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Verification, analytical validation and clinical validation (V3) of wearable dosimeters and light loggers
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 disorde...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9806438/ https://www.ncbi.nlm.nih.gov/pubmed/36601285 http://dx.doi.org/10.1177/20552076221144858 |
Sumario: | 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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