Abstract
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 language | English |
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Pages (from-to) | 53-60 |
Number of pages | 8 |
Journal | Physica A: Statistical Mechanics and its Applications |
Volume | 330 |
Issue number | 1-2 |
DOIs | |
State | Published - 1 Dec 2003 |
Externally published | Yes |
Event | Randomes and Complexity - Eilat, Israel Duration: 5 Jan 2003 → 9 Jan 2003 |
Funding
Funders | Funder number |
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National Institutes of Health | RR-13622, AG-08812, HD-39838, AG-14100 |
G. Harold and Leila Y. Mathers Charitable Foundation |
Keywords
- Complexity
- Human gait
- Locomotion
- Multiscale entropy
- Neural control