Early Detection and Prevention of Pressure Injury and Ulcer in Prolonged Care

This project aims to address the persistent issue of pressure injuries—commonly known as pressure ulcers or bedsores—that frequently affect immobile patients in long-term care or intensive care settings. These injuries, though largely preventable, result in significant health complications, extended recovery periods, and increased healthcare costs. The project proposes an integrated, technology-driven approach combining clinical risk assessments, smart wearable devices, and machine learning algorithms to detect and prevent these injuries proactively. Standard tools such as the Braden or Norton Scale assess risk levels, while sensor-embedded mattresses and wearable devices monitor pressure distribution, moisture, and patient movement in real time. This data is analyzed using predictive models to detect early signs of pressure injuries, triggering alerts for caregivers and enabling timely intervention. The system also includes a decision-support module that recommends individualized care strategies such as repositioning schedules and skincare routines, with all data integrated into electronic health records for comprehensive documentation and continuous care optimization. Expected outcomes include a significant reduction in pressure injury incidence, improved patient comfort and safety, enhanced caregiver responsiveness, and reduced healthcare burden. Overall, the project represents a shift from reactive treatment to proactive prevention, aiming to ensure safer, more dignified, and cost-effective care for patients requiring prolonged medical attention.