Mitigation of Pressure Injuries Utilizing Machine Learning and an Inertial Wearable

Pressure ulcers, or pressure injuries, are localized areas of skin and/or underlying tissue necrosis that typically occur over bony prominences due to a prolonged pressure or friction. They can lead to serious morbidity and mortality, emphasizing the need for prevention. This project utilizes a database of demographic and clinical features of a large patient data set and applies machine learning to determine the higher risk patients, coupled with a complimentary device to assist in the prevention of pressure injuries. A complementary monitoring system is built based on an inertial wearable utilizing an inexpensive microcontroller and a gyroscope. The combined approach is evaluated, fine-tuned, and assessed based on different performance metrics.