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Faculty Mentor

Dr. Philip K. Schot

Subject Area

Biological Sciences, Exercise Science

Abstract

Locomotion and movement economy are cornerstone topics in movement science. Modeling the leg as a hybrid mass-spring pendulum shows walking economy should be optimized when stride frequency matches the resonant frequency of the limb. Human walking is described as self-optimizing because mean preferred (PSF) and modeled resonant (RSF) stride frequencies usually are statistically equivalent, but this depiction may not be fully justified. Purpose: To more thoroughly examine the self-optimization characterization and the consequences of obligating use of the RSF. Methods: Forty-seven individuals of diverse statures completed 3 consecutive days of preferred walking trials on a treadmill where stride rate, stride length, walking speed, heart rate and walking economy measures were made under steady state heart rate conditions. Anthropometric measures were taken to build a hybrid model of the leg and model the RSF. Reliability across days was evaluated via repeated measures analysis of variance (ANOVA) and intra-class correlation (α=.05) and correlations were calculated for PSF and RSF. A separate sample of 20 participants walked under 3 conditions, (1) completely preferred; (2) at the original preferred speed using the RSF; and (3) with the option to establish a new preferred speed while using the RSF. Results: Gait characteristics were fundamentally reliable across days and the correlation between PSF and RSF was weak (8% explained variance). Walking economy improved 14% when using the RSF and allowed to self-select the speed / stride length used at that cadence. Conclusions: The results raised slight questions about current self-optimization presumptions and further emphasized the role of resonance in walking economy

Keywords

gait, self-optimization, resonance

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