An IoT-based Pressure Injury Prevention System

Abstract

Pressure injuries cost the medical system billions of dollars every year. The current way to prevent pressure injuries is inefficient and labor-intensive. The thesis conducted market research about pressure injuries and summarized market segments and user needs. An IoT device is designed and prototyped for caregivers to help pressure injury prevention by tracking, logging, and monitoring a patient’s activity. The system includes an innovative smart fabric-based sensor mat to measure sit- ting and lying pressure between a human body and a mattress or sitting surface, a battery-powered control and data transmission unit, and a suite of cloud-based software functions such as data transmission, storage database, analytical algorithms, and a data portal. The system measures pressure in real-time and uses machine learning to interpret a patient’s posture, and logs the posture history in a cloud database. By using the system, caregivers can manage multiple patients’ reposition schedules easily and remotely with a smartphone or tablet. Active patients’ self-repositioning can be logged accurately with the system, so their care schedules can be less labor-intensive for caregivers. The system increases the overall operating efficiencies for the caregivers and the care quality for wheelchair and bed-bound patients.