TY - JOUR
T1 - Multiscale entropy analysis of human gait dynamics
AU - Costa, M.
AU - Peng, C. K.
AU - Goldberger, Ary L.
AU - Hausdorff, Jeffrey M.
N1 - Funding Information:
This work was supported in part by NIH grants AG-14100, RR-13622, HD-39838 and AG-08812, and by the G. Harold and Leila Y. Mathers Charitable Foundation.
PY - 2003/12/1
Y1 - 2003/12/1
N2 - 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.
AB - 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.
KW - Complexity
KW - Human gait
KW - Locomotion
KW - Multiscale entropy
KW - Neural control
UR - http://www.scopus.com/inward/record.url?scp=0344118683&partnerID=8YFLogxK
U2 - 10.1016/j.physa.2003.08.022
DO - 10.1016/j.physa.2003.08.022
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AN - SCOPUS:0344118683
SN - 0378-4371
VL - 330
SP - 53
EP - 60
JO - Physica A: Statistical Mechanics and its Applications
JF - Physica A: Statistical Mechanics and its Applications
IS - 1-2
T2 - Randomes and Complexity
Y2 - 5 January 2003 through 9 January 2003
ER -
