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

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.