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

OBJECTIVE: To explore the possibility of an automatic grading algorithm to detect and quantify, from selfie pictures, the subtle changes of facial signs brought by the application of a foundation. MATERIAL AND METHODS: A total of 270 Japanese differently aged women (30-54y) living in four different Japanese cities took selfies before, immediately and 5 h after having applied their own foundation, with their own routine. RESULTS: The analysis of 810 selfie pictures revealed (3 times × 270 women) that, prior to applications, all women presented a low grade of facial ageing. In most cases, the severities of less marked facial signs were detected and quantified, found affected by routine at different extents in all age-classes, but more intensely in the older age-class (45-54y) despite their more pronounced signs in bare skin status. In contrast, periorbital wrinkles were detected as more severe in all age-classes at both timing, that is, immediately and 5 h post-application as well as Nasolabial folds 5 h post-application. The amplitude of these positive or negative changes, although found of low amplitude, as decimals of the initial grades, was significantly detected. CONCLUSION: This automatic system appears apt at grading subtle changes in facial ageing signs brought by a foundation and could be a valuable help to the consumers of make-up products, in refining their individual procedure to obtain a more personalized desired facial appearance.

OBJECTIF: Explorer la possibilité pour un algorithme de scorage automatique des signes faciaux de détecter et quantifier sur la base de photographies 'selfies', les changements subtils apportés par l'application et la tenue de fonds de teint. MATÉRIEL ET MÉTHODES: 270 femmes japonaises âgées de 30 à 54 ans et vivant dans 4 villes différentes ont pris des selfies sur la base de leur smartphone avant, immédiatement et 5 heures après avoir appliqué leurs routines cosmétiques incluant leur propre fond de teint. RÉSULTATS: L'analyse des 810 selfies (3 temps×270 femmes) a révélé que, avant application, la plupart des femmes présentent des grades faibles de vieillissement facial. Dans la plupart des cas, les sévérités des signes les moins marqués, détectés et quantifiés, a été trouvée affectée à différents niveaux dans toutes les classes d'âge, mais plus intensément pour les volontaires les plus âgées (45 à 54 ans) en dépit de leurs valeurs plus élevées sur peau nue. A contrario, les rides péri-orbitales ont été mesurées comme plus sévères dans toutes les classes d'âge à tous les temps, c'est-à-dire immédiatement et 5 heures apprès application du fond de teint tandis que le sillon nasogénien a été observé comme plus sévère 5 heures après application. L'amplitude de ces changements positifs ou négatifs, bien que faible avec des valeurs décimales des grades initiaux, a été significativement détectée. CONCLUSIONS: Le système de scorage automatique apparaît capable d'évaluer des changements subtils dans les signes de vieillissement faciaux apportés par l'application de fonds de teint et se révèle une aide intéressante aux consommateurs de produits de maquillage pour affiner leurs routines individuelles afin d'obtenir des résultats plus personnalisés sur l'apparence désirée.

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.

OBJECTIVES: To evaluate the potency of a new skin hydration sensor patch in the fast self-recording of skin hydration. MATERIAL AND METHODS: The Skin Hydration Sensor Patch (SHSP) turns the user's smartphone into a wireless skin moisture measuring device. The SHSP combines a capacitive measurement unit and Near Field Communication technology (NFC) for transmitting data and energy. The probe is fixed onto the back of the smartphone and pressed to the skin for a few seconds where the application immediately calculates the capacitance value. Once recorded, the probe is then immediately taken off from the skin. In a first study, this system was compared to the Corneometer® technique, in vivo, on various skin sites of 23 healthy French women. In a second study, 20 women with moderate dry skin on face and forearm self-recorded, through the SHSP the changes in skin hydration induced by a Xanthan gel containing 3% (w/w) of Glycerol, along 24 hours. A questionnaire based on 5 types of questions was established to be filled by subjects about their perception of the use of this new system. RESULTS: In the first study, the values recorded by the SHSP were found highly correlated with those provided by the Corneometer® . The second study allowed to observe significant differences in skin hydration of both sites at all times, as compared to values obtained before the application of the gel. Differences between both sites were observed, the face being less hydrated than forearm. From a practical aspect, the self-recordings on the face show a higher variability (approx. 10% than those of the forearm). The questionnaire led to positive answers on almost all points. CONCLUSION: This SHSP appears as a promising approach in the field of connected skin-related devices. As such, it opens or enlarges a new paradigm in the relationships between a consumer and a cosmetic product.

Developing an Artificial Intelligence (A.I)-based descriptor of facial appearance that fits with the assessments of makeup experts.

OBJECTIVE: To develop an A.I-based automatic descriptor that detects and grades, from selfie pictures, 23 facial signs, hairs included, as a help to making-up procedures. MATERIAL AND METHODS: The selfie images taken in very different conditions by 3326 women and men were used to create (90% of dataset) and validate (10% of dataset) a new algorithm architecture to appraise and grade 23 different facial signs such as lips, nose, eye color, eyebrows, eyelashes, and hair color as defined by makeup artists. Each selfie image was annotated by 12 experts and defined references to train Artificial Intelligence (A.I)-based algorithm. RESULTS: As some the 23 signs present a continuous or discontinuous feature, these were analyzed by two different statistical approaches. The results provided by the automatic descriptor system were not only in good agreement with the expert's assessments but were even found of a better precision and reproducibility. This automatic descriptor system has proven a good and robust accuracy despite the very variable conditions in the acquisition of selfie pictures. CONCLUSION: Such automatic descriptor system seems providing a valuable help in making-up procedures and may extend to other activities such as Skincare or Haircare. As such it should allow large investigations to better evaluate the consumers' needs of esthetical improvements.