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The WATCH AF Trial: SmartWATCHes for Detection of Atrial Fibrillation
Open accessAbstract
Objectives The WATCH AF (SmartWATCHes for Detection of Atrial Fibrillation) trial compared the diagnostic accuracy to detect atrial fibrillation (AF) by a smartwatch-based algorithm using photoplethysmographic (PPG) signals with cardiologists' diagnosis by electrocardiography (ECG).Background Timely detection of AF is crucial for stroke prevention.Methods In this prospective, 2-center, case-control trial, a PPG pulse wave recording using a commercially available smartwatch was obtained along with Internet-enabled mobile ECG in 672 hospitalized subjects. PPG recordings were analyzed by a novel automated algorithm. Cardiologists' diagnoses were available for 650 subjects, although 142 (21.8%) datasets were not suitable for PPG analysis, among them 101 (15.1%) that were also not interpretable by the automated Internet-enabled mobile ECG algorithm, resulting in a sample size of 508 subjects (mean age 76.4 years, 225 women, 237 with AF) for the main analyses.Results For the PPG algorithm, we found a sensitivity of 93.7% (95% confidence interval [CI]: 89.8% to 96.4%), a specificity of 98.2% (95% CI: 95.8% to 99.4%), and 96.1% accuracy (95% CI: 94.0% to 97.5%) to detect AF.Conclusions The results of the WATCH AF trial suggest that detection of AF using a commercially available smartwatch is in principle feasible, with very high diagnostic accuracy. Applicability of the tested algorithm is currently limited by a high dropout rate as a result of insufficient signal quality. Thus, achieving sufficient signal quality remains challenging, but real-time signal quality checks are expected to improve signal quality. Whether smartwatches may be useful complementary tools for convenient long-term AF screening in selected at-risk patients must be evaluated in larger population-based samples. (SmartWATCHes for Detection of Atrial Fibrillation [WATCH AF]:; NCT02956343).
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“but the reliability of such tools is limited by the presence of noise in data collected from wearable and handheld devices12,13.”
From Detection of left ventricular systolic dysfunction from single-lead electrocardiography adapted for portable and wearable devices (2023) · cites this paper as [12]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
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“with a wearable device-based atrial fibrillation screening study disqualifying 22% of patients due to insufficient signal quality12.”
From Detection of left ventricular systolic dysfunction from single-lead electrocardiography adapted for portable and wearable devices (2023) · cites this paper as [12]
In the citing paper
“A common way to deal with artifact-corrupted PPGs, and thus improve the reliability of arrhythmia detectors, is to exclude segments of poor signal quality [10,27,28] as well as accelerometer-identified motion [11][12][13][27][28][29][30].”
From Modeling of artifacts in the wrist photoplethysmogram: Application to the detection of life-threatening arrhythmias (2021) · cites this paper as [28]
In the citing paper
“The potential utility of wrist-worn PPG devices for detecting possible AF has been assessed in recent studies”
From Wearable Photoplethysmography for Cardiovascular Monitoring (2022) · cites this paper as [198]
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BackgroundHow to use digital devices to detect and manage arrhythmias: an EHRA practical guide
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Wearable Photoplethysmography for Cardiovascular Monitoring
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“The potential utility of wrist-worn PPG devices for detecting possible AF has been assessed in recent studies [197], [198].”
Metadata
- Authors
- Dörr, M., Nohturfft, V., Brasier, N., Bosshard, E., Djurdjevic, A., Gross, S., Raichle, C. J., Rhinisperger, M., Stöckli, R., & Eckstein, J.
- Affiliations
- Universitätsmedizin Greifswald (DE)
- University Hospital of Basel (CH)
- Corresponding author
- Dörr, Marcus
- Venue
- JACC. Clinical electrophysiology
- Publisher
- Elsevier BV
- Published
- 2019-02
- Volume
- 5
- Issue
- 2
- Pages
- 199-208
- ISSN
- 2405-500X (ISSN-L)
- OpenAlex
- W2902001060
- Cited by
- 245
- References
- 34
- Citations by year
- 2026: 15 · 2025: 21 · 2024: 32 · 2023: 37 · 2022: 45 · 2021: 47 · 2020: 33 · 2019: 14
- FWCI
- 9.39
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- JACC. Clinical electrophysiology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Universitätsspital Basel
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Atrial Fibrillation Management and Outcomes
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Keywords
- atrial fibrillation, smartwatches, photoplethysmography, atrial fibrillation detection, diagnostic accuracy, stroke prevention, hospitalized patients, signal quality
- MeSH terms
- Wearable Electronic Devices, Aged, Aged, 80 and over, Algorithms, Atrial Fibrillation, Electrocardiography, Female, Humans, Male, Prospective Studies, Sensitivity and Specificity, Reproducibility of Results, Case-Control Studies, Photoplethysmography, Pulse Wave Analysis
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