In-Vivo Skin 3-D Surface Reconstruction and Wrinkle Depth Estimation using Handheld High Resolution Tactile Sensing

2025-09-14

AI Summary

Existing 3D skin reconstruction and wrinkle depth quantification methods suffer from limited portability, insufficient resolution, and lack of cross-anatomic validation. To address these limitations, we propose a handheld, high-resolution tactile imaging system integrating GelSight-based tactile sensing, a custom elastomeric gel, force-feedback pressure control, and a learning-enhanced surface reconstruction algorithm. The system enables in vivo, multi-site (e.g., periorbital, forehead, dorsum of hand) 3D skin surface reconstruction and micrometer-precision wrinkle depth quantification. Validation on synthetic wrinkle phantoms yields a mean absolute error of only 12.55 μm; critically, this is the first study to perform clinical, multi-site validation on human subjects. Longitudinal experiments demonstrate statistically significant reductions in wrinkle height across all three anatomical sites following moisturization intervention (p < 0.01). This work establishes a portable, objective, and reproducible quantitative tool for dermatological assessment and cosmetic efficacy evaluation.

Technology Category

• Computer Vision: 3D Computer Vision
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Humans and AI: Interaction Techniques and Devices

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Three-dimensional (3-D) skin surface reconstruction offers promise for objective and quantitative dermatological assessment, but no portable, high-resolution device exists that has been validated and used for depth reconstruction across various body locations. We present a compact 3-D skin reconstruction probe based on GelSight tactile imaging with a custom elastic gel and a learning-based reconstruction algorithm for micron-level wrinkle height estimation. Our probe, integrated into a handheld probe with force sensing for consistent contact, achieves a mean absolute error of 12.55 micron on wrinkle-like test objects. In a study with 15 participants without skin disorders, we provide the first validated wrinkle depth metrics across multiple body regions. We further demonstrate statistically significant reductions in wrinkle height at three locations following over-the-counter moisturizer application. Our work offers a validated tool for clinical and cosmetic skin analysis, with potential applications in diagnosis, treatment monitoring, and skincare efficacy evaluation.

Problem

• Develops handheld 3D skin surface reconstruction device
• Estimates micron-level wrinkle depth across body regions
• Validates tool for clinical and cosmetic skin analysis

Innovation

• Handheld GelSight tactile imaging probe
• Learning-based micron-level reconstruction algorithm
• Force sensing for consistent contact control