Please use this identifier to cite or link to this item: http://dx.doi.org/10.25673/118526
Title: Wearables in chronomedicine and interpretation of circadian health
Author(s): Gubin, Denis
Weinert, DietmarLook up in the Integrated Authority File of the German National Library
Stefani, Oliver
Otsuka, Kuniaki
Borisenkov, Mikhail
Cornelissen, GermaineLook up in the Integrated Authority File of the German National Library
Issue Date: 2025
Type: Article
Language: English
Abstract: Wearable devices have gained increasing attention for use in multifunctional applications related to health monitoring, particularly in research of the circadian rhythms of cognitive functions and metabolic processes. In this comprehensive review, we encompass how wearables can be used to study circadian rhythms in health and disease. We highlight the importance of these rhythms as markers of health and well-being and as potential predictors for health outcomes. We focus on the use of wearable technologies in sleep research, circadian medicine, and chronomedicine beyond the circadian domain and emphasize actigraphy as a validated tool for monitoring sleep, activity, and light exposure. We discuss various mathematical methods currently used to analyze actigraphic data, such as parametric and non-parametric approaches, linear, non-linear, and neural network-based methods applied to quantify circadian and non-circadian variability. We also introduce novel actigraphy-derived markers, which can be used as personalized proxies of health status, assisting in discriminating between health and disease, offering insights into neurobehavioral and metabolic status. We discuss how lifestyle factors such as physical activity and light exposure can modulate brain functions and metabolic health. We emphasize the importance of establishing reference standards for actigraphic measures to further refine data interpretation and improve clinical and research outcomes. The review calls for further research to refine existing tools and methods, deepen our understanding of circadian health, and develop personalized healthcare strategies.
URI: https://opendata.uni-halle.de//handle/1981185920/120484
http://dx.doi.org/10.25673/118526
Open Access: Open access publication
License: (CC BY 4.0) Creative Commons Attribution 4.0(CC BY 4.0) Creative Commons Attribution 4.0
Journal Title: Diagnostics
Publisher: MDPI
Publisher Place: Basel
Volume: 15
Issue: 3
Original Publication: 10.3390/diagnostics15030327
Page Start: 1
Page End: 42
Appears in Collections:Open Access Publikationen der MLU

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