How can machine learning be used to treat and heal wounds? This is what a recent study published in npj Biomedical Innovations hopes to address as a team of researchers investigated how using a portable healing device combining machine learning and bioelectronics could provide more efficient and faster healing. This study has the potential to help scientists, medical professionals, and the public better understand the benefits of portable healing devices, specifically for rural communities.
For the study, the researchers introduced “a-Heal”, which is a portable and wearable device designed to analyze the healing stage of each patient and provide a suitable treatment, whether it’s medication or using an electric field to speed up wound closure. Not only is a-Heal portable and wireless, but it can be controlled through a laptop and even connect to any local Wi-Fi network.
For the experiments, the researchers used a-Heal on animals and monitored their progress over several weeks. The device works by using a tiny camera and AI image analysis to observe the healing stage and determine the best treatment. In the end, the researchers found that a-Heal contributed to faster healing times, decreased inflammation, and improved tissue regeneration.
Image of a-Heal. (Credit: Rolandi et al)
“It’s essentially a microscope in a bandage,” said Dr. Mircea Teodorescu, who is an associate professor of electrical and computer engineering at UC Santa Cruz and a co-author on the study. “Individual images say little, but over time, continuous imaging lets AI spot trends, wound healing stages, flag issues, and suggest treatments.”
Going forward, the team aspires to advance a-Heal by enabling it to observe and treat chronic and infected wounds, as opposed to simple wounds that were examined for this study.
How will a-Heal help provide portable healing in the coming years and decades? Only time will tell, and this is why we science!
As always, keep doing science & keep looking up!
Sources: npj Biomedical Innovations, EurekAlert!