Long range correlations in the stride interval of running

Jordan, Kimberlee; Challis, John H.; Newell, Karl M.

doi:10.1016/j.gaitpost.2005.08.003

Cited by 127 publications

(122 citation statements)

References 26 publications

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“…3). Subsequent studies also demonstrated that the fractal-like fluctuations are present even when healthy participants run or walk on a treadmill (Frenkel-Toledo et al, 2005b;Jordan, Challis, & Newell, 2006, 2007a. Thus, the fractal dynamics of the stride interval are normally quite robust, they are apparently intrinsic to the locomotor system, and they exist at a wide range of gait speeds.…”

Section: Robust Nature Of the Fractal Fluctuationsmentioning

confidence: 98%

Gait dynamics, fractals and falls: Finding meaning in the stride-to-stride fluctuations of human walking

Hausdorff

2007

Human Movement Science

729

594

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Until recently, quantitative studies of walking have typically focused on properties of a typical or average stride, ignoring the stride-to-stride fluctuations and considering these fluctuations to be noise. Work over the past two decades has demonstrated, however, that the alleged noise actually conveys important information. The magnitude of the stride-to-stride fluctuations and their changes over time during a walk -gait dynamics -may be useful in understanding the physiology of gait, in quantifying age-related and pathologic alterations in the locomotor control system, and in augmenting objective measurement of mobility and functional status Indeed, alterations in gait dynamics may help to determine disease severity, medication utility, and fall risk, and to objectively document improvements in response to therapeutic interventions, above and beyond what can be gleaned from measures based on the average, typical stride. This review discusses support for the idea that gait dynamics has meaning and may be useful in providing insight into the neural control of locomtion and for enhancing functional assessment of aging, chronic disease, and their impact on mobility.

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Section: Robust Nature Of the Fractal Fluctuationsmentioning

confidence: 98%

Gait dynamics, fractals and falls: Finding meaning in the stride-to-stride fluctuations of human walking

Hausdorff

2007

Human Movement Science

729

594

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“…Subsequent studies using a variety of different techniques have confirmed the presence of long-range correlations and fractal-like scaling in the gait of healthy young adults ͑see below͒, even during slow walking and during running. [80][81][82][83][84][85][86][87] From a neurophysiological control viewpoint, this behavior is of interest because it signifies the presence of longterm, non-trivial "dependence" or "memory" in the locomotor control system. This scale-invariance property has been associated with the survivability of the system in several physical and physiological systems.…”

Section: Beyond the First And Second Moments: Fractal Analysis Of mentioning

confidence: 99%

“…47,79,95 Longrange correlations also exist during running. 82,84 In contrast, during metronomically paced walking, fluctuations in the stride interval are altered. 79,86 Thus, the fractal dynamics of the stride interval are normally quite robust, largely independent of speed, and intrinsic to the locomotor system.…”

Section: Beyond the First And Second Moments: Fractal Analysis Of mentioning

confidence: 99%

Gait dynamics in Parkinson’s disease: Common and distinct behavior among stride length, gait variability, and fractal-like scaling

Hausdorff

2009

Chaos: An Interdisciplinary Journal of Nonlinear Science

507

409

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Parkinson’s disease (PD) is a common, debilitating neurodegenerative disease. Gait disturbances are a frequent cause of disability and impairment for patients with PD. This article provides a brief introduction to PD and describes the gait changes typically seen in patients with this disease. A major focus of this report is an update on the study of the fractal properties of gait in PD, the relationship between this feature of gait and stride length and gait variability, and the effects of different experimental conditions on these three gait properties. Implications of these findings are also briefly described. This update highlights the idea that while stride length, gait variability, and fractal scaling of gait are all impaired in PD, distinct mechanisms likely contribute to and are responsible for the regulation of these disparate gait properties.

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“…This process was repeated for different values of segment lengths, n. Fifty values of n that were evenly distributed between 4 and N/4 were used [30]. Typically, F(n) increases with n and a graph of log[F(n)] versus log(n) will exhibit a power-law relationship indicating the presence of scaling, such that F(n) ≅ n α .…”

Section: Modelmentioning

confidence: 99%

Possible biomechanical origins of the long-range correlations in stride intervals of walking

Gates

Dingwell

2007

Physica A: Statistical Mechanics and its Applications

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When humans walk, the time duration of each stride varies from one stride to the next. These temporal fluctuations exhibit long-range correlations. It has been suggested that these correlations stem from higher nervous system centers in the brain that control gait cycle timing. Existing proposed models of this phenomenon have focused on neurophysiological mechanisms that might give rise to these long-range correlations, and generally ignored potential alternative mechanical explanations. We hypothesized that a simple mechanical system could also generate similar long-range correlations in stride times. We modified a very simple passive dynamic model of bipedal walking to incorporate forward propulsion through an impulsive force applied to the trailing leg at each push-off. Push-off forces were varied from step to step by incorporating both "sensory" and "motor" noise terms that were regulated by a simple proportional feedback controller. We generated 400 simulations of walking, with different combinations of sensory noise, motor noise, and feedback gain. The stride time data from each simulation were analyzed using detrended fluctuation analysis to compute a scaling exponent, a. This exponent quantified how each stride interval was correlated with previous and subsequent stride intervals over different time scales. For different variations of the noise terms and feedback gain, we obtained short-range correlations (α < 0.5), uncorrelated time series (α = 0.5), long-range correlations (0.5 < α < 1.0), or Brownian motion (α > 1.0). Our results indicate that a simple biomechanical model of walking can generate long-range correlations and thus perhaps these correlations are not a complex result of higher level neuronal control, as has been previously suggested.

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Long range correlations in the stride interval of running

Cited by 127 publications

References 26 publications

Gait dynamics, fractals and falls: Finding meaning in the stride-to-stride fluctuations of human walking

Gait dynamics, fractals and falls: Finding meaning in the stride-to-stride fluctuations of human walking

Gait dynamics in Parkinson’s disease: Common and distinct behavior among stride length, gait variability, and fractal-like scaling

Possible biomechanical origins of the long-range correlations in stride intervals of walking

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