Exploring In Vivo Skin Mechanics: A Multi-Faceted Approach Using 3D Digital Image Correlation

Skin movement plays a critical role in how we interact with the world—conveying texture, protecting against harm, and fostering emotional connection. Just as it helps us perceive our surroundings, skin movement can also reveal information about our bodies, such as hydration or wound healing. A deeper understanding of skin mechanics can support advances in diagnostics, therapeutics, personalized medicine, and haptic interface design. Yet characterizing skin in vivo remains challenging due to its layered structure, anisotropy, and variability across individuals and body regions. Most existing techniques, such as indentation, myotonometry, or elastography, capture static or localized behavior, limiting their ability to assess dynamic deformation during natural movement. To bridge this gap, this work develops and applies a non-invasive, high-resolution imaging approach using 3D digital image correlation (3D-DIC) to quantify skin surface deformation in tactile and clinical contexts. The system is first optimized for in vivo use with bio-safe speckling methods, adaptable multi-camera configurations, and custom analysis pipelines that preserve natural tissue behavior. It is then applied to tactile perception studies, where touch sensitivity is commonly assessed using thin monofilaments that bend at known forces. While such tests help identify sensory impairment by measuring detection thresholds, they do not measure the skin’s mechanical response—despite the fact that mechanoreceptors respond to strain rather than force alone. To address this, fingertip deformation is captured in response to von Frey monofilaments spanning perceptual thresholds. The results show that 3D-DIC resolves displacement and strain patterns corresponding to just-noticeable differences at absolute detection and discrimination thresholds. Next, to objectively assess soft tissue mobility—a key aspect often evaluated subjectively in chronic musculoskeletal pain—eleven strain-based biomarkers are derived from skin surface deformation measured during a standardized soft tissue manipulation (STM) lateral stretch assessment. Designed to capture clinically relevant indicators of soft tissue mobility, the biomarkers successfully identify individual-specific directional and bilateral differences that align with anatomical asymmetries and self-reported pain. When evaluated before and after intervention, the biomarkers demonstrate sensitivity to changes in tissue mobility, with greater changes observed on the more painful side in participants with asymmetric pain. These findings are consistent with the expectation that more restricted tissue exhibits reduced mobility and may respond more markedly to soft tissue manipulation, reinforcing the potential of these biomarkers as objective measures to augment clinical practice. Together, this work introduces a powerful optical imaging framework for quantifying skin deformation in vivo, enabling objective assessment of touch, tissue mobility, and therapeutic outcomes across clinical and technological domains.