Regression Modeling of Spinal Forces during Constrained Lifting Postures

Abstract

Back injuries are the leading cause of lost work time in the U.S. coal mining industry. Miners frequently perform labor in constrained postures, namely stooped and kneeling, due to low seam heights. This work uses regression models coupled with a biomechanical model to predict forces and torques in the spine during lifting tasks performed in constrained postures. Twelve males performed tasks consisting of symmetric lifting, asymmetric lifting, symmetric lowering, and asymmetric lowering. Independent variables included posture (stooped or kneeling), height of lift, and weight of lift. Dependent variables included estimates of spinal compressive forces, spinal shear forces, and torques about the spine. Regression models were developed which predicted the spinal loads based upon the statistically significant independent variables and interactions. These regression models can be used to estimate spinal loads during actual lifting tasks, and these loads can be compared to known limits to determine the relative risk associated with a particular task. In this way, the models can be used to better design manual materials handling tasks that are performed in restricted postures.