Wound healing involves multiple stages: blood coagulation and hemostasis, immune system response, scab formation and scar formation.
a research team led by Professor Marco Rolandi from the University of California, Santa Cruz, has designed the wearable device "A-Heal", which integrates a camera, bioelectronic technology and AI, aiming to optimize every stage of the wound healing process. This system identifies the healing stage through a miniature camera and AI technology and provides drug or electric field treatment. This system can respond to the patient's unique healing process and achieve personalized treatment.
This portable wireless device makes it easier for patients in remote areas or those with limited mobility to access wound treatment. On September 23rd, the research results published in the journal npj Biomedical Innovations showed that the device could effectively accelerate the wound healing process.
The AI-driven a-Heal device can adjust the treatment plan in real time to accelerate wound healing. Preclinical research results show that it may completely transform the healing process, especially for chronic wounds. Our system comprehensively captures human body signals and optimizes the healing process through external intervention. Rolandi said.
The device uses a miniature camera developed by Mircea Teodorescu, an associate professor at the University of California, Santa Cruz, to take pictures of the wound every two hours. The images were input into a machine learning model developed by Associate Professor Marcella Gomez.
This is essentially a bandage-type microscope. Teodorescu explained, "The information of a single image is limited, but continuous imaging enables AI to identify trends, determine the healing stage, mark problems and provide treatment plan suggestions."
The AI doctor diagnoses the wound stage through images and compares it with the ideal healing timeline. If delayed healing is detected, the machine learning model will initiate treatment: delivering drugs through bioelectronic technology or applying an electric field that promotes the migration of cells to the wound. The AI doctor will determine the optimal dosage and electric field intensity. After the treatment had been carried out for some time, the camera took pictures again, initiating a new round of treatment cycle.
During operation, the device will transmit data such as images and healing rates to a secure network interface, facilitating manual intervention by doctors and precise adjustment of treatment plans. This device can be directly pasted onto commercially available bandages, ensuring convenient and firm use.
To assess its clinical applicability, the team from the University of California, Davis, tested the device in a preclinical wound model. Studies show that wounds treated with a-Heal heal approximately 25% faster than those with standard care. These findings not only highlight the potential of this technology to accelerate the healing of acute wounds, but also hold significant value in restarting the healing process of chronic wounds.
Currently, the research team is exploring the potential of this device to promote the healing of chronic and infected wounds.