Tracking skin colour and wrinkle changes during cosmetic product trials using smartphone images

Abstract

Background To explore how the efficacy of product trials for skin cosmetics can be improved through the use of consumer‐level images taken by volunteers using a conventional smartphone. Materials and Methods 12 women aged 30‐60 years participated in a product trial and had close‐up images of the cheek and temple regions of their faces taken with a high‐resolution Antera 3D CS camera at the start and end of a 4‐week period. Additionally, they each had “selfies” of the same regions of their faces taken regularly throughout the trial period. Automatic image analysis to identify changes in skin colour used three kinds of colour normalisation and analysis for wrinkle composition identified edges and calculated their magnitude. Results Images taken at the start and end of the trial acted as baseline ground truth for normalisation of smartphone images and showed large changes in both colour and wrinkle magnitude during the trial for many volunteers. Conclusions Results demonstrate that regular use of selfie smartphone images within trial periods can add value to interpretation of the efficacy of the trial.

A 5‐hour follow‐up of the impact on ageing facial signs of some foundations in Japanese women through automatically analysed selfie pictures

“…Emergence of smartphones with high‐resolution camera and powerful hardware is a pathway to new evaluation and monitoring in real life condition, especially in a dynamic way. [7, 8]…”

“…Some methods have been applied successfully to make‐up products assessments [8] demonstrating complementary benefits to less nomad methods in assessing their wear [9].…”

“…Emergence of smartphones with high-resolution camera and powerful hardware is a pathway to new evaluation and monitoring in real life condition, especially in a dynamic way. [7,8] Some methods have been applied successfully to make-up products assessments [8] demonstrating complementary benefits to less nomad methods in assessing their wear [9]. Specific algorithms were developed and validated by experts/dermatologists [10][11][12] for evaluating facial signs, based on referential Skin Aging Atlases [13][14][15][16][17], and the valuable use of standardized photographic scales in clinical evaluations has been previously demonstrated [18][19][20][21].…”

Comparing the self‐perceived effects of a facial anti‐aging product to those automatically detected from selfie images of Chinese women of different ages and cities

“…With regard their application to the Skincare domain, a recent study, 10 carried out under well-controlled conditions, determined how selfie images contribute to a more precise interpretation of the efficacy of a cosmetic product through a new type of normalization. The latter used an Artificial Intelligence (A.I) methodology processed by algorithms issued from deep learning in either medical or cosmetic applications.…”

Skin moisture assessment using Hydration Sensor Patches coupled with smartphones via Near Field Communication (NFC). A pilot study with the first generation of patches that allow self‐recordings of skin hydration

“…This approach aims at understanding, in sincere and accurate ways, the modifications of the skin brought by various factors such as circadian rhythm, 11 hormonal status, 12 exposome, 13 and influence of hydrating/moisturizing products. 7,8 This interactive way of measuring some cutaneous parameters is now made possible through selfie smartphones' images comprising A.I-based automatic analysis, [14][15][16] wearable sensors, 17 or nomad devices like GPSkin ® (GPOWER, Seoul, South Korea) for simultaneously recording the skin hydration status and trans-Epidermal Water-Loss (TEWL) on the very same skin area. [18][19][20] The GPSkin ® device, the data of which correlate well with those provided by the Corneometer ® , was previously shown as efficient tool for consumers to assess both their own skin hydration and TEWL, at home.…”