Numerical correlation between non-visual metrics and brightness metrics—implications for the evaluation of indoor white lighting systems in the photopic range
Abstract From the beginning of the $$21\textrm{st}$$ 21 st 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 realiz...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-09-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-41371-3 |
| _version_ | 1797452678960250880 |
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| author | Tran Quoc Khanh Trinh Quang Vinh Peter Bodrogi |
| author_facet | Tran Quoc Khanh Trinh Quang Vinh Peter Bodrogi |
| author_sort | Tran Quoc Khanh |
| collection | DOAJ |
| description | Abstract From the beginning of the $$21\textrm{st}$$ 21 st 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 ( $$CS_{2018}$$ C S 2018 , $$CS_{2021}$$ C S 2021 ), Melanopic Equivalent Daylight ( $$D_{65}$$ D 65 ) 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. $$CS_{2021}$$ C S 2021 with the improvement of Circadian Light $$CL_{A,2021}$$ C L A , 2021 ( $$CL_{A\,2.0}$$ C L A 2.0 ) has solved the disadvantage of $$CS_{2018}$$ C S 2018 , especially for the interrupted point between warm and cold white (about $$3710\,K$$ 3710 K ) or the junction between negative and positive signal of the opponent channel ( $$B -(L+M)$$ B - ( L + M ) ). 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. |
| first_indexed | 2024-03-09T15:11:10Z |
| format | Article |
| id | doaj.art-cbd2f5231b554f8ab73dd0e0c43d4217 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-09T15:11:10Z |
| publishDate | 2023-09-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-cbd2f5231b554f8ab73dd0e0c43d42172023-11-26T13:21:27ZengNature PortfolioScientific Reports2045-23222023-09-0113111210.1038/s41598-023-41371-3Numerical correlation between non-visual metrics and brightness metrics—implications for the evaluation of indoor white lighting systems in the photopic rangeTran Quoc Khanh0Trinh Quang Vinh1Peter Bodrogi2Department of Electrical Engineering and Information Technology, Laboratory of Adaptive Lighting Systems and Visual Processing, Technical University of DarmstadtDepartment of Electrical Engineering and Information Technology, Laboratory of Adaptive Lighting Systems and Visual Processing, Technical University of DarmstadtERCO GmbHAbstract From the beginning of the $$21\textrm{st}$$ 21 st 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 ( $$CS_{2018}$$ C S 2018 , $$CS_{2021}$$ C S 2021 ), Melanopic Equivalent Daylight ( $$D_{65}$$ D 65 ) 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. $$CS_{2021}$$ C S 2021 with the improvement of Circadian Light $$CL_{A,2021}$$ C L A , 2021 ( $$CL_{A\,2.0}$$ C L A 2.0 ) has solved the disadvantage of $$CS_{2018}$$ C S 2018 , especially for the interrupted point between warm and cold white (about $$3710\,K$$ 3710 K ) or the junction between negative and positive signal of the opponent channel ( $$B -(L+M)$$ B - ( L + M ) ). 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.https://doi.org/10.1038/s41598-023-41371-3 |
| spellingShingle | Tran Quoc Khanh Trinh Quang Vinh Peter Bodrogi Numerical correlation between non-visual metrics and brightness metrics—implications for the evaluation of indoor white lighting systems in the photopic range Scientific Reports |
| title | Numerical correlation between non-visual metrics and brightness metrics—implications for the evaluation of indoor white lighting systems in the photopic range |
| title_full | Numerical correlation between non-visual metrics and brightness metrics—implications for the evaluation of indoor white lighting systems in the photopic range |
| title_fullStr | Numerical correlation between non-visual metrics and brightness metrics—implications for the evaluation of indoor white lighting systems in the photopic range |
| title_full_unstemmed | Numerical correlation between non-visual metrics and brightness metrics—implications for the evaluation of indoor white lighting systems in the photopic range |
| title_short | Numerical correlation between non-visual metrics and brightness metrics—implications for the evaluation of indoor white lighting systems in the photopic range |
| title_sort | numerical correlation between non visual metrics and brightness metrics implications for the evaluation of indoor white lighting systems in the photopic range |
| url | https://doi.org/10.1038/s41598-023-41371-3 |
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