L'Oréal Research and Innovation, Clichy, France.
ModiFace-A L'Oréal Group Company, Toronto, Ontario, Canada.
Skin Res Technol. 2022 Jul;28(4):596-603. doi: 10.1111/srt.13153. Epub 2022 May 1.
To evaluate the capacity of the automatic detection system to accurately grade, from smartphones' selfie pictures, the severity of fifteen facial signs in South African women and their changes related to age and sun-exposure habits.
A two-steps approach was conducted based on self-taken selfie images. At first, to assess on 306 South African women (20-69 years) enrolled in Pretoria area (25.74°S, 28.22°E), age changes on fifteen facial signs measured by an artificial intelligence (AI)-based automatic grading system previously validated by experts/dermatologists. Second, as these South African panelists were recruited according to their usual behavior toward sun-exposure, that is, nonsun-phobic (NSP, N = 151) and sun-phobic (SP, N = 155) and through their regular and early use of a photo-protective product, to characterize the facial photo-damages.
(1) The automatic scores showed significant changes with age, by decade, of sagging and wrinkles/texture (p < 0.05) after 20 and 30 years, respectively. Pigmentation cluster scores presented no significant changes with age whereas cheek skin pores enlarged at a low extent with two plateaus at thirties and fifties. (2) After 60 years, a significantly increased severity of wrinkles/texture and sagging was observed in NSP versus SP women (p < 0.05). A trend of an increased pigmentation of the eye contour (p = 0.06) was observed after 50 years.
This work illustrates specific impacts of aging and sun-exposures on facial signs of South African women, when compared to previous experiments conducted in Europe or East Asia. Results significantly confirm the importance of sun-avoidance coupled with photo-protective measures to avoid long-term skin damages. In inclusive epidemiological studies that aim at investigating large human panels in very different contexts, the AI-based system offers a fast, affordable and confidential approach in the detection and quantification of facial signs and their dependency with ages, environments, and lifestyles.
评估自动检测系统从南非女性的智能手机自拍照片中准确分级十五种面部特征严重程度的能力，以及这些变化与年龄和日晒习惯的关系。
采用两步法基于自拍图像进行研究。首先，在 306 名南非女性（20-69 岁）中评估，这些女性是在比勒陀利亚地区（25.74°S，28.22°E）招募的，她们的年龄变化是由人工智能（AI）为基础的自动分级系统测量的，该系统之前已经由专家/皮肤科医生验证过。其次，由于这些南非参与者是根据她们对日晒的通常行为招募的，即非日晒恐惧症（NSP，N=151）和日晒恐惧症（SP，N=155），并且她们定期和早期使用防晒产品，所以该系统用于描述面部光损伤。
（1）自动评分显示出与年龄相关的显著变化，每十年一阶段，分别在 20 岁和 30 岁后出现下垂和皱纹/纹理（p<0.05）。色素沉着群评分与年龄无关，而脸颊皮肤毛孔在三十岁和五十岁时出现两个平台，略微扩大。（2）60 岁以后，NSP 女性的皱纹/纹理和下垂严重程度明显高于 SP 女性（p<0.05）。五十岁以后，眼轮廓色素沉着增加呈趋势（p=0.06）。
与之前在欧洲或东亚进行的实验相比，这项工作说明了衰老和日晒对南非女性面部特征的具体影响。结果显著证实了避免日晒和采取防晒措施的重要性，以避免长期的皮肤损伤。在旨在调查非常不同背景下的大量人群的综合性流行病学研究中，基于 AI 的系统提供了一种快速、经济实惠且保密的方法，用于检测和量化面部特征及其与年龄、环境和生活方式的依赖性。
