Human stair ascent and descent simulation using a hybrid optimization formulation

Human stair ascent and descent motions are simulated in this work by using a skeletal human model with 55 degrees of freedom (DOF). An optimization formulation is used to predict the stair ascent and descent motions of humans carrying weapons and backpacks. The total performance measure is a mixed objective function with normalized motion capture data and normalized dynamic effort in a multi-objective optimization (MOO) problem. In addition, the joint angle profiles are treated as unknowns in the formulation. The joint torques are inversely evaluated from the equations of motion. The model predicts the joint profiles using optimization schemes and task-based physical constraints. The results indicated that the model can realistically simulate human motion and ground reaction forces (GRFs) during stair ascent and descent tasks. This framework can be used in human-centred engineering design such as optimization of load-carriage distribution and lower-limb prosthesis design.