Smartwatch Algorithm for Automated Detection of Atrial Fibrillation
Open accessAbstract
Background The Kardia Band (KB) is a novel technology that enables patients to record a rhythm strip using an Apple Watch (Apple, Cupertino, California). The band is paired with an app providing automated detection of atrial fibrillation (AF).Objectives The purpose of this study was to examine whether the KB could accurately differentiate sinus rhythm (SR) from AF compared with physician-interpreted 12-lead electrocardiograms (ECGs) and KB recordings.Methods Consecutive patients with AF presenting for cardioversion (CV) were enrolled. Patients underwent pre-CV ECG along with a KB recording. If CV was performed, a post-CV ECG was obtained along with a KB recording. The KB interpretations were compared to physician-reviewed ECGs. The KB recordings were reviewed by blinded electrophysiologists and compared to ECG interpretations. Sensitivity, specificity, and K coefficient were measured.Results A total of 100 patients were enrolled (age 68 ± 11 years). Eight patients did not undergo CV as they were found to be in SR. There were 169 simultaneous ECG and KB recordings. Fifty-seven were noninterpretable by the KB. Compared with ECG, the KB interpreted AF with 93% sensitivity, 84% specificity, and a K coefficient of 0.77. Physician interpretation of KB recordings demonstrated 99% sensitivity, 83% specificity, and a K coefficient of 0.83. Of the 57 noninterpretable KB recordings, interpreting electrophysiologists diagnosed AF with 100% sensitivity, 80% specificity, and a K coefficient of 0.74. Among 113 cases where KB and physician readings of the same recording were interpretable, agreement was excellent (K coefficient = 0.88).Conclusions The KB algorithm for AF detection supported by physician review can accurately differentiate AF from SR. This technology can help screen patients prior to elective CV and avoid unnecessary procedures.
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Wearables were used in one study to confirm persistent atrial fibrillation before admission for cardioversion.
“Wearables were used in one study to confirm persistent AF before admission for cardioversion53”
From Smart wearable devices in cardiovascular care: Where we are and how to move forward (2021) · cites this paper as [53]
KardiaBand coupled with the SmartRhythm 2.0 DNN showed a sensitivity of >97% for detecting AF episodes lasting ≥1 h.
“KardiaBand (AliveCor, USA), now commercially discontinued, coupled with the SmartRhythm 2.0 DNN was compared with implantable cardiac monitors in a study that collected >31,000 h of continuous heart rhythm data and showed a sensitivity of >97% for detecting AF episodes lasting ≥1 h (ref.53).”
From Smart wearable devices in cardiovascular care: Where we are and how to move forward (2021) · cites this paper as [53]
KardiaBand experienced difficulty in interpreting up to 33.3% of recordings in another analysis.
“However, the KardiaBand experienced difficulty in interpreting up to 33.3% of recordings in another analysis53.”
From Smart wearable devices in cardiovascular care: Where we are and how to move forward (2021) · cites this paper as [53]
Poor signal quality and false alarms can lead to inappropriate interpretation, resulting in unnecessary medical referrals and testing.
“For example, poor signal quality and false alarms can lead to inappropriate interpretation, resulting in unnecessary medical referrals and testing.141”
From Artificial intelligence for detection of cardiovascular-related diseases from wearable devices: A systematic review and meta-analysis (2022) · cites this paper as [141]
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- Authors
- Bumgarner, J. M., Lambert, C. T., Hussein, A. A., Cantillon, D. J., Baranowski, B., Wolski, K., Lindsay, B. D., Wazni, O. M., & Tarakji, K. G.
- Affiliations
- Cleveland Clinic (US)
- Corresponding author
- Tarakji, Khaldoun G.
- ORCID
- Venue
- Journal of the American College of Cardiology
- Publisher
- Elsevier BV
- Published
- 2018-05
- Volume
- 71
- Issue
- 21
- Pages
- 2381-2388
- ISSN
- 0735-1097 (ISSN-L)
- OpenAlex
- W2791889721
- Cited by
- 446
- References
- 14
- Citations by year
- 2026: 25 · 2025: 41 · 2024: 45 · 2023: 43 · 2022: 69 · 2021: 83 · 2020: 71 · 2019: 52 · 2018: 15
- FWCI
- 41.80
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of the American College of Cardiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Atrial Fibrillation Management and Outcomes
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Keywords
- atrial fibrillation, automated detection, Apple Watch, smartwatches, electrocardiogram, sinus rhythm, cardioversion, physician review, diagnostic accuracy
- MeSH terms
- Wearable Electronic Devices, Aged, Aged, 80 and over, Algorithms, Atrial Fibrillation, Electric Countershock, Electrocardiography, Female, Humans, Male, Middle Aged, Prospective Studies, Single-Blind Method, Mobile Applications
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