Predicting slips and falls considering required and available friction.

This study investigated the relationship among measurements of friction, the biomechanics of gait, and actual slip and fall events. The goal was to develop a method for estimating the probability of slips and falls based on measurements of available friction and required friction. Five subjects wearing safety harnesses walked down a ramp at various angles with either a tile or carpeted surface under dry, wet or soapy conditions. Ramp angles of 0 degree, 10 degrees and 20 degrees were used to vary the shear and normal foot force requirements. The dynamic coefficient of friction (DCOF) of shoe, floor surface and contaminant interfaces was measured. Required friction was assessed by examining the foot forces during walking trials when no slips occurred. Slips with recoveries and slips resulting in falls were recorded and categorized using a force plate and high-speed video camera. These data were then incorporated into a logistic regression to model the probability of a slip or fall event occurring based on the difference between the COF required by the foot forces generated and the measured DCOF. The results showed that the number of slip and fall events increased as the difference between the required COF and the measured DCOF increased. The logistic regression model fit the data well, resulting in an estimate of the probability of a slip or fall event based on the difference between the measured and required friction. This type of model could be used in the future to evaluate slip resistance measurement devices under various environments and assist in the design of safer work environments.