1997
DOI: 10.1016/s0003-9993(97)90034-4
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Increased gait unsteadiness in community-dwelling elderly fallers

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Cited by 520 publications
(469 citation statements)
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References 31 publications
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“…To focus on the assessment of the dynamics of continuous, 'normal' walking and each participant's 'intrinsic' dynamics and to insure that the analysis was not influenced by atypical strides, a median filter was applied to each participant's time series to remove data points that were three standard deviations greater than or less than the median value (Hausdorff, Edelberg, Mitchell, Goldberger, & Wei, 1997;Hausdorff, Rios, & Edelberg, 2001). There is typically general agreement between the values obtained before and after application of the median filter, however, occasionally important differences occur that should be considered.…”
Section: Notes On Nomenclature and Data Collection Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…To focus on the assessment of the dynamics of continuous, 'normal' walking and each participant's 'intrinsic' dynamics and to insure that the analysis was not influenced by atypical strides, a median filter was applied to each participant's time series to remove data points that were three standard deviations greater than or less than the median value (Hausdorff, Edelberg, Mitchell, Goldberger, & Wei, 1997;Hausdorff, Rios, & Edelberg, 2001). There is typically general agreement between the values obtained before and after application of the median filter, however, occasionally important differences occur that should be considered.…”
Section: Notes On Nomenclature and Data Collection Methodsmentioning
confidence: 99%
“…Subsequently, the generated time series of stride time (and/or swing time or other parameters) can then become the input to algorithms that quantify the dynamics. For example, stride time variability, the magnitude of the stride-to-stride fluctuations in the gait cycle duration, is calculated by determining the standard deviation (SD) or the coefficient of variation (CV) of each subject's stride time time series (Maki, 1997;Hausdorff, Edelberg et al, 1997;Hausdorff, Rios et al, 2001). Similar methods can be used to study the variability of other measures of gait timing (e.g., swing time).…”
Section: Notes On Nomenclature and Data Collection Methodsmentioning
confidence: 99%
“…This suggested spatial gait variability is increased when individuals are forced to modulate spatial aspects of gait at their preferred temporal frequency when dealing with increasing gait interruptions. This has significant implications, particularly for older individuals, for whom increased gait variability has been linked to increased falls risk [5,6].…”
Section: Walking Path Configuration and Duration Effects On Gait Varimentioning
confidence: 99%
“…Due to its simplicity and close relation to activities of daily living, the 6MWT has been used to represent functional capacity in chronic obstructive pulmonary disease and total knee arthroplasty patients and older individuals [1][2][3]. Conversely, measures of gait variability are more specific indicators of the neural control of gait [4] and have been used to discriminate between older fallers and nonfallers and to predict older adults at risk of falling, a major health hazard in this population [5,6].…”
Section: Introductionmentioning
confidence: 99%
“…The trunk variability measures correctly classiWed 80% of the subjects into their respective group (sensitivity = 0.75, speciWcity = 0.85). 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%