Determine atrial fibrillation burden with a photoplethysmographic mobile sensor: the atrial fibrillation burden trial : detection and quantification of episodes of atrial fibrillation using a cloud analytics service connected to a wearable with photoplethysmographic sensor

Reissenberger, Pamela; Serfözö, Peter; Piper, Diana; Juchler, Norman; Glanzmann, Sara; Gram, Jasmin; Hensler, Karina; Tonidandel, Hannah; Börlin, Elena; D’Souza, Marcus; Badertscher, Patrick; Eckstein, Jens

doi:10.1093/ehjdh/ztad039

Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-28467

Publication type:	Article in scientific journal
Type of review:	Peer review (publication)
Title:	Determine atrial fibrillation burden with a photoplethysmographic mobile sensor: the atrial fibrillation burden trial : detection and quantification of episodes of atrial fibrillation using a cloud analytics service connected to a wearable with photoplethysmographic sensor
Authors:	Reissenberger, Pamela Serfözö, Peter Piper, Diana Juchler, Norman Glanzmann, Sara Gram, Jasmin Hensler, Karina Tonidandel, Hannah Börlin, Elena D’Souza, Marcus Badertscher, Patrick Eckstein, Jens
et. al:	No
DOI:	10.1093/ehjdh/ztad039 10.21256/zhaw-28467
Published in:	European Heart Journal - Digital Health
Volume(Issue):	4
Issue:	5
Page(s):	402
Pages to:	410
Issue Date:	6-Jul-2023
Publisher / Ed. Institution:	Oxford University Press
ISSN:	2634-3916
Language:	English
Subjects:	Atrial fibrillation; AF burden; Photoplethysmography; Smartwatch; Monitoring
Subject (DDC):	004: Computer science 616: Internal medicine and diseases
Abstract:	Aims: Recent studies suggest that atrial fibrillation (AF) burden (time AF is present) is an independent risk factor for stroke. The aim of this trial was to study the feasibility and accuracy to identify AF episodes and quantify AF burden in patients with a known history of paroxysmal AF with a photoplethysmography (PPG)-based wearable. Methods and results: In this prospective, single-centre trial, the PPG-based estimation of AF burden was compared with measurements of a conventional 48 h Holter electrocardiogram (ECG), which served as the gold standard. An automated algorithm performed PPG analysis, while a cardiologist, blinded for the PPG data, analysed the ECG data. Detected episodes of AF measured by both methods were aligned timewise.Out of 100 patients recruited, 8 had to be excluded due to technical issues. Data from 92 patients were analysed [55.4% male; age 73.3 years (standard deviation, SD: 10.4)]. Twenty-five patients presented AF during the study period. The intraclass correlation coefficient of total AF burden minutes detected by the two measurement methods was 0.88. The percentage of correctly identified AF burden over all patients was 85.1% and the respective parameter for non-AF time was 99.9%. Conclusion: Our results demonstrate that a PPG-based wearable in combination with an analytical algorithm appears to be suitable for a semiquantitative estimation of AF burden in patients with a known history of paroxysmal AF.
URI:	https://digitalcollection.zhaw.ch/handle/11475/28467
Fulltext version:	Published version
License (according to publishing contract):	CC BY-NC 4.0: Attribution - Non commercial 4.0 International
Departement:	Life Sciences and Facility Management
Organisational Unit:	Institute of Computational Life Sciences (ICLS)
Appears in collections:	Publikationen Life Sciences und Facility Management

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Reissenberger, P., Serfözö, P., Piper, D., Juchler, N., Glanzmann, S., Gram, J., Hensler, K., Tonidandel, H., Börlin, E., D’Souza, M., Badertscher, P., & Eckstein, J. (2023). Determine atrial fibrillation burden with a photoplethysmographic mobile sensor: the atrial fibrillation burden trial : detection and quantification of episodes of atrial fibrillation using a cloud analytics service connected to a wearable with photoplethysmographic sensor. European Heart Journal - Digital Health, 4(5), 402–410. https://doi.org/10.1093/ehjdh/ztad039

Reissenberger, P. et al. (2023) ‘Determine atrial fibrillation burden with a photoplethysmographic mobile sensor: the atrial fibrillation burden trial : detection and quantification of episodes of atrial fibrillation using a cloud analytics service connected to a wearable with photoplethysmographic sensor’, European Heart Journal - Digital Health, 4(5), pp. 402–410. Available at: https://doi.org/10.1093/ehjdh/ztad039.

P. Reissenberger et al., “Determine atrial fibrillation burden with a photoplethysmographic mobile sensor: the atrial fibrillation burden trial : detection and quantification of episodes of atrial fibrillation using a cloud analytics service connected to a wearable with photoplethysmographic sensor,” European Heart Journal - Digital Health, vol. 4, no. 5, pp. 402–410, Jul. 2023, doi: 10.1093/ehjdh/ztad039.

REISSENBERGER, Pamela, Peter SERFÖZÖ, Diana PIPER, Norman JUCHLER, Sara GLANZMANN, Jasmin GRAM, Karina HENSLER, Hannah TONIDANDEL, Elena BÖRLIN, Marcus D’SOUZA, Patrick BADERTSCHER und Jens ECKSTEIN, 2023. Determine atrial fibrillation burden with a photoplethysmographic mobile sensor: the atrial fibrillation burden trial : detection and quantification of episodes of atrial fibrillation using a cloud analytics service connected to a wearable with photoplethysmographic sensor. European Heart Journal - Digital Health. 6 Juli 2023. Bd. 4, Nr. 5, S. 402–410. DOI 10.1093/ehjdh/ztad039

Reissenberger, Pamela, Peter Serfözö, Diana Piper, Norman Juchler, Sara Glanzmann, Jasmin Gram, Karina Hensler, et al. 2023. “Determine Atrial Fibrillation Burden with a Photoplethysmographic Mobile Sensor: The Atrial Fibrillation Burden Trial : Detection and Quantification of Episodes of Atrial Fibrillation Using a Cloud Analytics Service Connected to a Wearable with Photoplethysmographic Sensor.” European Heart Journal - Digital Health 4 (5): 402–10. https://doi.org/10.1093/ehjdh/ztad039.

Reissenberger, Pamela, et al. “Determine Atrial Fibrillation Burden with a Photoplethysmographic Mobile Sensor: The Atrial Fibrillation Burden Trial : Detection and Quantification of Episodes of Atrial Fibrillation Using a Cloud Analytics Service Connected to a Wearable with Photoplethysmographic Sensor.” European Heart Journal - Digital Health, vol. 4, no. 5, July 2023, pp. 402–10, https://doi.org/10.1093/ehjdh/ztad039.