Wound healing occurs in several stages. From clotting and inflammatory responses to tissue repair and scar formation. This process can be slow or disrupted in patients with acute or chronic wounds, leading to complications, longer recovery times and higher healthcare costs. An interdisciplinary team of engineers from the University of California, Santa Cruz and UC Davis has now developed an innovative wearable device that directly addresses this challenge.
The system, called a-Heal, uses artificial intelligence (AI), bioelectronics and a built-in camera to monitor and actively accelerate the progress of wound healing.
Personalised wound care with AI
The device is attached directly to a standard bandage and functions as a closed-loop system. A built-in camera captures images of the wound every two hours. These photos are then analysed by a machine learning model, which the researchers call the “AI doctor”. This model compares the wound status with a timeline of optimal healing. If healing is found to be lagging behind, the device can automatically initiate treatment, such as:
- Medication: fluoxetine is administered locally via bioelectronic actuators. This drug, known as an antidepressant, promotes wound closure by reducing inflammation and stimulating tissue regeneration.
- Bio-electrical stimulation: the device can generate a gentle electrical field that stimulates cell migration to the wound, thereby accelerating recovery.
This approach makes it possible to dynamically adapt the healing process to the individual patient. Each intervention is followed by new imaging, allowing the system to continuously learn and refine the treatment.
Better outcomes, less burden
The first preclinical results, published in npj Biomedical Innovations, show that wounds treated with a-Heal healed approximately 25 per cent faster than with standard care. This can have a major impact, especially in the case of chronic wounds, which often heal poorly or not at all.
In addition to automated treatment, the device also offers telemonitoring. Images and data, such as healing speed and treatment response, are securely transmitted to a web interface. This allows a doctor to monitor progress remotely and intervene where necessary. This makes the technology particularly suitable for patients in remote areas or people with limited mobility.
AI that grows with the patient
The AI model behind a-Heal uses a form of reinforcement learning. This means that the algorithm continuously learns which treatment combinations promote recovery the most. The model's goal is to minimise healing time and it is “rewarded” when progress is made. In this way, the system develops a patient-specific strategy that adapts as recovery progresses.
The researchers see great opportunities for the application of a-Heal in the treatment of chronic wounds and infections, which often represent a long-term and costly care burden. The combination of AI, bioelectronics and wearable technology offers a promising route to faster, patient-centred and more sustainable wound care.
A-Heal demonstrates how digital innovations can not only monitor processes, but also intervene and treat directly. The device thus marks a step towards a future in which AI-driven solutions complement and improve standard care, with tangible benefits for both patients and the healthcare system.
Innovation in wound healing
Two years ago, researchers at Chalmers University of Technology and the University of Freiburg developed a promising method using electrical stimulation to treat chronic wounds. Their experiments show that skin cells are electrotactic and move in a specific direction within electric fields. By applying this principle, wounds were found to heal up to three times faster than without stimulation.
The study also examined whether this method was effective in wound healing in diabetes, where wound healing is hampered by damage to nerves and blood vessels. It was discovered that electrical stimulation can also accelerate healing in diabetic cells to almost the level of healthy skin cells.
