Merging Bioelectronics and Machine Learning for Optimized Wound Healing
Автор: UC Santa Cruz Arts, Lectures, and Entertainment
Загружено: 2026-02-06
Просмотров: 28
Описание:
January Slugs and Steins with Professor Marco Rolandi
The average person experiences one to three wounds each year, leading to an estimated 24 billion wounds globally. Most heal on their own, but many require medical care to avoid infection, scarring, or permanent damage. Traditional wound management relies on standardized protocols that do not adapt to patient differences or the changing state of a wound. Recent progress in bioelectronic wearables and smart bandages now enables individualized wound treatment through sensing, drug delivery, and electrical or light stimulation. Continuous and adaptive therapy remains difficult because no sensor can track all relevant biomarkers in real time. Here, I will discuss machine learning driven bioelectronic strategies for sensing and wound therapy to create a personalized wound therapy that updates in real time depending on the wound stage.
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