Journal article
3D HUMAN LIFTING MOTION PREDICTION WITH DIFFERENT PERFORMANCE MEASURES
International journal of HR : humanoid robotics, Vol.9(2), pp.1250012-1250021
06/2012
DOI: 10.1142/S0219843612500120
Abstract
This paper presents an optimization-based method for predicting a human dynamic lifting task. The three-dimensional digital human skeletal model has 55 degrees of freedom. Lifting motion is generated by minimizing an objective function (human performance measure) subjected to basic physical and kinematical constraints. Four objective functions are investigated in the formulation: the dynamic effort, the balance criterion, the maximum shear force at spine joint and the maximum pressure force at spine joint. The simulation results show that various human performance measures predict different lifting strategies: the balance and shear force performance measures predict back-lifting motion and the dynamic effort and pressure force performance measures generate squat-lifting motion. In addition, the effects of box locations on the lifting strategies are also studied. All kinematics and kinetic data are successfully predicted for the lifting motion by using the predictive dynamics algorithm and the optimal solution was obtained in about one minute.
Details
- Title: Subtitle
- 3D HUMAN LIFTING MOTION PREDICTION WITH DIFFERENT PERFORMANCE MEASURES
- Creators
- YUJIANG XIANG - Virtual Soldier Research Program (VSR), Center for Computer Aided Design (CCAD), College of Engineering, The University of Iowa, Iowa City, IA 52242, United StatesJASBIR S ARORA - Virtual Soldier Research Program (VSR), Center for Computer Aided Design (CCAD), College of Engineering, The University of Iowa, Iowa City, IA 52242, United StatesKARIM ABDEL-MALEK - Virtual Soldier Research Program (VSR), Center for Computer Aided Design (CCAD), College of Engineering, The University of Iowa, Iowa City, IA 52242, United States
- Resource Type
- Journal article
- Publication Details
- International journal of HR : humanoid robotics, Vol.9(2), pp.1250012-1250021
- DOI
- 10.1142/S0219843612500120
- ISSN
- 0219-8436
- eISSN
- 1793-6942
- Language
- English
- Date published
- 06/2012
- Academic Unit
- Mechanical Engineering; Civil and Environmental Engineering; Roy J. Carver Department of Biomedical Engineering
- Record Identifier
- 9984064247802771
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