Numerical correlation between non-visual metrics and brightness metrics-implications for the evaluation of indoor white lighting systems in the photopic range

Tran Quoc Khanh; Trinh Quang Vinh; Peter Bodrogi

doi:10.1038/s41598-023-41371-3

Numerical correlation between non-visual metrics and brightness metrics-implications for the evaluation of indoor white lighting systems in the photopic range

Sci Rep. 2023 Sep 8;13(1):14858. doi: 10.1038/s41598-023-41371-3.

Authors

Tran Quoc Khanh¹, Trinh Quang Vinh², Peter Bodrogi³

Affiliations

¹ Department of Electrical Engineering and Information Technology, Laboratory of Adaptive Lighting Systems and Visual Processing, Technical University of Darmstadt, 64289, Darmstadt, Germany.
² Department of Electrical Engineering and Information Technology, Laboratory of Adaptive Lighting Systems and Visual Processing, Technical University of Darmstadt, 64289, Darmstadt, Germany. vinh@lichttechnik.tu-darmstadt.de.
³ ERCO GmbH, 58507, Lüdenscheid, Germany.

Abstract

From the beginning of the [Formula: see text] century until today, the demand for lighting systems includes not only visual parameters (brightness, contrast perception, color quality), but also non-visual parameters. It is necessary to define the new non-visual parameters for the realization of the new concept of Human Centric Lighting (HCL) or Integrative Lighting. As a contribution to this approach, many international research groups have tried to quantify the non-visual parameters such as Circadian Stimulus by Rea et. al. in USA ([Formula: see text], [Formula: see text]), Melanopic Equivalent Daylight ([Formula: see text]) illuminance, mEDI of the CIE S 026/E:2018 or the latest formula by Giménez et al., for the nocturnal melatonin suppression. Therefore, it is necessary to analyze the correlation between these non-visual metrics and brightness metrics such as the equivalent luminance of Fotios et al., or the latest brightness model of TU Darmstadt so that scientists, lighting engineers and lighting system users can correctly apply them in their work. In this context, this paper attempts to investigate and analyze these correlations between the three metric groups based on the database of 884 light sources of different light source technologies and daylight spectra. The obtained results show that the latest Circadian Stimulus model of Rea et. al. [Formula: see text] with the improvement of Circadian Light [Formula: see text] ([Formula: see text]) has solved the disadvantage of [Formula: see text], especially for the interrupted point between warm and cold white (about [Formula: see text]) or the junction between negative and positive signal of the opponent channel ([Formula: see text]). Moreover, these three metrics of the three research groups contain a high correlation coefficient, so that one metric can be transformed by linear functions to the other two parameters.