As a wound heals, it goes through several stages: clotting to stop bleeding, immune system response, scabbing, and scarring.
A wearable device called "a-Heal," designed by engineers at the University of California, Santa Cruz, aims to optimize each stage of the process. The system uses a tiny camera and AI to detect the stage of healing and deliver a treatment in the form of medication or an electric field. The system responds to the unique healing process of the patient, offering personalized treatment.
The portable, wireless device could make wound therapy more accessible to patients in remote areas or with limited mobility. Initial preclinical results, published in the journal npj Biomedical Innovations, show the device successfully speeds up the healing process.
Designing a-Heal
A team of UC Santa Cruz and UC Davis researchers, sponsored by the DARPA-BETR program and led by UC Santa Cruz Baskin Engineering Endowed Chair and Professor of Electrical and Computer Engineering (ECE) Marco Rolandi, designed a device that combines a camera, bioelectronics, and AI for faster wound healing. The integration in one device makes it a "closed-loop system" -- one of the firsts of its kind for wound healing as far as the researchers are aware.
"Our system takes all the cues from the body, and with external interventions, it optimizes the healing progress," Rolandi said.
The device uses an onboard camera, developed by fellow Associate Professor of ECE Mircea Teodorescu and described in a Communications Biology study, to take photos of the wound every two hours. The photos are fed into a machine learning (ML) model, developed by Associate Professor of Applied Mathematics Marcella Gomez, which the researchers call the "AI physician" running on a nearby computer.
"It's essentially a microscope in a bandage," Teodorescu said. "Individual images say little, but over time, continuous imaging lets AI spot trends, wound healing stages, flag issues, and suggest treatments."
The AI physician uses the image to diagnose the wound stage and compares that to where the wound should be along a timeline of optimal wound healing. If the image reveals a lag, the ML model applies a treatment: either medicine, delivered via bioelectronics; or an electric field, which can enhance cell migration toward wound closure.
The treatment topically delivered through the device is fluoxetine, a selective serotonin reuptake inhibitor which controls serotonin levels in the wound and improves healing by decreasing inflammation and increasing wound tissue closure. The dose, determined by preclinical studies by the Isseroff group at UC Davis group to optimize healing, is administered by bioelectronic actuators on the device, developed by Rolandi. An electric field, optimized to improve healing and developed by prior work of the UC Davis' Min Zhao and Roslyn Rivkah Isseroff, is also delivered through the device.
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