Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Jul 8, 2023
Date Accepted: Oct 19, 2023
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Novel Physical Activity Pattern Analysis Using Wrist-worn Wearables: Time-series Clustering
ABSTRACT
Background:
Physical activity plays a crucial role in maintaining a healthy lifestyle, and wrist-worn wearables have become popular tools for measuring activity levels. However, studies using these devices often rely on a single device model or use improper methods for analyzing the data.
Objective:
This study aimed to identify methods suitable for analyzing wearable data and determine daily physical activity patterns. The study also explored the association between these physical activity patterns and health risk factors.
Methods:
We collected personal health data and measured physical activity levels over the course of 1 week in adults with metabolic risk factors who wore wrist-worn wearables. A total of 47 participants were included in the analysis. The TADPole clustering method was used to identify physical activity patterns, while logistic regression models were used to analyze the relationship between activity patterns and health risk factors.
Results:
Participants were categorized into stable and shifting groups based on the similarity of physical activity patterns between weekdays and weekends. Logistic regression analysis revealed a significant association between older age (≥ 40 years) and shifting physical activity patterns (OR: 8.68, 95% CI: 1.95–48.85).
Conclusions:
This study found that age significantly influenced physical activity patterns. It also suggests a potential role of wrist-worn wearables and the TADPole clustering method in wearable data analysis.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.