A validation methodology for an optimization-based predictive dynamics framework for digital human motion simulation is presented in this work. The proposed validation methodology has been implemented in time and frequency domains on a predicted walking task. The methodology uses selected critical key frames in the comparison process in the time domain, as against the full profile of all joint angles. In the frequency domain, the methodology considers using fast Fourier transform and power spectrum density. In addition to human kinematics, the methodology compares inertia and ground reaction forces, a key kinetic parameter for motion validation. The results have shown considerable correlation and insight information between the predicted and the measured data.

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