TY - JOUR
T1 - Three-dimensional asymmetric maximum weight lifting prediction considering dynamic joint strength
AU - Zaman, Rahid
AU - Xiang, Yujiang
AU - Cruz, Jazmin
AU - Yang, James
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research is supported by projects from NSF (CBET 1849279 and 1703093).
Publisher Copyright:
© IMechE 2021.
PY - 2021/4
Y1 - 2021/4
N2 - In this study, the three-dimensional (3D) asymmetric maximum weight lifting is predicted using an inverse-dynamics-based optimization method considering dynamic joint torque limits. The dynamic joint torque limits are functions of joint angles and angular velocities, and imposed on the hip, knee, ankle, wrist, elbow, shoulder, and lumbar spine joints. The 3D model has 40 degrees of freedom (DOFs) including 34 physical revolute joints and 6 global joints. A multi-objective optimization (MOO) problem is solved by simultaneously maximizing box weight and minimizing the sum of joint torque squares. A total of 12 male subjects were recruited to conduct maximum weight box lifting using squat-lifting strategy. Finally, the predicted lifting motion, ground reaction forces, and maximum lifting weight are validated with the experimental data. The prediction results agree well with the experimental data and the model’s predictive capability is demonstrated. This is the first study that uses MOO to predict maximum lifting weight and 3D asymmetric lifting motion while considering dynamic joint torque limits. The proposed method has the potential to prevent individuals’ risk of injury for lifting.
AB - In this study, the three-dimensional (3D) asymmetric maximum weight lifting is predicted using an inverse-dynamics-based optimization method considering dynamic joint torque limits. The dynamic joint torque limits are functions of joint angles and angular velocities, and imposed on the hip, knee, ankle, wrist, elbow, shoulder, and lumbar spine joints. The 3D model has 40 degrees of freedom (DOFs) including 34 physical revolute joints and 6 global joints. A multi-objective optimization (MOO) problem is solved by simultaneously maximizing box weight and minimizing the sum of joint torque squares. A total of 12 male subjects were recruited to conduct maximum weight box lifting using squat-lifting strategy. Finally, the predicted lifting motion, ground reaction forces, and maximum lifting weight are validated with the experimental data. The prediction results agree well with the experimental data and the model’s predictive capability is demonstrated. This is the first study that uses MOO to predict maximum lifting weight and 3D asymmetric lifting motion while considering dynamic joint torque limits. The proposed method has the potential to prevent individuals’ risk of injury for lifting.
KW - Lifting
KW - asymmetric lifting
KW - dynamic joint strength
KW - inverse dynamic optimization
KW - maximum weight lifting
UR - http://www.scopus.com/inward/record.url?scp=85099031787&partnerID=8YFLogxK
U2 - 10.1177/0954411920987035
DO - 10.1177/0954411920987035
M3 - Article
C2 - 33427066
AN - SCOPUS:85099031787
VL - 235
SP - 437
EP - 446
JO - Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine
JF - Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine
SN - 0954-4119
IS - 4
ER -