Pressure ulcers are a great handicap for those who develop one. Pressure ulcers can take a long time to heal especially if detected late. These afflictions require a lot of time from the medical personnel and thus a great amount of money. We aim here to check the impact of continuous measurement on the performance of early pressure ulcer detection algorithms.

To detect pressure ulcers early on we use a simulation of a human buttocks to simulate the reaction of it to pressure. This simulation considers the most recent findings about pressure ulcers. In particular, the phenomenon of muscle stiffening when pressure is applied for a long period of time, and the reperfusion phenomenon. We can then simulate pressure captors on the outside interface of the buttocks to use these measurements for detection. We then determine the best threshold on the measured pressures to create standard algorithms that we compare to novel algorithms using an optimized threshold on a calculated damage based on the pressure measurement of the last 2 hours.

We compare these different algorithms for the early detection of pressure ulcers and show the need to take the measurement variation in time for a better detection. The detection error is improved by 7.3% for balanced classes and 2.7% for a dataset with a majority of healthy buttocks.

We showed that taking the evolution of pressure instead of only instantaneous measurement can improve the early detection of pressure ulcer.