Conference proceeding
Optimization-Based Posture Prediction for Analysis of Box Lifting Tasks
Digital Human Modeling, Vol.6777, pp.151-160
Lecture Notes in Computer Science
01/01/2011
DOI: 10.1007/978-3-642-21799-9_17
Abstract
New methods for optimization-based posture prediction with external forces are presented and tested. The proposed approach incorporates prediction of 113 degrees of freedom including global position and orientation of the body as well as foot position, while considering balance. Postures and joint torques are successfully predicted and compared to motion-capture data and literature-based data respectively. This approach is applied to a box-lifting task and provides a robust tool for studying human performance and for preventing injuries.
Details
- Title: Subtitle
- Optimization-Based Posture Prediction for Analysis of Box Lifting Tasks
- Creators
- Tim Marler - University of IowaLindsey Knake - Center for Computer Aided Design, Virtual Soldier Research Program, The Univeristy of Iowa, Iowa City, IowaRoss Johnson - University of Iowa
- Contributors
- V G Duffy (Editor)
- Resource Type
- Conference proceeding
- Publication Details
- Digital Human Modeling, Vol.6777, pp.151-160
- Publisher
- Springer Nature
- Series
- Lecture Notes in Computer Science
- DOI
- 10.1007/978-3-642-21799-9_17
- ISSN
- 0302-9743
- eISSN
- 1611-3349
- Number of pages
- 10
- Language
- English
- Date published
- 01/01/2011
- Academic Unit
- Stead Family Department of Pediatrics; Roy J. Carver Department of Biomedical Engineering; Neonatology
- Record Identifier
- 9984353845002771
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