Background: After washing hair, prolonged and frequent use of hair dryers to dry hair can cause heat damage to hair fibers. Currently, various hair care products designed to repair heat damage are available in the market.Objective: To establish a model of heat‐damaged hair for evaluating the effectiveness of hair care products that claim to repair such damage.Methods: A blast drying oven was used in this study to expose in vitro hair tresses to 24 h of drying at 60°C, simulating the effects of daily hair drying with a hair dryer for 1 month. The effectiveness of the heat‐damaged model for hair was assessed through microscopic observation and physicochemical testing. Statistical analysis was conducted to compare the cuticle morphology, surface contact angle, water content, mechanical properties, released amount of protein, and tryptophan content of virgin hair, hair dried with a hair dryer over an extended period, and hair from the heat‐damaged model.Results: Compared to virgin hair, hair dried daily with a hair dryer for the equivalent of 1 month exhibits lifted cuticles. The surface contact angle, water content, mechanical properties, and tryptophan content are significantly reduced, while the released amount of protein is significantly increased. In the heat‐damaged hair model, these indicators are either further worsened or show no significant difference compared to hair dried with a hair dryer for 1 month.Conclusion: The heat‐damaged model for hair is capable of simulating the damage inflicted on hair by daily use of a hair dryer for a period of 1 month, leading to even more severe damage effects.

This study comprehensively integrated expert assessment with measurements of hair parameters to investigate the voluminous hair greasiness content for maintaining voluminous hair in Chinese women with different hair texture types, aiming to provide preliminary reference for subsequent research on personalized hair care. The study cohort comprised 128 Chinese females aged 18 to 60 years. Frontal and posterior images of the participants were captured using a digital camera. Three expert assessors evaluated hair volume based on the images. Concurrently, measurements were conducted for hair greasiness content, hair area, flyaway hair area, crown height, and crown angle. A novel Hair Volume Index (HVI) is proposed, and a corresponding machine learning-driven automated calculation model is constructed to achieve objective quantitative evaluation of hair image. Furthermore, ROC curve analysis was used for exploratory assessment of the voluminous hair greasiness content across different hair texture types.