Multiscale entropy analysis of human gait dynamics

M. Costa, C. K. Peng, Ary L. Goldberger, Jeffrey M. Hausdorff*

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

432 Scopus citations


We compare the complexity of human gait time series from healthy subjects under different conditions. Using the recently developed multiscale entropy algorithm, which provides a way to measure complexity over a range of scales, we observe that normal spontaneous walking has the highest complexity when compared to slow and fast walking and also to walking paced by a metronome. These findings have implications for modeling locomotor control and for quantifying gait dynamics in physiologic and pathologic states.

Original languageEnglish
Pages (from-to)53-60
Number of pages8
JournalPhysica A: Statistical Mechanics and its Applications
Issue number1-2
StatePublished - 1 Dec 2003
Externally publishedYes
EventRandomes and Complexity - Eilat, Israel
Duration: 5 Jan 20039 Jan 2003


FundersFunder number
National Institutes of HealthRR-13622, AG-08812, HD-39838, AG-14100
G. Harold and Leila Y. Mathers Charitable Foundation


    • Complexity
    • Human gait
    • Locomotion
    • Multiscale entropy
    • Neural control


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