Device uses AI and bioelectronics to speed up wound healing (news.ucsc.edu)

UC Santa Cruz and UC Davis researchers unveiled a wearable system called a-Heal that combines a tiny onboard camera, bioelectronic drug delivery and an AI “physician” to accelerate wound healing. In preclinical models reported in npj Biomedical Innovations, wounds treated with a-Heal closed about 25% faster than standard care. The device images the wound every two hours, compares its stage of healing to an optimal timeline, and—if progress lags—automatically applies a tailored intervention: topical fluoxetine delivered by bioelectronic actuators and/or a controlled electric field shown to boost cell migration. All data are streamed to a secure web interface so clinicians can monitor and adjust treatment remotely, making the system especially promising for patients in rural areas or with limited mobility. Technically, the system is a closed-loop platform: image capture feeds a reinforcement-learning model (the “AI physician”) guided by a Deep Mapper algorithm that quantifies healing stage, learns a linear dynamic model of each patient’s trajectory, forecasts outcomes, and optimizes drug dose and field strength to minimize time-to-closure. This real-time adaptive control is one of the first integrated AI–bioelectronics loops for wound therapy, with implications for jump-starting stalled chronic wounds and for regulated, personalized in-home interventions. The project—DARPA- and ARPA-H–supported—now moves toward testing on chronic/infected wound models and potential clinical translation.