Ms. Minami Shinkawa, MHS, RN, PHN in department of gerontological nursing/wound care management
Early detection and risk assessment are essential for preventing pressure injuries (bedsores), which are commonly seen in elderly individuals. Traditional risk assessment scales rely heavily on subjective judgment and therefore face challenges in reliability. This study aimed to develop a novel, non-invasive, and non-restrictive method for estimating changes in skin temperature—such as those caused by ischemia or inflammation—by placing temperature sensors underneath bed sheets. In a simulation experiment, we created an artificial skin model to mimic skin temperature changes and evaluated the accuracy of temperature estimation using machine learning models (Extra Trees, LGBM, and linear regression). Additionally, in a study involving healthy participants, we demonstrated that skin temperature at the sacrum could be estimated from temperature sensors placed beneath the sheets (R² = 0.8145). Our findings suggest that time-series changes in skin temperature can be accurately and non-invasively estimated through a combination of interface pressure sensors and under-sheet temperature sensors. The outcomes of this study hold promise for early detection of pressure injury risks and for application in personalized nursing care.
Access the full paper here: https://pubmed.ncbi.nlm.nih.gov/39876615/