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Abstract In this study, the fatigue progression and optimal motion trajectory during repetitive lifting task is predicted by using a 10 degrees of freedom (DOFs) two-dimensional (2D) digital human model and a three-compartment controller (3CC) fatigue model. The numerical analysis is further validated by conducting an experiment under similar conditions. The human is modeled using Denavit-Hartenberg (DH) representation. The task is mathematically formulated as a nonlinear optimization problem where the dynamic effort of the joints is minimized subjected to physical and task specific constraints. A sequential quadratic programming method is used for the optimization process. The design variables include control points of (1) quartic B-splines of the joint angle profiles; and (2) the three compartment sizes profiles for the six physical joints of interest — spine, shoulder, elbow, hip, knee, and ankle. Both numerical and experimental liftings are performed with a 15.2 kg box as external load. The simulation reports the human joint torque profiles and the progression of joint fatigue. The joint torque profiles show periodic trends. A maximum of 17 cycles are predicted before the repetitive lifting task fails, which also reasonably agrees with that of the experimental results (16 cycles). This formulation is also a generalized one, hence it can be used for other repetitive motion studies as well.
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This content will become publicly available on June 1, 2026
Repetitive Lifting Motion Predictions Considering Muscle Fatigue
Abstract This paper predicts the optimal motion for a repetitive lifting task considering muscle fatigue. The Denavit–Hartenberg (DH) representation is employed to characterize the two-dimensional (2D) digital human model with 10 degrees-of-freedom (DOFs). Two joint-based muscle fatigue models, i.e., a three-compartment controller (3CC) muscle fatigue model (validated for isometric tasks) and a four-compartment controller with augmented recovery (4CCr) muscle fatigue model (validated for dynamic tasks), are utilized to account for the fatigue effect due to the repetitive motion. The lifting problem is formulated mathematically as an optimization problem, with the objective of minimizing dynamic effort and joint acceleration subjected to both physical and task-specific constraints. The design variables include joint angle profiles, discretized by quartic B-splines, and the control points of the profiles of the fatigue compartments associated with major body joints (spinal, shoulder, elbow, hip, and knee joints). The outcomes of the simulation encompass profiles of joint angles, joint torques, and the advancement of joint fatigue. It is notable that the profiles of joint angles and torques exhibit distinct periodic patterns. Numerical simulations and experiments with a 20 kg box reveal that the maximum predicted lifting cycles are 11 for the 3CC fatigue model and 13 for the 4CCr fatigue model while the experimental result is 13 cycles. The results indicate that the 4CCr muscle fatigue model provides enhanced accuracy over the 3CC model for predicting task duration (number of cycles) of repetitive lifting.
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- PAR ID:
- 10627121
- Publisher / Repository:
- ASME
- Date Published:
- Journal Name:
- Journal of Biomechanical Engineering
- Volume:
- 147
- Issue:
- 6
- ISSN:
- 0148-0731
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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