New breakthrough in incorporating Artificial Intelligence (AI) in the healthcare field. The Spanish Patent and Trademark Office (OEPM) has granted a "utility model" to the intelligent urinometer developed by the IASalud group at the Universidad Europea. This transdisciplinary project, which facilitates the work of nursing professionals and aids in medical decision-making, has involved students and faculty from the Universidad Europea, as well as doctors from the HLA Universitario Moncloa Hospital.
"The automatic measurement of urine from catheterized patients and its widespread use in hospital clinical settings through data collection paves the way for incorporating the IoMT (Internet of Medical Things) into this area of healthcare," explains Juan José Beunza, director of IASalud at the Universidad Europea. The revolutionary device, whose production cost could be as low as 50 euros, not only detects the urine flow of catheterized patients but, thanks to an infrared barrier, measures the volume of urine in real time, stores the history with a precise date, generates alarms in case of risk, and analyzes colorimetric changes in the urine. In this way, as Dr. Beunza emphasizes, "the data can feed machine learning models that allow the development of intelligent clinical decision support systems."
Currently, urine flow is measured in the Intensive Care Unit (ICU) manually with graduated containers that nursing professionals use to calculate the fluid every hour. In an ICU with 15 beds, about 12 hours a day are dedicated to this task (estimating 2 minutes per hourly measurement), in which errors can occur that delay the detection of kidney failure or other pathologies. The intelligent device designed in the "Sensors" course, led by José Luis Lafuente Carrasco in the Biomedical Engineering degree, measures and analyzes diuresis, sending the results directly to doctors' computers.
With the approval of the "utility model" by the OEPM and the support of the scientific community, the urinometer that integrates AI is emerging as a key tool in the modernization of intensive care. Its implementation not only promises to improve accuracy in patient monitoring but also opens the door to future innovations in the healthcare field, integrating artificial intelligence and the IoMT into clinical decision-making.
