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Three-dimensional asymmetric maximum weight lifting prediction considering dynamic joint strength.

Rahid Zaman1, Yujiang Xiang1, Jazmin Cruz2

  • 1School of Mechanical and Aerospace Engineering, Oklahoma State University, Stillwater, OK, USA.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of Engineering in Medicine
|January 11, 2021
PubMed
Summary

This study predicts maximum weight lifting using a 3D model and optimization, considering joint torque limits. The method accurately predicts lifting motion and weight, potentially reducing injury risk.

Keywords:
Liftingasymmetric liftingdynamic joint strengthinverse dynamic optimizationmaximum weight lifting

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Area of Science:

  • Biomechanics
  • Ergonomics
  • Human Movement Science

Background:

  • Lifting is a common activity with a high risk of injury.
  • Previous models often simplify lifting dynamics or lack realistic joint torque constraints.
  • Predicting maximum lifting capacity and motion requires advanced biomechanical modeling.

Purpose of the Study:

  • To predict three-dimensional (3D) asymmetric maximum weight lifting.
  • To incorporate dynamic joint torque limits into the prediction model.
  • To validate the model's predictions against experimental data.

Main Methods:

  • An inverse-dynamics-based optimization method was employed.
  • A 40-degrees of freedom (DOFs) 3D model was utilized.
  • Multi-objective optimization (MOO) simultaneously maximized box weight and minimized joint torque squares, considering dynamic joint torque limits.

Main Results:

  • The model accurately predicted lifting motion, ground reaction forces, and maximum lifting weight.
  • Predictions showed good agreement with experimental data from 12 male subjects.
  • The model demonstrated significant predictive capability for complex lifting tasks.

Conclusions:

  • This study presents the first MOO approach for predicting 3D asymmetric lifting with dynamic joint torque limits.
  • The validated model offers a promising tool for assessing lifting capacity.
  • The proposed method has the potential to mitigate injury risks associated with lifting activities.