Two-Dimensional Versus Three-Dimensional Symmetric Lifting Motion Prediction Models: A Case Study

Abstract

Symmetric lifting is a common manual material handling strategy in daily life and is the main cause of low back pain. In the literature, symmetric lifting is mainly simulated by using two-dimensional (2D) models because of their simplicity and low computational cost. In practice, however, symmetric lifting can generate asymmetric kinetics especially when the lifting weight is heavy and symmetric lifting based on 2D models misses this important asymmetric kinetics information. Therefore, three-dimensional (3D) models are necessary for symmetric lifting simulation to capture asymmetric kinetics. The purpose of this single-subject case study is to compare the optimization formulations and simulation results for symmetric lifting by using 2D and 3D human models and to identify their pros and cons. In this case study, a 10-degrees-of-freedom (DOFs) 2D skeletal model and a 40-DOFs 3D skeletal model are employed to predict the symmetric maximum weight lifting motion, respectively. The lifting problem is formulated as a multi-objective optimization (MOO) problem to minimize the dynamic effort and maximize the box weight. An inverse dynamic optimization approach is used to determine the optimal lifting motion and the maximum lifting weight considering dynamic joint strength. Lab experiments are carried out to validate the predicted motions. The predicted lifting motion, ground reaction forces (GRFs), and maximum box weight from the 2D and 3D human models for Subject #8 are compared with the experimental data. Recommendations are given.