Abstract
This paper describes an efficient optimization method for determining the subject-specific strength percentile and predicting the maximum weight lifting motion by considering dynamic joint strength in symmetric box lifting. Dynamic strength is modeled as a three-dimensional function of joint angle and joint angular velocity based on experimentally obtained joint strength data from the literature. The function is further formulated as the joint torque limit constraint in an inverse dynamics optimization formulation to predict the maximum weight lifting motion. The initial, mid-time, and final postures are obtained from experiments and imposed as tracking constraints in the optimization formulation. In addition, the box weight and time duration are given as inputs for the lifting optimization problem. The normalized joint torque squared is used as the objective function. Subject-specific strength percentile (\(z\_\mathrm{score}\)) is enumerated until the optimal solution is achieved. The determined strength percentile is a global score considering interactions of all joints for the two-dimensional symmetric lifting task. Results show that incorporating dynamic strength is critical in predicting lifting motion in extreme lifting conditions. The proposed algorithm can determine the subject-specific strength percentile based on experimental box lifting data. The accurate strength percentile is critical to predict strength related tasks to protect workers from injury.
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This research is supported by projects from NSF (Award #1700865, 1849279, and 1703093).
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Xiang, Y., Zaman, R., Rakshit, R. et al. Subject-specific strength percentile determination for two-dimensional symmetric lifting considering dynamic joint strength. Multibody Syst Dyn 46, 63–76 (2019). https://doi.org/10.1007/s11044-018-09661-1
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DOI: https://doi.org/10.1007/s11044-018-09661-1