Optimization of human gait using singular-value decomposition-based design variables

Abstract Age, walking speed, the presence of problems, slope ground, and many other parameters affect human gait. Understanding gait variations obtaining a reference behavior under different conditions is important for identifying abnormal behaviors designing assistive devices, orthoses, prostheses. Predictive dynamics can be used to determine motion given task. In predictive approach, generated using design variables, equation considered constraint. Several variables were generate motion, biological limits joints additional constraints in previous studies. A foot-ground contact model was vertical horizontal ground reaction forces nonlinear spring-damper model. This study proposed singular value decomposition-based joint angle generation method reduce number constraints. First, angles calculated capture data 225 participants. Then, matrix containing all participants experiments created. The modes extracted singular-value decomposition. by summing multiplication first nine their corresponding variables. Therefore, significantly reduced. Moreover, related intrinsically satisfied. Joint angles, moments, power obtained optimal energy moment square cases at speeds. results found consistent with experimental literature.