Abstract:

The changes in the appearance of facial skin are an obvious physiological phenomenon in the process of human aging. People are increasingly concerned about the comprehensive skin status. In recent years, newly developed instruments or methods have continuously emerged in the field of non-invasive skin testing. Skin testing and skin photography are the most widely used. Through the analysis of skin testing and skin photography data, objective and true skin data can be obtained to quantify the skin status. Therefore, it is necessary and feasible to establish a new comprehensive skin condition evaluation model to achieve objective and accurate quantification of skin status. Herein, 1,085 female volunteers aged 22-42 were randomly selected from the Chinese Female Skin Testing Database （Beijing Technology and Business University）. The data of skin physiological indicators, VISIA front face and left face cross-polarized light image data （extracted by machine learning algorithms） were collected for correlation analysis between indicators and principal component analysis （PCA） to obtain the core indicators for evaluating individual skin status. KMO test and Bartlett’s test sphere test were used to test the reliability of the principal component data, and the coefficients of each item in the evaluation model were calculated by the method of principal component analysis. There were 10 core indicators related to skin conditions, including age, skin elasticity, skin glossiness, melanin content, heme content, skin moisture content, transdermal water loss, ITA°, sebum secretion, and pores. Eventually, a comprehensive skin status evaluation model was constructed, and the quantified skin score could be obtained by inputting the data of skin physiological indicators into the model. This model gives an objective quantitative judgment on the comprehensive skin condition of women, which avoids the influences of the surrounding environment and the personal subjective consciousness from the naked eye judgment and solves the limitation of time and space for skin evaluation. Collecting relevant index data can be effective on women’s skin evaluation. The research results can provide technical support for comprehensive evaluation of women’s skin status.

Key words: skin status, evaluation model, core indicator, female skin database