Two newly developed indices evaluating facial skin aging

Area of Science:

• Dermatology
• Biometrics
• Medical Imaging

Background:

• Traditional skin aging assessment relies on subjective characteristics like wrinkles and spots, often using pattern recognition.
• Emerging methods include facial landmark detection and machine learning for age prediction.
• There's a need for objective, quantitative measures of facial aging.

Purpose of the Study:

• To develop and validate two novel indices for quantifying facial aging severity.
• To assess the correlation of these indices with chronological age and facial skin characteristics.
• To determine if these indices offer distinct insights into facial aging compared to conventional measures.

Main Methods:

• Defined two indices based on ratios of facial distances (bizygomatic/bigonial and mandibular degrees) from 2D frontal images.
• Evaluated indices' ability to reflect age-related downward facial deformation.
• Conducted correlation and association tests with age and facial skin features, including age-adjusted analyses.

Main Results:

• The proposed indices demonstrated strong correlations with chronological age (r=0.557 and 0.464).
• Indices also correlated with specific facial skin characteristics.
• Age-adjusted associations between indices and skin features were weak or non-significant, suggesting distinctiveness.

Conclusions:

• Introduced two novel, quantitative indices for facial aging evaluation using frontal face images.
• These indices show significant correlation with age and key facial skin features.
• The new indices serve as differentiated indicators of facial aging, distinct from general skin feature measurements.