Big data simulation study on human physique measurement parameters based on the movement speed of sports race-walking

This research, grounded in the theory of passive walking, constructs a bipedal action mechanics model. Leveraging national standard human body parameters, it undertakes comprehensive simulation studies, with a focus on delving into how variations in human body parameters influence walking speed. Through meticulous analysis, it is revealed that two crucial parameters—calf length and foot height, along with the ratio of (calf length + foot height) to lower limb length—exhibit a notable positive correlation with walking speed. Significantly, this pattern aligns remarkably well with those derived by other researchers from human measurement data and the competition outcomes of race walkers. This congruence strongly validates the substantial effectiveness and reliability of the model simulation approach adopted in this study. Consequently, the findings of this research offer a valuable reference for subsequent selection processes of race walking athletes. It is anticipated that this will render the selection of race walking athletes more scientific and precise, thereby laying a solid groundwork for identifying more promising race walking talents.