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  Verification, analytical validation and clinical validation (V3) of wearable dosimeters and light loggers

Spitschan, M., Smolders, K., Vandendriessche, B., Bent, B., Bakker, J., Rodriguez-Chavez, I., et al. (2022). Verification, analytical validation and clinical validation (V3) of wearable dosimeters and light loggers. Digital Health, 8(12): 20552076221144858. doi:10.1177/20552076221144858.

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 Creators:
Spitschan, M1, Author                 
Smolders, K, Author
Vandendriessche, B, Author
Bent, B, Author
Bakker, JP, Author
Rodriguez-Chavez, IR, Author
Vetter, C, Author
Affiliations:
1Research Group Translational Sensory and Circadian Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_3360460              

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 Abstract: Background
Light exposure is an important driver and modulator of human physiology, behavior and overall health, including the biological clock, sleep-wake cycles, mood and alertness. Light can also be used as a directed intervention, e.g., in the form of light therapy in seasonal affective disorder (SAD), jetlag prevention and treatment, or to treat circadian disorders. Recently, a system of quantities and units related to the physiological effects of light was standardized by the International Commission on Illumination (CIE S 026/E:2018). At the same time, biometric monitoring technologies (BioMeTs) to capture personalized light exposure were developed. However, because there are currently no standard approaches to evaluate the digital dosimeters, the need to provide a firm framework for the characterization, calibration, and reporting for these digital sensors is urgent.
Objective
This article provides such a framework by applying the principles of verification, analytic validation and clinical validation (V3) as a state-of-the-art approach for tools and standards in digital medicine to light dosimetry.
Results
This article describes opportunities for the use of digital dosimeters for basic research, for monitoring light exposure, and for measuring adherence in both clinical and non-clinical populations to light-based interventions in clinical trials.

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 Dates: 2022-12
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1177/20552076221144858
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Title: Digital Health
Source Genre: Journal
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Publ. Info: Thousand Oaks, CA, USA : Sage
Pages: - Volume / Issue: 8 (12) Sequence Number: 20552076221144858 Start / End Page: - Identifier: ISSN: 2055-2076
CoNE: https://pure.mpg.de/cone/journals/resource/2055-2076