Contemporary ReviewSmartwatch-based detection of cardiac arrhythmias: Beyond the differentiation between sinus rhythm and atrial fibrillation
Introduction
The rapid and widespread introduction of smartwatches in health care presents both unique opportunities and challenges. Within the span of a few years, watches have functionally morphed from objects that tell time to de facto wearable minicomputers. Consumers from the general public now have direct access to devices and applications that offer real-time recordings of electrocardiogram (ECG) tracings. The tracings are recorded from 2 electrodes, one located on the back of the watch in contact with the skin and the other positioned on the watch casing (usually the digital crown). The tracing is automatically analyzed by an algorithm included in a proprietary application that measures the heart rate, analyzes the regularity of the rhythm, and searches for evidence of atrial fibrillation (AF). The tracings obtained by these devices differ in important ways from those of standard 12-lead ECGs that are typically performed in clinical settings as only 1 lead (lead I) is recorded. Accordingly, smartwatch tracings are not as comprehensive as 12-lead ECGs and should not be considered substitutes for them. However, a considerable amount of information, especially relating to the wearer’s heart rate, can be deduced from this single lead.
Interest in these types of devices and in their capabilities is growing rapidly.1,2 It is now not uncommon to see patients in whom diagnostic tracings of clinically relevant arrhythmias proved elusive until a smartwatch was used. Given that cardiac arrhythmias are often difficult to capture using standard investigations, the potential benefits of empowering individuals to record their own ECG tracings in real-time in various clinical scenarios are considerable but remain to be robustly demonstrated.
The main objective of this review is to describe the information that can be obtained from an ECG recording with a single lead beyond the differentiation between sinus rhythm and AF. We also review the strengths and limitations of using these devices in clinical settings and propose solutions to maximize their value.
Section snippets
Technical considerations
Although there exist important technical differences among available smartwatches and their ECG recordings, they share common features. Three points should be considered when using these devices to diagnose or monitor cardiac arrhythmias:
- 1.
Unlike ambulatory Holter monitoring and implantable loop recorders, smartwatches do not continuously record ECGs. The user must initiate a recording and actively hold the contralateral index finger on the smartwatch. This is a major limitation for their use in
Accuracy of smartwatch for the detection of AF
AF is the most common sustained rhythm disorder encountered in clinical practice and is an increasingly important public health problem, with nearly one-third of all strokes being attributed to this arrhythmia.3 Wearables have been proposed as screening tools to detect AF both in high-risk groups and in the general population with the goal of initiating anticoagulants to prevent strokes.4 This technology could similarly be used for patients with known AF to assess the effectiveness of
Organized atrial arrhythmias
Although its incidence is approximately 10 times lower than that of AF, typical atrial flutter remains relatively common.11 It has a characteristic appearance on the 12-lead ECG of stable flutter waves (“sawtooth” appearance) in the inferior leads. When the smartwatch is positioned on the left wrist, the diagnosis of typical atrial flutter can be difficult to make. There is usually very low voltage atrial activity in lead I, as it is largely oriented perpendicular to the activation vector.
Atrioventricular (nodal) reentry tachycardia: The ideal indication?
Atrioventricular (nodal) reentry tachycardias can occur at all ages but generally manifest in young patients without structural heart disease, which is also the population most likely to wear a smartwatch. Patients usually describe a history of recurrent palpitations of varying duration that resolve spontaneously or with vagal maneuvers. In the vast majority of cases, the arrhythmia is hemodynamically well tolerated, which enables the recording of an ECG with a smartwatch (Figure 4B).13
Wide complex tachycardias and the risk of false positives
The incidence of dangerous rhythm disturbances is very low in the young and healthy, which form the majority of smartwatch wearers. A less than perfect screening test used in a population with a very low pretest probability of serious arrhythmias translates not only into a modest posttest probability of disease but also a real risk of anxiety, unnecessary diagnostic testing, hospitalization, and even potentially inappropriate treatments. Thus, every tracing consistent with sustained ventricular
Perspectives
Fundamental shifts in medicine are set to occur as the digital and connected era extends to the clinical realm. The Apple Watch is currently the dominant product with more than half of the global market share and more than 100 million watches sold. Since the launch of the Apple Watch Series 4, one of its objectives has clearly been to establish itself as the world leader in connected health, made clear by their current slogan “The future of health is on your wrist.” Currently their smartwatches
Conclusion
Real-time access to ECGs, without a physician’s order, could allow individuals to play a more active role in their health care, facilitate screening efforts, and constitute a true revolution to our discipline. In the future, advances in artificial intelligence should reduce the number of false positives but could also lead to a significant expansion of automated diagnostic capabilities that are currently limited to differentiating between sinus rhythm and AF. Health care professionals should
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2023, Trends in Cardiovascular MedicineRole of Coexisting ECG Anomalies in the Accuracy of Smartwatch ECG Detection of Atrial Fibrillation
2022, Canadian Journal of Cardiology
Funding sources: This work received financial support from the French Government as part of the “Investments of the Future” program managed by the National Research Agency (ANR) (grant number ANR-10-IAHU-04), a Canadian Institutes of Health Research Banting Postdoctoral Fellowship, and a Royal College of Physicians and Surgeons of Canada Detweiler Travelling Fellowship (to F.D.R.).
Disclosures: The authors have no conflicts of interest to disclose. In particular, the authors have received no funding or goods from smartwatch manufacturers.