sufficient quality in 3407 measurements. A single measurement exhibited good quality more often with ECG (93.2%) compared to PPG (89.5%; P < 0.001). However, PPG signal quality improved to 96.6% with repeated measurements. Photoplethysmography-based detection of AF demonstrated excellent sensitivity [98.3%; confidence interval (CI): 96.7–99.9%], specificity (99.9%; CI: 99.8–100.0%), positive predictive value (99.6%; CI: 99.1–100.0%), and negative predictive value (99.6%; CI: 99.0–100.0%). Photoplethysmography underestimated the heart rate in AF with 6.6 b.p.m. (95% CI: 5.8 b.p.m. to 7.4 b.p.m.). Bland–Altman analysis revealed increased underestimation in high heart rates. The root mean square error was 11.8 b.p.m. Conclusion Smartphone applications using PPG can be used to monitor patients with AF in unsupervised real-world conditions. The accuracy of AF detection algorithms in this setting is excellent, but PPG-derived heart rate may tend to underestimate higher heart rates.

Funder

Scientific Research Flanders

Qompium NV

Publisher

Oxford University Press (OUP)

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