An objective skin-type classification based on non-invasive biophysical parameters

Area of Science:

• Dermatology and Bioengineering
• Cosmetic Science

Background:

• Skin-type analysis traditionally relies on subjective assessments, hindering objective classification.
• Advancements in cosmetic science and AI dermatology necessitate an objective, data-driven skin-type system.

Purpose of the Study:

• To develop an objective skin-type classification system using only non-invasive bioengineering devices.
• To establish population-specific reference values for the Korean demographic.
• To compare these reference values with existing published data.

Main Methods:

• Utilized data from 434 healthy South Korean adults from the 2018 International Skin Characteristics Data Bank Project.
• Employed eight non-invasive bioengineering devices to measure key biophysical parameters.
• Defined reference points using tertile values associated with unfavorable skin characteristics.

Main Results:

• Proposed a five-category (sensitivity, hydration, oiliness, elasticity, skin tone) and five-subcategory (erythema, roughness, pores, wrinkles, pigmentation) classification.
• Established specific thresholds for sensitive (TEWL > 18.0 g/m²/h or pH > 5.45), dehydrated (< 47.17 A.U.), oily (> 70 μg/cm²), and loose skin (< 0.68 E/mm).

Conclusions:

• This study presents the first comprehensive skin-type classification based solely on non-invasive biophysical parameters.
• The established reference points will be refined with accumulating data and further subdivided by demographic factors.
• The developed classification system provides a robust foundation for future AI-based skin-type analysis.