Nocturnal enuresis (NE), or bedwetting, affects up to 20% of 5-year-old children and 5% of 10-year-old children. AI technology could soon provide families with an effective method for exploring and treating this common issue, according to a new study published in Medical & Biological Engineering & Computing.
The study’s authors noted that catheterization is how an individual’s bladder volume is typically measured, but this process is “invasive, uncomfortable to the patient and introduces the risk of infection and trauma.” Numerous non-invasive options do exist for bedwetting, but they aren’t “satisfactory in alleviating the predicaments of children with NE.”
Noting that ending NE can reduce stress in both children and their families, the researchers aimed to develop an advanced mechatronics device equipped with ultrasound (US) sensors that stops the problem through a “pre-void alarm.” Once the prototype of their MyPad device was complete, they worked directly with children suffering from NE and their families to learn more about how they could improve it. Tests were also performed to ensure the device was comfortable to wear, and a wireless US device was developed to place within the MyPad. The final product was designed to warn users via a smartphone application when the child may soon need to use the bathroom.
“This device will be unique in that it recognizes the warning signs of a pending emptying of the bladder via tracking expansion of the bladder volume over time, and will wake the patient up in time to prevent it,” wrote first author Kaya Kuru, University of Central Lancashire in the UK, and colleagues. “This process is customized or tuned to an individual patient’s bladder volume trigger point. This more accurate advanced warning system will help the children to alter their behavior over time, reducing the frequency of NE through learning bladder control over time.”
Overall, though the team still has work to do before the device is finalized, they found that their MyPad was successful with phantoms and human volunteers. Next steps include refining the device so that it is more effective and running additional tests with volunteers.
Michael has more than 16 years of experience as a professional writer and editor. He has written at length about cardiology, radiology, artificial intelligence and other key healthcare topics.