The authors specifically looked at atrial fibrillation because it can go undetected and be difficult to manage. Office visits and short-term monitoring provide limited information on disease presence and burden, which can result in serious complications. However, ongoing monitoring with mHealth devices is an opportunity to prevent strokes, manage symptoms and reduce hospitalizations from atrial fibrillation. Machine learning has emerged as a powerful technology to enhance atrial fibrillation detection from wearable devices. Importantly, physical activity and fitness are also linked with primary prevention of atrial fibrillation and reduced atrial fibrillation burden and recurrence. The authors note the importance of broad collaboration to further integrate mHealth technology into clinical care, with the potential for substantial individual and societal benefits.


The American College of Cardiology is the professional home for the entire cardiovascular care team. The mission of the College and its more than 52,000 members is to transform cardiovascular care and to improve heart health. The ACC leads in the formation of health policy, standards and guidelines. The College operates national registries to measure and improve care, offers cardiovascular accreditation to hospitals and institutions, provides professional medical education, disseminates cardiovascular research and bestows credentials upon cardiovascular specialists who meet stringent qualifications. For more, visit acc.org.
The Journal of the American College of Cardiology ranks among the top cardiovascular journals in the world for its scientific impact. JACC is the flagship for a family of journals--JACC: Cardiovascular Interventions, JACC: Cardiovascular Imaging, JACC: Heart Failure, JACC: Clinical Electrophysiology and JACC: Basic to Translational Science--that prides themselves in publishing the top peer-reviewed research on all aspects of cardiovascular disease. Learn more at JACC.org.

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