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Related Experiment Videos

Constrained optimization in human running.

Anne K Gutmann1, Brian Jacobi, Michael T Butcher

  • 1Department of Theoretical and Applied Mechanics, Cornell University, Ithaca, NY 12853, USA.

The Journal of Experimental Biology
|February 2, 2006
PubMed
Summary

Human gait selection in running can be predicted by constrained optimization models. This suggests that general metabolic cost surfaces can predict locomotion behavior across different groups.

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Area of Science:

  • Biomechanics
  • Human locomotion
  • Movement science

Background:

  • Human walking gait selection is explained by constrained optimization of the cost of transport.
  • It remains unclear if this principle applies to other forms of locomotion, such as running.

Purpose of the Study:

  • To investigate running gait selection using constrained optimization.
  • To compare self-selected running gaits with predicted gaits based on literature cost data.

Main Methods:

  • Examined running gait parameters (speed, frequency, step length).
  • Normalized behavioral data by preferred speed and frequency to reduce variability.
  • Compared self-selected gaits to predictions from a general human cost surface.

Main Results:

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  • Self-selected running gaits closely matched predictions from the constrained optimization model.
  • Agreement was within the 95% confidence interval and minimal cost region.
  • Observed similar agreement levels as previously reported for walking.

Conclusions:

  • Gait parameter selection in running is largely predictable via constrained optimization.
  • General metabolic cost surfaces derived from one group can predict locomotion behavior in other groups.