The PUMaA System Project (Pressure Ulcer Monitoring and Analysis System) involves the application of artificial intelligence in the form of a computer vision system, supported by machine learning, to recognize skin changes focused on chronic wounds – pressure ulcers. The project aims to assess the degree of pressure ulcers in patients and assist in the professional selection of wound care products, supporting healthcare professionals in monitoring (and statistics) of patients/clients. The planned solution, utilizing AI (Artificial Intelligence) and ML (Machine Learning) technologies, will help in more accurate patient diagnoses, improve predictions of future health status, and recommend better treatment methods.

W chwili obecnej projekt dobiega końca w zakresie fazy B+R . Posiadamy rozwiązanie umożliwiające rozpoznanie zaawansowania odleżyny z dużą pewnością, umozliwiającą na oddanie aplikacji w charakterze doradcy, chociaż oczywiście nie aplikacja nie zastąpi prawdziwego lekarza czy doświadczonej pielęgniarki, to jednak może być pomocna zwłaszcza u osób nie mających żadnego doświadczenia z ranami przewlekłymi.

The Project's Genesis

Pumaa techCurrently, diagnosing skin changes requires extensive expertise in the field of medicine. Diagnosis is often a tedious, time-consuming, and costly process, and most importantly, it is frequently delayed. The number of experts in the field of chronic wound care is disproportionate to the number of individuals in need of care, putting healthcare personnel under pressure and often delaying patient diagnosis. Our team, which includes specialists who professionally provide long-term patient care and specialize in the care and monitoring of chronic wounds, recognized this issue.

The project is based on a group of experts from technical universities who, together with medical specialists, developed the concept of automating the diagnosis of the health status of patients with chronic wounds.