Skin Relevant Biomaterials from Wound Healing, Medical Aesthetics, Flexible Electronics to Artificial Intelligence and Beyond.

This research line looks at combining skin‑compatible biomaterials with flexible electronics, artificial intelligence, and modern medical‑image processing. It aims to track how biomaterials break down, how wounds heal, and how new tissue forms, using non‑invasive imaging methods. Machine‑learning and deep‑learning models will be used to examine high‑resolution medical images and sensor data collected from flexible electronic patches. The workflow includes cleaning raw sensor signals, pulling out space‑time features from thermal, optical, or ultrasound images, and classifying wound conditions so that treatments can be fine‑tuned. The work also studies how AI can predict the interaction between biomaterials and tissue and how to model their mechanical match. The project provides a step‑by‑step

approach for: – simulating how sensors contact skin, – measuring signal‑to‑noise ratios in flexible‑electronic readouts, – testing image‑segmentation algorithms that detect wound edges. Overall, the framework offers a practical guide for researchers who want to link biomaterial science, flexible sensor networks, and smart diagnostic tools in medical aesthetics and regenerative medicine.

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