Practical Monte Carlo Simulation Method Highlighting on Tail Probability with Application to Biomechanics Analysis of Pressure Ulcer

Abstract

The Monte Carlo method is a well-known method for calculating uncertainty, but it has the disadvantage of high computational cost because it usually requires 10,000 sampling points. In this paper, a practical sampling algorithm named Stepwise Limited Sampling (SLS) is proposed to obtain both accurate expected values and very accurate tail probability values in the Monte Carlo simulation. This method was then applied to a biomechanics problem concerning the risk prediction of pressure ulcers. It is known that the initial damage that leads to a fatal stage of pressure ulcer occurs in deep muscle, but its location has not been clarified. By modeling assumed damage at the bone-muscle interface in the human buttock as a cutout, and by judging whether the damage propagates or not, sets of material properties of muscle and fat in the tail probability that result in high interface shear strain were obtained as a function of body positioning during nursing.