title: Understanding the complexity of human gait dynamics.
abstract: Time series of human gait stride intervals exhibit fractal and multifractal properties under several conditions. Records from subjects walking at normal, slow, and fast pace speed are analyzed to determine changes in the fractal scalings as a function of the stress condition of the system. Records from subjects with different age from children to elderly and patients suffering from neurodegenerative disease are analyzed to determine changes in the fractal scalings as a function of the physical maturation or degeneration of the system. A supercentral pattern generator model is presented to simulate the above two properties that are typically found in dynamical network performance: that is, how a dynamical network responds to stress and to evolution.
authors: Department of Physics, Duke University, Durham, North Carolina 27708, USA.
authors: Nicola
authors: N
authors: Scafetta
authors: Damiano
authors: D
authors: Marchi
authors: Bruce J
authors: BJ
authors: West
mesh_terms: D000328:Adult; D000368:Aged; D000375:Aging / Q000502:physiology; D001696:Biomechanical Phenomena; D002648:Child; D002675:Child, Preschool; D017709:Fractals; D005684:Gait / Q000502:physiology*; D006801:Humans; D008954:Models, Biological; D008959:Models, Neurological; D019636:Neurodegenerative Diseases / Q000503:physiopathology; D017711:Nonlinear Dynamics; D016138:Walking / Q000502:physiology; D055815:Young Adult