From consistent subjective assessment of skin sensitivity severity to its accurate objective scoring.

BACKGROUND: Sensitive skin (SenS) is a syndrome leading to unpleasant sensations with little visible signs. Grading its severity generally relies on questionnaires or subjective ratings. MATERIALS AND METHODS: The SenS status of 183 subjects was determined by trained assessors. Answers from a four-item questionnaire were converted into numerical scores, leading to a 0-15 SenS index that was asked twice or thrice. Parameters from hyperspectral images were used as input for a multi-layer perceptron (MLP) neural network to predict the four-item questionnaire score of subjects. The resulting model was used to evaluate the soothing effect of a cosmetic cream applied to one hemiface, comparing it to that of a placebo applied to the other hemiface. RESULTS: The four-item questionnaire score accurately predicts SenS assessors' classification (92.7%) while providing insight into SenS severity. Most subjects providing repeatable replies are non-SenS, but accepting some variability in answers enables identifying subjects with consistent replies encompassing a majority of SenS subjects. The MLP neural network model predicts the SenS score of subjects with consistent replies from full-face hyperspectral images (R2 Validation set  = 0.969). A similar quality is obtained with hemiface images. Comparing the effect of applying a soothing cosmetic to that of a placebo revealed that subjects with the highest instrumental index (> 5) show significant SenS improvement. CONCLUSION: A four-item questionnaire enables calculating a SenS index grading its severity. Objective evaluation using hyperspectral images with an MLP neural network accurately predicts SenS severity and its favourable evolution upon the application of a soothing cream.

Evaluation of a new connected portable camera for the analysis of skin microrelief and the assessment of the effect of skin moisturisers.

BACKGROUND: Silicone replicas and non-contact methods are effective methods to analyse the micrometric scale of the skin microrelief. Yet, they imply data capture in research facilities. The capabilities of a new connected portable camera were evaluated to analyse microrelief under nomadic conditions, also studying the effect of moisturisers. MATERIALS AND METHODS: 3D depth maps were constructed using shape-from-shading algorithms. Roughness heterogeneity (Spa) was computed, and skin profiles were extracted to calculate roughness amplitude (Ra, Rq), as well as furrows/plateaus characteristics. Validation of the connected camera was performed on tanned cowhide leather and on the inner forearm skin of a single subject. The forearms of 18 subjects (23-60 years old) were also evaluated. While living their regular life, they self-performed triplicate acquisitions at various times. The effects of a placebo and of cream containing moisturisers-saccharide isomerate, urea or xylitylglucoside-anhydroxylitol-xylitol-were investigated, using untreated control skin as a reference. RESULTS: Validation of the device on leather and forearm skin shows high repeatability. The 18 subjects show the known correlation between age and changes in microrelief. While testing formulas, 8 h after a single application, all decreased Spa (-1.6/-2.1 folds). Only saccharide isomerate and xylitylglucoside-anhydroxylitol-xylitol decreased Ra (-2.4/-2.8 folds). The sectional area of plateaus was reduced from -1.5 (urea) to -2.1 folds (xylitylglucoside-anhydroxylitol-xylitol). The height of plateaus is also decreased by all moisturisers, from -1.5 (urea) to -2.1 folds (xylitylglucoside-anhydroxylitol-xylitol). CONCLUSION: This novel camera device enables microrelief analysis under nomadic conditions, allowing monitoring its changes along the day and upon moisturisers' application.