Work

Friction and vibration generated during sliding over bare skin correlate with perceived smoothness and moistness

Year: 2025

Type: article

Abstract: Objective Tactile perception of the skin is a key factor for consumers when evaluating skincare products, yet conventional sensory assessments are subjective, costly and often lack clear physical interpretations. This study aims to bridge this gap by developing a tactile sensor that quantifies physical parameters relevant to skin feel and combines these measurements with sensory evaluation. Methods A tactile sensor with a stainless‐steel probe replicating a human fingerprint was developed to measure physical parameters—specifically, vibration and friction—during controlled rubbing on the cheek. Simultaneously, blinded sensory evaluations were performed by assessors rating six attributes: smooth–rough, moisturized–dry, soft–hard (surface), soft–hard (base), elastic–not elastic and oily–not oily. Multiple regression analyses were conducted using vibration features and friction coefficients as independent variables and sensory evaluation scores as dependent variables. Results Regression analysis revealed that perceived smoothness (smooth–rough) was predicted by amplitudes of high‐frequency vibration ( R 2 = 0.708; adjusted R 2 = 0.676). Moistness (moisturized–dry) was best predicted by a combination of high‐frequency vibration amplitude and friction coefficients ( R 2 = 0.584; adjusted R 2 = 0.538). No significant regression models were obtained for the other sensory attributes. Conclusion These findings highlight the potential of objective, instrument‐based tactile measurements to elucidate the physical basis of sensory evaluation terms in skincare. This approach may enhance the training of sensory evaluation panels and improve the consistency and reliability of product assessment, ultimately supporting more effective product development.

Source: International Journal of Cosmetic Science

DOI: 10.1111/ics.70066

Authors: Naoki Saito, Kohei Matsumori, Taiki Kazama, Naomi Arakawa, Shogo Okamoto

Institutions: Shiseido Group (Japan), Tokyo Metropolitan University

Language: English

Topic: Sensory Analysis and Statistical Methods

Subfield: Food Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $3,570