Human stair ascent and descent are simulated in this work by using a skeletal digital human model with 55 degrees of freedom (DOFs). Hybrid predictive dynamics approach is used to predict the stair climbing motion with weapons and backpacks. In this process, the model predicts joints dynamics using optimization schemes and task-based physical constraints. The results indicated that the model can realistically match human motion and ground reaction forces data during stair climbing tasks. This can be used in human health domain such as leg prosthesis design.

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