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Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health
Published on: February 21, 2025
Personalized cardiovascular risk management for outdoor activities: a digital health application
Marco Vecchiato1,2,3, Nicola Borasio1,4, Sandro Savino5
1Sports and Exercise Medicine Division, Department of Medicine, University of Padova, Via Giustiniani 2, Padova 35128, Italy.
Abstract:
Hiking is a widely practiced outdoor activity with well-known cardiovascular and mental health benefits. However, its popularity among individuals with chronic conditions and across varying fitness levels raises safety concerns, especially in mountainous environments. Current trail planning tools typically rely on generic metrics, without considering individual cardiovascular risk or functional capacity. To address this gap, a novel digital system named MOVE was developed. Based on a patented algorithm, MOVE integrates user-specific characteristics, such as age, sex, body mass index, physical activity level, cardiovascular risk factors, and chronic conditions, with trail features, such as slope, elevation, and altitude. The system provides estimated cardiorespiratory fitness (eCRF), classifies cardiovascular risk according to ESC guidelines, and generates personalized predictions of hiking time, energy expenditure, heart rate ranges, and relative effort. Following its public release in late 2024, the app was widely adopted in spring-summer 2025, with over 3000 hikes recorded. Users included individuals with a wide range of eCRF and cardiovascular risk profiles, highlighting MOVE's potential for real-world applicability. The app was particularly used in collaboration with Alpine tourist regions, supported by trail signage and QR codes. Nearly one-third of hikes were classified as high-effort, mainly in individuals with lower eCRF or greater trail demands. MOVE represents a promising step towards personalized outdoor physical activity. Future developments include real-time tracking, adaptive feedback, wearable integration, and AI-driven modelling. This approach may enhance safety and accessibility of hiking, particularly for at-risk populations, supporting public health through safe engagement with nature-based exercise.
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