AI 기반 디지털 피부분석 시스템을 활용한 20대 피부특성 분석과 셀프케어 프로그램 개선방안
Analysis of Skin Characteristics in 20s and Improvement of Self-care Programs Using AI-based Digital Skin Analysis System
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초록
(Purpose) The purpose of this study is to propose a self-care program for college students in their 20s by measuring their skin and analyzing skin characteristics according to skin type using an AI-based digital skin analysis system that applies deep learning technology and skin analysis algorithm. (Design/methodology/approach) The study included 33 men and women in their 20s. After analyzing the skin type and detailed skin features of each area, a self-care program was proposed. A total of eight skin analysis items were measured, including skin type, pores, elasticity, pigmentation, UV pigmentation, sebum, porphyrin, and moisture. (Findings) The sebum secretion was categorized into oily, dry, and neutral, and the moisture secretion was categorized into hydrated, dehydrated, and hydrated. When analyzing the pore area ratio it was found that more cases were above the average for their age group, which is related to the fact that the skin type is more oily than dry. When analyzing the elasticity area ratio, it was found that more people were below the average for their age group, and 39.4% needed elasticity care above the average for their age group. The pigmentation area ratio shows that the highest percentage of people below the age group average is 54.5%, while the UV pigmentation area ratio is very high at 78.8% above the age group average. The porphyrin ratio was 66.7% above the age group average, which is believed to be due to more oily skin type subjects. (Research implications or Originality) The balance of oil and moisture is crucial for the skin to remain healthy and beautiful through its protective functions. For personalized skin care, it is important to accurately measure and diagnose the skin condition to analyze whether the oil-water balance is appropriate, and to identify pores, elasticity, pigmentation, sebum and water secretion. Compared to other ages, people in their 20s should focus on preventive skin care. With the recent release of smart and diverse digital beauty devices, apps that allow self-diagnosis and care are also being developed. By utilizing an AI-based digital skin analysis system that applies big data, deep learning technology, and skin analysis algorithms, it will be possible to manage skin health more effectively.
Abstract
(Purpose) The purpose of this study is to propose a self-care program for college students in their 20s by measuring their skin and analyzing skin characteristics according to skin type using an AI-based digital skin analysis system that applies deep learning technology and skin analysis algorithm. (Design/methodology/approach) The study included 33 men and women in their 20s. After analyzing the skin type and detailed skin features of each area, a self-care program was proposed. A total of eight skin analysis items were measured, including skin type, pores, elasticity, pigmentation, UV pigmentation, sebum, porphyrin, and moisture. (Findings) The sebum secretion was categorized into oily, dry, and neutral, and the moisture secretion was categorized into hydrated, dehydrated, and hydrated. When analyzing the pore area ratio it was found that more cases were above the average for their age group, which is related to the fact that the skin type is more oily than dry. When analyzing the elasticity area ratio, it was found that more people were below the average for their age group, and 39.4% needed elasticity care above the average for their age group. The pigmentation area ratio shows that the highest percentage of people below the age group average is 54.5%, while the UV pigmentation area ratio is very high at 78.8% above the age group average. The porphyrin ratio was 66.7% above the age group average, which is believed to be due to more oily skin type subjects. (Research implications or Originality) The balance of oil and moisture is crucial for the skin to remain healthy and beautiful through its protective functions. For personalized skin care, it is important to accurately measure and diagnose the skin condition to analyze whether the oil-water balance is appropriate, and to identify pores, elasticity, pigmentation, sebum and water secretion. Compared to other ages, people in their 20s should focus on preventive skin care. With the recent release of smart and diverse digital beauty devices, apps that allow self-diagnosis and care are also being developed. By utilizing an AI-based digital skin analysis system that applies big data, deep learning technology, and skin analysis algorithms, it will be possible to manage skin health more effectively.
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