[en] Light exposure fundamentally influences human physiology and behavior, with light being the most important zeitgeber of the circadian system. Throughout the day, people are exposed to various scenes differing in light level, spectral composition and spatio-temporal properties. Personalized light exposure can be measured through wearable light loggers and dosimeters, including wrist-worn actimeters containing light sensors, yielding time series of an individual’s light exposure. There is growing interest in relating light exposure patterns to health outcomes, requiring analytic techniques to summarize light exposure properties. Building on the previously published Python-based pyActigraphy module, here we introduce the module pyLight. This module allows users to extract light exposure data recordings from a wide range of devices. It also includes software tools to clean and filter the data, and to compute common metrics for quantifying and visualizing light exposure data. For this tutorial, we demonstrate the use of pyLight in one example dataset with the following processing steps: (1) loading, accessing and visual inspection of a publicly available dataset, (2) truncation, masking, filtering and binarization of the dataset, (3) calculation of summary metrics, including time above threshold (TAT) and mean light timing above threshold (MLiT). The pyLight module paves the way for open-source, large-scale automated analyses of light-exposure data.
Disciplines :
Neurosciences & behavior
Author, co-author :
Hammad, Grégory ; Université de Liège - ULiège > Département de Psychologie > Neuropsychologie de l'adulte ; Chair of Neurogenetics, Institute of Human Genetics, University Hospital, Technical University of Munich, Munich, Germany
Wulff, Katharina; Department of Molecular Biology, Umea University, Umea, Sweden ; Wallenberg Centre for Molecular Medicine (WCMM), Umea University, Umea, Sweden
Skene, Debra J.; Chronobiology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
Münch, Mirjam; Centre for Chronobiology, Psychiatric Hospital of the University of Basel, Basel, Switzerland ; Transfaculty Platform for Molecular and Cognitive Neuroscience, University of Basel, Basel, Switzerland
Spitschan, Manuel ; Translational Sensory & Circadian Neuroscience, Max Planck Institute for Biological Cybernetics, Tübingen, Germany ; TUM School of Medicine & Health, Technical University of Munich, Munich, Germany ; TUM Institute for Advanced Study, Technical University of Munich, Garching, Germany
Language :
English
Title :
Open-Source Python Module for the Analysis of Personalized Light Exposure Data from Wearable Light Loggers and Dosimeters
Publication date :
28 February 2024
Journal title :
LEUKOS - Journal of Illuminating Engineering Society of North America
Velux Stiftung Wellcome Trust University of Oxford KAW - Knut and Alice Wallenberg Foundation
Funding text :
This project was financially supported by the Daylight
Academy (DLA), a non-profit organization to promote the
research on and use of daylight funded by the Velux Stiftung.
K.W., D.S., M.M. and M.S. are members of DLA. During
early parts of this work, G.H., and M.S. were supported by
participating in the OLS-3 (Open Life Sciences) program.
During parts of this work, M.S. was supported by a Sir
Henry Wellcome Postdoctoral Fellowship (Wellcome Trust,
204686/Z/16/Z) and Linacre College, University of Oxford
(Biomedical Sciences Junior Research Fellowship). M.M. is
supported by the Velux Stiftung. K.W.’s contribution was in
part supported by the Knut and Wallenberg Foundation.
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