Stability and the time-dependent structure of gait variability in walking and running

Jordan, Kimberlee; Challis, John H.; Cusumano, Joseph P.; Newell, Karl M.

doi:10.1016/j.humov.2008.09.001

Cited by 86 publications

(89 citation statements)

References 28 publications

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“…The strength of long-range correlations can be calculated for a number of gait parameters, including step length, step time, impulse, duration of contact and peak active force [134][135][136]. We chose to include this measure in the current review because of its prominence in the gait literature [3,9,35,79,119,132,134 -155].…”

Section: General Descriptionmentioning

confidence: 99%

Assessing the stability of human locomotion: a review of current measures

Bruijn

Meijer

Beek³

et al. 2013

J. R. Soc. Interface.

529

365

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Falling poses a major threat to the steadily growing population of the elderly in modern-day society. A major challenge in the prevention of falls is the identification of individuals who are at risk of falling owing to an unstable gait. At present, several methods are available for estimating gait stability, each with its own advantages and disadvantages. In this paper, we review the currently available measures: the maximum Lyapunov exponent (l S and l L ), the maximum Floquet multiplier, variability measures, long-range correlations, extrapolated centre of mass, stabilizing and destabilizing forces, foot placement estimator, gait sensitivity norm and maximum allowableperturbation. We explain what these measures represent and how they are calculated, and we assess their validity, divided up into construct validity, predictive validity in simple models, convergent validity in experimental studies, and predictive validity in observational studies. We conclude that (i) the validity of variability measures and l S is best supported across all levels, (ii) the maximum Floquet multiplier and l L have good construct validity, but negative predictive validity in models, negative convergent validity and (for l L ) negative predictive validity in observational studies, (iii) long-range correlations lack construct validity and predictive validity in models and have negative convergent validity, and (iv) measures derived from perturbation experiments have good construct validity, but data are lacking on convergent validity in experimental studies and predictive validity in observational studies. In closing, directions for future research on dynamic gait stability are discussed.

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Section: General Descriptionmentioning

confidence: 99%

Assessing the stability of human locomotion: a review of current measures

Bruijn

Meijer

Beek³

et al. 2013

J. R. Soc. Interface.

529

365

View full text Add to dashboard Cite

show abstract

“…4A) and is in agreement with the higher estimated triceps surae muscle force and power during running at the WRT speed (Neptune and Sasaki, 2005;Farris and Sawicki, 2012b;Arnold et al, 2013). We cannot rule out, however, that the combination of the limitation in plantarflexion torque and dorsiflexion fatigue may contribute to the loss of local dynamic stability at the ankle joint when walking at speeds beyond the WRT (Jordan et al, 2009), and may together reflect a dynamic systems determinant of the WRT as opposed to a discrete ankle joint determinant.…”

Section: Research Articlementioning

confidence: 97%

Joint-level mechanics of the walk-to-run transition in humans

Pires

Lay

Rubenson

2014

Journal of Experimental Biology

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Two commonly proposed mechanical explanations for the walk-to-run transition (WRT) include the prevention of muscular over-exertion (effort) and the minimization of peak musculoskeletal loads and thus injury risk. The purpose of this study was to address these hypotheses at a joint level by analysing the effect of speed on discrete lower-limb joint kinetic parameters in humans across a wide range of walking and running speeds including walking above and running below the WRT speed. Joint work, peak instantaneous joint power, and peak joint moments in the sagittal and frontal plane of the ankle, knee and hip from eight participants were collected for 10 walking speeds (30-120% of their WRT) and 10 running speeds (80-170% of their WRT) on a force plate instrumented treadmill. Of the parameters analysed, three satisfied our statistical criteria of the 'effort-load' hypothesis of the WRT. Mechanical parameters that provide an acute signal (peak moment and peak power) were more strongly associated with the gait transition than parameters that reflect the mechanical function across a portion of the stride. We found that both the ankle (peak instantaneous joint power during swing) and hip mechanics (peak instantaneous joint power and peak joint moments in stance) can influence the transition from walking to running in human locomotion and may represent a cascade of mechanical events beginning at the ankle and leading to an unfavourable compensation at the hip. Both the ankle and hip mechanisms may contribute to gait transition by lowering the muscular effort of running compared with walking at the WRT speed. Although few of the examined joint variables satisfied our hypothesis of the WRT, most showed a general marked increase when switching from walking to running across all speeds where both walking and running are possible, highlighting the fundamental differences in the mechanics of walking and running. While not eliciting the WRT per se, these variables may initiate the transition between stable walking and running patterns. Those variables that were invariant of gait were predominantly found in the swing phase.

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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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Stability and the time-dependent structure of gait variability in walking and running

Cited by 86 publications

References 28 publications

Assessing the stability of human locomotion: a review of current measures

Assessing the stability of human locomotion: a review of current measures

Joint-level mechanics of the walk-to-run transition in humans

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

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