Lifting motion simulation using a hybrid approach

Abstract

In this study, a hybrid dynamic model for lifting motion simulation is presented. The human body is represented by a two-dimensional (2D) five-segment model. The lifting motions are predicted by solving a nonlinear optimisation problem, the objective function of which is defined based on a minimal-effort performance criterion. In the optimisation procedure, the joint angular velocities are bounded by time-functional constraints that are determined by actual motions. Symmetric lifting motions performed by younger and older adults under varied task conditions were simulated. Comparisons between the simulation results and actual motion data were made for model evaluation. The results showed that the mean and median joint angle errors were less than 10°, which suggests the proposed model is able to accurately simulate 2D lifting motions. The proposed model is also comparable with the existing motion simulation models in terms of the prediction accuracy. Strengths and limitations of this hybrid model are discussed.

Abstract

Practitioner Summary: Human motion simulation is a useful tool in assessing the risks of occupational injuries. Lifting motions are associated with low-back pain. A hybrid model for lifting motion simulation was constructed. The model was able to accurately simulate 2D lifting motions in varied task scenarios for younger and older subjects.

Keywords::

• lifting
• hybrid motion simulation
• minimum effort
• data-based constraints
• optimisation

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This study was conducted at Nanyang Technological University and was supported in part by the Academic Research Fund from Ministry of Education, Singapore [Project Reference: 2013-T1-002-068].