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 literaturebased data respectively. This approach is applied to a box-lifting task and provides a robust tool for studying human performance and for preventing injuries.
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Marler, T., Knake, L., Johnson, R. (2011). Optimization-Based Posture Prediction for Analysis of Box Lifting Tasks. In: Duffy, V.G. (eds) Digital Human Modeling. ICDHM 2011. Lecture Notes in Computer Science, vol 6777. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21799-9_17
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DOI: https://doi.org/10.1007/978-3-642-21799-9_17
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