Abstract

Summary

This paper (despite an abstract mismatch suggesting a fNIRS paper was accidentally attached) describes open-source Python tools for processing and analyzing personal light exposure data, enabling more standardized and reproducible circadian light research. Practical applications include quantifying individual light dose metrics such as melanopic EDI, supporting better lighting design informed by real-world exposure patterns.
Categories

Categories

Sleep & Circadian Health: Open-source Python routines for analyzing personalized light exposure data are directly relevant to circadian rhythm research and light dosimetry.
The Science of Light: The toolset supports analysis of melanopic and spectral light exposure metrics relevant to circadian lighting standards and photoreceptor biology.
Authors

Author(s)

K Wulff, DJ Skene, M Münch, M Spitschan, G Hammad
Publication Date

Publication Year

2023
View more publications