Human simulation system for injury assessment due to repetitive loading

Abstract

The subject of this research is to investigate human simulation to predict injuries due to the fatigue of a repetitive loading. This work over the past few years has sought to integrate high-fidelity computational methods for stress/strain analysis, namely finite element analysis (FEA), with biomechanics predictions through digital human modeling and simulation (DHMS). Previous work by this group is a simulation environment called SANTOS®, which enables the prediction of human motion, including all aspects of its biomechanics. The SANTOS environment provides a joint- and physics-based predictive dynamics including a muscle model. Repetitiveness of work activity has been shown to be a strong risk factor for cumulative trauma disorders (repetitive strain injuries). Both cumulative load theory and deferential fatigue theory claim that repetitive activities precipitate musculoskeletal injury. The cumulative load theory suggests that repeated load application may result in cumulative fatigue, reducing stress-bearing capacity. Such changes may reduce the threshold stress at which the tissues fail. The deferential fatigue theory proposes that the muscles operating the joints may be differentially loaded and that this may not be proportional to the individual muscles’ capabilities. This can create a significant stress concentration in some tissues, causing an injury. This paper presents a local biomechanics model in a virtual environment, whereby the DHMS model calculates the muscle forces and motion profiles (i.e., the kinematics of the motion across time for each degree of freedom for the body). Predictive dynamics, a method developed and implemented by this group, is able to characterize the motion using an optimization algorithm that calculates the motion profiles. These motion profiles and muscle forces are calculated for each task over a repetitive cycle and are used as input for the multi-scale FEA model. The FEA model of the selected joint computes the stresses of the joint components. The system compares the current stresses of the components with the newly yielded strength that has been affected by cyclic loading and indicates the injury status of the components. This paper presents promising results to quantify and predict injury in a particular joint that is undergoing a specific repetitive motion. This integrated system allows one to study the effects of various motions and task parameters on knee joints so as to modify tasks, save analysis time, and reduce the likelihood of injury.