Performance Evaluation on OpenSim's Virtual Markers Trajectory System for Running Simulation

Running is a locomotion ability that human equipped to move from one place to another in faster pace compared to walking. Shoe cushioning alters the running gait in some extent. Depending on the hardness of the shoe cushioning, some may cause increase in the ground reaction force. Thus, this paper investigated on the moment gait between hard and soft shoe cushioning under running, and evaluating the performance via the OpenSim virtual marker trajectory tracking based on inverse kinematics tools, which include inverse kinematics (IK), Reduce Residual Algorithm (RRA) and MocoTrack. The results show that in knee moment with hard shoe cushioning, MocoTrack performed the best, and vice-versa in soft shoe cushioning. RRA was found to be most effective in the determination of ankle moment. Statistically, the Root Mean Square Error (RMSE), correlation (r), in knee and ankle moments, under different types of shoe cushioning, no significant differences were found, with 0.3 kg/Nm of RMSE and approximately 95% of correlation in comparison with the experimental data. Thus, in this case, the computational time does become the key factor in evaluating them. In conclusion, IK was the best performed in simulating the knee and ankle joint moments in running motion under different types of hardness shoe cushioning, then followed by RRA and MocoTrack, which had the longest computational time respectively.