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Human carrying is simulated in this work by using a skeletal digital human model with 55 degrees of freedom. An optimization-based approach is used to predict the carrying motion with symmetric and asymmetric loads. In this process, the model predicts joint dynamics using optimization schemes and task-based physical constraints. The results indicate that the model can predict different carrying strategies during symmetric and asymmetric load-carrying tasks. The model can also indicate the risk factors for extreme loading situations. With such robust prediction capability, the model could be used for biomedical and ergonomic studies.
Yujiang Xiang (Corresponding Author) is with the Department of Mechanical Engineering, University of Alaska Fairbanks, Fairbanks, Alaska.