An Adaptive System Identification Model of the Biomechanical Response of the Human Trunk During Sudden Loading

Abstract

Sudden loading injuries to the low back are a concern. Current models are limited in their ability to quantify the time-varying nature of the sudden loading event. The method of approach used six males who were subjected to sudden loads. Response data (EMG and kinematics) were input into a system identification model to yield time-varying torso stiffness estimates. The results show estimates of system stiffness in good agreement with values in the literature. The average root mean square error of the model’s predictions of sagittal motion was equal to 0.1deg. In conclusion, system identification can be implemented with minimal error and used to gain more insight into the time-dependent trunk response to sudden loads.