Most age-related changes that appear on the surface of facial skin are caused by changes within the skin. Therefore, analyzing the internal state of the skin could make it possible to provide evidence-based counseling, which could offer benefits to customers. However, it is difficult to perform simple analyses of the inner condition of the skin, and conventional methods of analysis generally require costly laboratory equipment. Therefore, we used multiple regression analysis to create an estimation formula to calculate the skin's inner structure feature values based on skin surface feature values, which can be easily obtained. As objective variables, we used the number of dermal papillary structures and a score for dermal fibrous structure clearness. As explanatory variables, we used the feature values for sulci cutis and crista cutis characteristics, color characteristics, and frequency characteristics, as calculated from data including skin images. The concordance rate between corresponding before- and after-scores obtained with our novel estimation formula and the actual scores based on measured values for the number of dermal papilla structures was 100% and that for the clearness of dermal fibrous structures was 95%. These results demonstrate that skin surface feature values, which can be obtained using a simple device such as a microscope, can be used to estimate the condition of the inner structures of the skin, including the number of dermal papillary structures and the clearness of dermal fibrous structures.
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