Objective: This study examined the accuracy of smartwatches in predicting running performance.
Methods: A total of 154 amateur runners (123 males and 31 females) were recruited. After wearing the HUAWEI WATCH GT Runner for a minimum of six weeks, the runners' actual completion times for 5 km, 10 km, and half marathon distances were measured, resulting in 288 test instances. The predicted completion times for the same distances displayed on the watch on the test day were recorded simultaneously.
Results: The actual and predicted performances for the 5, 10, and 21.1 km distances were highly correlated, with ≥ 0.95 ( < 0.001) and ≥ 0.9 for all three distances, an error rate between the measured and predicted values of less than 3%, and intraclass correlation coefficient ≥0.9. The bias ± 95% limits of agreement were -20.4 ± 44.2 s for 5 km, 4.1 ± 299.1 s for 10 km, and 143.8 ± 400.4 s for the half marathon.
Conclusions: This study confirmed that the smartwatch exhibits high precision in predicting 5 km, 10 km, and half marathon performances, with an accuracy exceeding 97%. The performance prediction features of smartwatches can effectively guide amateur runners in setting reasonable competition goals and preparing for races.
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http://dx.doi.org/10.3389/fspor.2025.1517632 | DOI Listing |
J Vis Exp
February 2025
Department of Artificial Intelligence, Faculty of Computer Science and Information Technology, Universiti Malaya;
This study aims to validate the accuracy of low-cost fitness smartwatches by comparing their data with gold-standard measurements for cardiovascular and physical activity parameters. The study enrolled 50 subjects, 26 undergoing validation testing for heart rate, blood oxygen saturation (SpO2), and sleep data against polysomnography (PSG). Additionally, 24 subjects participated in the 3-Minute Walk Test (3MWT) and Stairs Climbing (SC), with step counts validated against manual video calculations.
View Article and Find Full Text PDFJ Clin Monit Comput
March 2025
Department of Anaesthesiology, Intensive Care, Emergency and Pain Medicine, University Hospital Würzburg, Oberdürrbacher Str. 6, 97080, Würzburg, Germany.
Wearables and Internet of Things (IoT) technologies are increasingly incorporated into healthcare, including perioperative settings. These devices offer continuous non-invasive monitoring of vital signs, patient position, and mobilization. Nonetheless, there is currently little information about tolerance and acceptance of wearables in postoperative patients.
View Article and Find Full Text PDFPNAS Nexus
March 2025
Department of Management Science & Engineering, Stanford University, Huang Engineering Center, 475 Via Ortega, Stanford, CA 94305, USA.
Recent studies have demonstrated that wearable devices, such as smartwatches, can accurately detect infections in presymptomatic and asymptomatic individuals. Yet, the extent to which smartwatches can contribute to prevention and control of infectious diseases through a subsequent reduction in social contacts is not fully understood. We developed a multiscale modeling framework that integrates within-host viral dynamics and between-host interactions to estimate the risk of viral disease outbreaks within a given population.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
July 2024
Advancements in human-computer interaction (HCI) and machine learning are seen as key avenues to help individuals living with upper limb disabilities in accomplishing their activities of daily living. Multi-channel myoelectric systems are a promising approach for HCI due to their intuitive and accurate capture of user intent through muscle activity. However, such systems are still bulky compared to widely accepted smartwatches-like devices and as such pose a challenge for seamless integration into daily life.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
July 2024
In the rapidly growing field of wearable technology, optical devices are emerging as a significant innovation, offering non-invasive methods for analyzing skin and underlying tissue properties. Despite their promise, progress has been slowed by a lack of specialized prototypes and advanced analysis techniques. Addressing this gap, our study introduces, HydroTrack, an 18-channel spectroscopy sensor, ingeniously embedded in a smart-watch.
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