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Open-source python ...
Open-source python module for the analysis of personalized light exposure data from wearable light loggers and dosimeters
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- Hammad, Grégory (författare)
- Sleep & Chronobiology Group, GIGA – CRC in Vivo Imaging, University of Liège, Liège, Belgium; Chair of Neurogenetics, Institute of Human Genetics, University Hospital, Technical University of Munich, Munich, Germany
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- Wulff, Katharina (författare)
- Umeå universitet,Wallenberg centrum för molekylär medicin vid Umeå universitet (WCMM),Institutionen för molekylärbiologi (Medicinska fakulteten),Institutionen för molekylärbiologi (Teknisk-naturvetenskaplig fakultet)
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- Skene, Debra J. (författare)
- Chronobiology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom
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- Münch, Mirjam (författare)
- Centre for Chronobiology, Psychiatric Hospital of the University of Basel, Basel, Switzerland; Transfaculty Platform for Molecular and Cognitive Neuroscience, University of Basel, Basel, Switzerland
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- Spitschan, Manuel (författare)
- 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
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(creator_code:org_t)
- Taylor & Francis, 2024
- 2024
- Engelska.
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Ingår i: LEUKOS The Journal of the Illuminating Engineering Society of North America. - : Taylor & Francis. - 1550-2724 .- 1550-2716. ; 20:4, s. 380-389
- Relaterad länk:
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https://doi.org/10.1...
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https://umu.diva-por... (primary) (Raw object)
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinska och farmaceutiska grundvetenskaper -- Neurovetenskaper (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Basic Medicine -- Neurosciences (hsv//eng)
Nyckelord
- analysis
- dosimetry
- Light exposure
- light loggers
- open-source software
- python
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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