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<p>This study used expert assessment, consumer perception, and noninvasive measurements of skin physiological parameters to develop a mathematical model for characterizing facial skin laxity in Chinese females, providing the scientific basis for personalized beauty and skin-firming strategies. The study involved 64 Chinese females (18–60&#xa0;years) whose facial regions were imaged using VISIA-CR. Five experts assessed facial skin laxity using VISIA-CR images, while 72 consumers compared paired images to identify higher laxity. Noninvasive measurements of skin elasticity and other parameters were taken. The data were analyzed using Bradley-Terry analysis and support vector machine regression modeling. Consistent with expectations, facial skin laxity was negatively correlated with skin elasticity R2 values and positively correlated with skin elasticity F4 values. A novel Facial Skin Laxity Index (<i>FSLI</i>) was introduced to evaluate product efficacy in reducing laxity. Facial skin laxity can be characterized and quantified using a combination of expert assessments, consumer perceptions, and noninvasive measurements. The <i>FSLI</i> enables precise evaluation of product performance in improving facial skin laxity.</p>

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A comprehensive model for characterizing Chinese female facial skin laxity by expert assessment, consumer perception, and noninvasive skin physiological parameters

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月14日

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  • Yusha Zi,
  • Jiaqi Zhang,
  • Qi Liu,
  • Sisi Chang,
  • Wei Liu,
  • Hua Zhao,
  • Jianwei Liu

摘要

This study used expert assessment, consumer perception, and noninvasive measurements of skin physiological parameters to develop a mathematical model for characterizing facial skin laxity in Chinese females, providing the scientific basis for personalized beauty and skin-firming strategies. The study involved 64 Chinese females (18–60 years) whose facial regions were imaged using VISIA-CR. Five experts assessed facial skin laxity using VISIA-CR images, while 72 consumers compared paired images to identify higher laxity. Noninvasive measurements of skin elasticity and other parameters were taken. The data were analyzed using Bradley-Terry analysis and support vector machine regression modeling. Consistent with expectations, facial skin laxity was negatively correlated with skin elasticity R2 values and positively correlated with skin elasticity F4 values. A novel Facial Skin Laxity Index (FSLI) was introduced to evaluate product efficacy in reducing laxity. Facial skin laxity can be characterized and quantified using a combination of expert assessments, consumer perceptions, and noninvasive measurements. The FSLI enables precise evaluation of product performance in improving facial skin laxity.