Version 1
: Received: 9 September 2024 / Approved: 10 September 2024 / Online: 11 September 2024 (00:12:23 CEST)
How to cite:
Parraga, S. P.; Shah, S. C.; Yi, R. C.; Girard, G. S.; Taylor, S. L.; Feldman, S. R. The Effect of Lighting Variability on a Facial Skin Analysis Device. Preprints2024, 2024090822. https://doi.org/10.20944/preprints202409.0822.v1
Parraga, S. P.; Shah, S. C.; Yi, R. C.; Girard, G. S.; Taylor, S. L.; Feldman, S. R. The Effect of Lighting Variability on a Facial Skin Analysis Device. Preprints 2024, 2024090822. https://doi.org/10.20944/preprints202409.0822.v1
Parraga, S. P.; Shah, S. C.; Yi, R. C.; Girard, G. S.; Taylor, S. L.; Feldman, S. R. The Effect of Lighting Variability on a Facial Skin Analysis Device. Preprints2024, 2024090822. https://doi.org/10.20944/preprints202409.0822.v1
APA Style
Parraga, S. P., Shah, S. C., Yi, R. C., Girard, G. S., Taylor, S. L., & Feldman, S. R. (2024). The Effect of Lighting Variability on a Facial Skin Analysis Device. Preprints. https://doi.org/10.20944/preprints202409.0822.v1
Chicago/Turabian Style
Parraga, S. P., Sarah L Taylor and Steven R Feldman. 2024 "The Effect of Lighting Variability on a Facial Skin Analysis Device" Preprints. https://doi.org/10.20944/preprints202409.0822.v1
Abstract
Facial artificial intelligence (AI) skincare applications offer patients simple and effective means of obtaining quantitative information regarding their skin characteristics. Advances in AI may facilitate dermatologic assessments by providing accurate and reliable scores for common skin concerns. The objective of our study was to assess the effect of different lighting on facial characteristic scores produced by an iPad-based AI skin analysis system. Participants were recruited from dermatology clinics. Images were captured using an AI skincare app in different lighting settings: below average lighting (L1), standard room lighting (L2), and enhanced studio lighting (L3). Raw scores produced for twenty facial characteristics were recorded. Higher raw scores indicated better skin health. Scores were compared between the three lighting conditions. Below average lighting had the highest mean raw scores for facial characteristics (79.67 ±10.56). Mean raw scores were lowest for enhanced studio lighting conditions (74.43 ±10.24). The difference in scores produced by the different lighting conditions was not statistically significant (p=0.79). Enhanced studio lighting did not appear necessary as scores were similar without the additional lighting. The application used in our study may serve as a cost-effective and convenient tool both within and outside clinical settings allowing enhanced quantitative analysis of facial characteristics.
Keywords
general dermatology; artificial intelligence; lighting; facial characteristics; assessment
Subject
Medicine and Pharmacology, Dermatology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
