Not all wounds heal at the same pace, and chronic wounds can be especially difficult to treat. Engineers at the University of California, Santa Cruz have created a smart bandage called a-Heal that uses artificial intelligence and bioelectronics to monitor and accelerate healing. The device combines a small camera, machine learning, and therapeutic delivery in one wearable system.
Every two hours, a-Heal captures images of the wound and analyzes them using an AI model. If healing is slower than expected, the system responds by applying either fluoxetine to reduce inflammation or an electric field to stimulate cell migration. This closed-loop approach allows for personalized treatment based on real-time data.
The AI model, developed by Marcella Gomez, uses reinforcement learning to adapt its strategy over time. It learns from each patient’s healing progress and adjusts interventions accordingly. The device also sends updates to a secure web interface, so clinicians can monitor recovery remotely.
Tests conducted with the University of California Davis showed that wounds treated with a-Heal healed about 25 percent faster than those receiving standard care. The device attaches to a regular bandage and operates wirelessly, making it easy to use in both clinical and home settings.
This technology represents a major advance in personalized wound care. By integrating sensing, diagnosis, and treatment into one system, a-Heal could help patients recover faster and reduce the burden on healthcare providers.
Article from UCSC: Smart device uses AI and bioelectronics to speed up wound healing process
Abstract in npj Biomedical Innovations: Towards adaptive bioelectronic wound therapy with integrated real-time diagnostics and machine learning–driven closed-loop control
