When human walking becomes random walking: fractal analysis and modeling of gait rhythm fluctuations

Hausdorff, Jeffrey M.; Ashkenazy, Yosef; Peng, Chung-Kang; Ivanov, Plamen Ch.; Stanley, H. Eugene; Goldberger, Ary L.

doi:10.1016/s0378-4371(01)00460-5

Cited by 203 publications

(174 citation statements)

References 21 publications

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“…We first studied the stride-to-stride fluctuations present in healthy adults in order to gain insight into normal locomotor function and its control mechanisms and thereby better appreciate pathological deviations (Hausdorff, Ashkenazy et al, 2001;Hausdorff et al, 1996). Variability, the magnitude of the stride-to-stride fluctuations, and stride dynamics, how the stride fluctuates with time, independent of the magnitude, may rely upon different control mechanisms.…”

Section: First Evidence Of Fractal-like Fluctuations In Gaitmentioning

confidence: 99%

“…These include deterministic models, stochastic models, as well as combinations of the two (Ashkenazy et al, 2002;Hausdorff, Ashkenazy et al, 2001;Hausdorff, Peng et al, 1995;Kurz & Stergiou, 2005;West & Latka, 2005;West & Scafetta, 2003). Some of these models are able to reproduce and explain the fractal-like fluctuations and many of the observed alterations with aging and disease have been captured as well.…”

Section: Modeling the Stride-to-stride Fractal Fluctuationsmentioning

confidence: 99%

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

Hausdorff

2007

Human Movement Science

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729

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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: First Evidence Of Fractal-like Fluctuations In Gaitmentioning

confidence: 99%

Section: Modeling the Stride-to-stride Fractal Fluctuationsmentioning

confidence: 99%

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

Hausdorff

2007

Human Movement Science

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729

594

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“…By using pressure sensors in the shoe (HausdorV et al 1995), it could be demonstrated that gait inter-cycle variability is signiWcantly higher in faller than non-fallers and young subjects (HausdorV et al 1997). Moreover, using the same sensors, it could be demonstrated that the long-range variability in gait patterns is strongly related to degree of functional impairment (HausdorV et al 2001). …”

Section: Assessment Of Balance and Gaitmentioning

confidence: 99%

Mobility assessment in older people: new possibilities and challenges

2007

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A major challenge for researchers and clinicians who address health issues in the ageing population is to monitor functioning, and to timely initiate interventions that aim to prevent loss of functional abilities and to improve the quality of life of older people. With the progress of technologies in the last decades, methods have become available that use body Wxed sensors (BFS) to measure aspects of human performance under real-life conditions. These methods are based on the use of miniaturised and integrated sensors in combination with lightweight, small measuring devices that both can be carried on the body without interfering with normal behaviour. This paper addresses the potential relevance of new technology for monitoring motor function in older people, thereby speciWcally focusing on mobility assessment. After a short introduction with background information about BFS based technology, this paper identiWes areas of particular relevance, and discusses the application of ambulatory techniques for long-term monitoring of daily physical activity, fall detectors, fall risk evaluation, and assessment of motor performance such as gait and balance control. Examples are given how these techniques can become clinically relevant, particularly in the context of fall interventions for older people.

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“…This suggests an adaptive process aimed at allowing greater stabilization around the joint (Peterson and Martin, 2010;Schmitz et al, 2009). This seems to be supported by the fact that aging can lead to loss of balance (Woollacott, 1993) and stability in gait (Hausdorff, 2007;Hausdorff et al, 2001). Therefore, the larger amount of co-activation displayed by the elderly for a given velocity might contribute to further increase the stability.…”

Section: Introductionmentioning

confidence: 96%

Antagonist muscle co-activation during straight walking and its relation to kinematics: Insight from young, elderly and Parkinson's disease

et al. 2012

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Increased antagonist muscle co-activation of the lower limb during walking seems to be an adaptive process to the physiological changes of aging, in order to gain joint stability. In the healthy subjects this view seems to be reinforced by the fact that the co-activation index (CAI) increases when the gait is faster. The few reports on antagonist coactivation in Parkinson's disease (PD) patients indicate that they have larger co-activation than the healthy elderly, supporting the idea of the stabilization role of CAI during gait, as postural instability is a cardinal feature of PD. However it has also been reported that there is a reduction of the CAI when increasing velocity in PD or normal elderly. This questions the role of coactivation in stabilization during increased velocity. In this study we have analyzed the gait of healthy subjects (young and elderly), and PD patients (with and without freezing of gait, FOG) in order to better understand the relation between co-activation and gait kinematics, and to gain insight into the pathological changes associated with FOG in PD. We used Multiple Linear Regression models to study the relationship in shank muscles between CAI, velocity and cadence. Our results indicate that, for all groups of interest, the relationship between co-activation and the kinematics of gait is poor, due to the high degree of variability, questioning the explanatory value of the index.

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When human walking becomes random walking: fractal analysis and modeling of gait rhythm fluctuations

Cited by 203 publications

References 21 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

Mobility assessment in older people: new possibilities and challenges

Antagonist muscle co-activation during straight walking and its relation to kinematics: Insight from young, elderly and Parkinson's disease

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