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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.