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Validity, Accuracy, and Safety Assessment of an Aerobic Interval Training Using an App-Based Prehabilitation Program (PROTEGO MAXIMA Trial) Before Major Surgery: Prospective, Interventional Pilot Study

smartwatches

Sara Fatima Faqar Uz Zaman, Svenja Sliwinski, Lisa Mohr-Wetzel, Julia Dreilich, Natalie Filmann, Charlotte Detemble, Dora Zmuc, Felix Chun, Wojciech Derwich, Waldemar Schreiner, Wolf Bechstein, Johannes Fleckenstein, Andreas A Schnitzbauer

JMIR Mhealth Uhealth 2025;13:e55298

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Step Count Accuracy of the Life Plus Connected Watch at Different Localizations and Speeds in Healthy Adults, Patients With Cardiovascular Disease, and Patients With Peripheral Artery Disease: Step Count Validation Study in Laboratory Settings

In healthy populations, wearable devices such as smartwatches are frequently used as motivational and self-monitoring tools for physical activity [11-14]. These wearable physical activity tracker devices offer considerable advantages in health care and personalized physical activity management in populations with chronic disease [15]. The gait of these patients can be different than those of healthy persons and may therefore influence the wearable device’s accuracy [16-19].

Anne-Noëlle Heizmann, Edouard Ollier, Pierre Labeix, Ivan Goujon, Frédéric Roche, Claire Le Hello

JMIR Form Res 2025;9:e58964

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Exploring the Use of Smartwatches and Activity Trackers for Health-Related Purposes for Children Aged 5 to 11 years: Systematic Review

(2) What are the characteristics of the smartwatches and activity trackers being used for health-related applications with children aged 5 to 11 years (eg, device type and features included)? (3) What is the feasibility and acceptability of using smartwatches and activity trackers for health-related applications with children aged 5 to 11 years?

Lauren Thompson, Sydney Charitos, Jon Bird, Paul Marshall, Amberly Brigden

J Med Internet Res 2025;27:e62944

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The Value of Smartwatches in the Health Care Sector for Monitoring, Nudging, and Predicting: Viewpoint on 25 Years of Research

A significant development is Germany’s recent legislation, which allows patients to transfer health data collected by smartwatches directly into their health records [7]. Numerous studies explore the integration of smartwatches into health care [8-14]. Yet, many studies concentrate on particular facets or stand-alone applications of smartwatches, often lacking a comprehensive framework that encompasses the diverse challenges and opportunities these devices present.

Charlotte Köhler, Alexander Bartschke, Daniel Fürstenau, Thorsten Schaaf, Eduardo Salgado-Baez

J Med Internet Res 2024;26:e58936

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Using a Smartwatch App to Understand Young Adult Substance Use: Mixed Methods Feasibility Study

Moreover, smartwatches offer extensive health-sensing features that allow individuals to track and understand health behaviors. Thus, in recent years, there has been wide adoption of smartwatches: globally, approximately 202 million individuals own smartwatches [17], with 1 in 5 Americans using a smartwatch or fitness tracker [18]. This uptake of smartwatches by consumers has propelled researchers to investigate how smartwatches can be used as instruments of behavioral health studies.

Sahiti Kunchay, Ashley N Linden-Carmichael, Saeed Abdullah

JMIR Hum Factors 2024;11:e50795

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Accuracy of the Apple Watch Series 4 and Fitbit Versa for Assessing Energy Expenditure and Heart Rate of Wheelchair Users During Treadmill Wheelchair Propulsion: Cross-sectional Study

Reference 33: Accuracy of commercially available smartwatches in assessing energy expenditure duringsmartwatches

Marius Lyng Danielsson, Melanie Vergeer, Guy Plasqui, Julia Kathrin Baumgart

JMIR Form Res 2024;8:e52312

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Using Wearable Devices and Speech Data for Personalized Machine Learning in Early Detection of Mental Disorders: Protocol for a Participatory Research Study

Wearable devices, such as smartwatches and fitness trackers, have emerged as a promising tool for detecting mental health conditions. Several studies have investigated wearables data in combination with machine learning algorithms to detect various mental health conditions, such as depression, anxiety, and bipolar disorder, by analyzing physiological data, such as heart rate and sleep patterns [29,30].

Ramon E Diaz-Ramos, Isabella Noriega, Luis A Trejo, Eleni Stroulia, Bo Cao

JMIR Res Protoc 2023;12:e48210

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Characterizing Real-World Implementation of Consumer Wearables for the Detection of Undiagnosed Atrial Fibrillation in Clinical Practice: Targeted Literature Review

In one meta-analysis that included 5 observational studies of smartwatches, the sensitivity and specificity were 93% and 94%, respectively, and PPG provided slightly better diagnostic accuracy than single-lead ECG, although there was heterogeneity among the studies [5]. Another review of 18 studies, nearly all of which used PPG, estimated that the sensitivity, specificity, and accuracy of smartwatches for the detection of cardiac arrhythmias were 100%, 95%, and 97%, respectively [37].

Julie K Simonson, Misty Anderson, Cate Polacek, Erika Klump, Saira N Haque

JMIR Cardio 2023;7:e47292

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