Establishment of a PCA model for skin health evaluation

Abstract

The aim of this study is to establish an objective skin evaluation system through testing skin data and scoring conducted by general dermatology experts. First, 18 data points including left cheek face water evaporation, and left cheek oil content are collected. Second, comprehensive skin information is obtained from volunteers by the mathematical model of principal component analysis (PCA), following scoring the status of the volunteers' skin by dermatology experts. Then, 99 volunteers are randomly divided into two groups, namely model information and test information. Specifically, skin model information is obtained from 80 volunteers, and test information is obtained from 19 volunteers. PCA is used to extract 18 independent variables of skin test data by means of R Studio software, followed by principal component regression by expert scoring and the extracted principal components. Finally, based on the expert score and model score, skin grading classification can be conducted by MATLAB software, in order to intuitively and effectively evaluate skin status.

Statistical analysis of age-related skin parameters

“…The purpose of the present study was to determine the age at which each skin parameter change in order to efficiently prevent skin aging. These indices have been determined by many studies [1]; however, to date, no study has determined the exact age at which the skin condition S66 H. Meng et al / Statistical analysis of age-related skin parameters begins to worsen. Knowledge of this exact age can help guide companies to scientifically develop better skincare products.…”

“…In our previous study [ 1 ], we investigated how skin parameters change during the aging process, determining that the moisture and sebum indices of human skin decrease with age. Different results have been obtained in other studies, for instance Luebberding et al [ 2 ] evaluated age-related changes in skin barrier function, reporting that the moisture index does not significantly decrease with age.…”

Modeling of global skin aging indices among Caucasian and Asian women

“…Thereafter, Nkengne et al 5 propose a skin aging index built from the combination of skin parameters related to wrinkles, firmness, and skin tone of Caucasian women. The main idea behind this approach is that the measured parameters (e.g., wrinkles) are generally related to the same underlying skin condition; principal component analysis (PCA) for skin evaluation is also proposed by He et al 6 to establish a model for skin health evaluation. Most recently, Pardo et al 7 combined several skin-aging attributes to identify three main types of aging.…”