scholarly journals Variability of human gait: Long-range autocorrelations and fluctuation magnitude of stride duration

2014 ◽  
Vol 57 ◽  
pp. e427-e428
Author(s):  
B. Bollens ◽  
C. Detrembleur ◽  
F. Crevecoeur ◽  
T. Lejeune
Keyword(s):  
Long Range ◽  
Human Gait ◽  
Stride Duration

scholarly journals Influence of Autocorrelated Rhythmic Auditory Stimulations on Parkinson’s Disease Gait Variability: Comparison With Other Auditory Rhythm Variabilities and Perspectives

2020 ◽  
Vol 11 ◽  
Author(s):  
Alexis Lheureux ◽  
Thibault Warlop ◽  
Charline Cambier ◽  
Baptiste Chemin ◽  
Gaëtan Stoquart ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Long Range ◽  
Coefficient Of Variation ◽  
Gait Speed ◽  
Step Length ◽  
Temporal Organization ◽  
Fluctuation Analysis ◽  
Gait Parameters ◽  
Stride Duration

Parkinson’s Disease patients suffer from gait impairments such as reduced gait speed, shortened step length, and deterioration of the temporal organization of stride duration variability (i.e., breakdown in Long-Range Autocorrelations). The aim of this study was to compare the effects on Parkinson’s Disease patients’ gait of three Rhythmic Auditory Stimulations (RAS), each structured with a different rhythm variability (isochronous, random, and autocorrelated). Nine Parkinson’s Disease patients performed four walking conditions of 10–15 min each: Control Condition (CC), Isochronous RAS (IRAS), Random RAS (RRAS), and Autocorrelated RAS (ARAS). Accelerometers were used to assess gait speed, cadence, step length, temporal organization (i.e., Long-Range Autocorrelations computation), and magnitude (i.e., coefficient of variation) of stride duration variability on 512 gait cycles. Long-Range Autocorrelations were assessed using the evenly spaced averaged Detrended Fluctuation Analysis (α-DFA exponent). Spatiotemporal gait parameters and coefficient of variation were not modified by the RAS. Long-Range Autocorrelations were present in all patients during CC and ARAS although all RAS conditions altered them. The α-DFA exponents were significantly lower during IRAS and RRAS than during CC, exhibiting anti-correlations during IRAS in seven patients. α-DFA during ARAS was the closest to the α-DFA during CC and within normative data of healthy subjects. In conclusion, Isochronous RAS modify patients’ Long-Range Autocorrelations and the use of Autocorrelated RAS allows to maintain an acceptable level of Long-Range Autocorrelations for Parkinson’s Disease patients’ gait.

Effects of age and walking speed on long-range autocorrelations and on fluctuation magnitude of stride duration

2012 ◽  
Vol 36 ◽  
pp. S44-S45
Author(s):  
B. Bollens ◽  
C. Detrembleur ◽  
F. Crevecoeur ◽  
T. Lejeune
Keyword(s):  
Long Range ◽  
Walking Speed ◽  
Stride Duration

scholarly journals Peripheral neuropathy does not alter the fractal dynamics of stride intervals of gait

2007 ◽  
Vol 102 (3) ◽  
pp. 965-971 ◽  
Author(s):  
Deanna H. Gates ◽  
Jonathan B. Dingwell
Keyword(s):  
Peripheral Neuropathy ◽  
Spectral Density ◽  
Power Spectral Density ◽  
Long Range ◽  
Sensory Loss ◽  
Human Gait ◽  
Time Variability ◽  
Long Range Correlations ◽  
Power Spectral ◽  
Detrended Fluctuation

The purpose of this study was to determine the effect (if any) of significant sensory loss on the long-range correlations normally observed in the stride intervals of human gait. Fourteen patients with severe peripheral neuropathy and 12 gender-, age-, height-, and weight-matched nondiabetic controls participated. Subjects walked around an ∼200-m open-level walkway for 10 min at their comfortable pace. Continuous knee joint kinematics were recorded and used to calculate a stride interval time series for each subject. Power spectral density and detrended fluctuation analyses were used to determine whether these stride intervals exhibited long-range correlations. If the loss of long-range correlations indicates deterioration of the central control of gait, then changes in peripheral sensation should have no effect. If instead the loss of long-range correlations is a consequence of a general inability to regulate gait cycle timing, then a similar loss should occur in patients with peripheral locomotor disorders. Both power spectral density analyses and detrended fluctuation analyses showed that temporal correlations in the stride times of neuropathic and control subjects were statistically identical ( P = 0.954 and P = 0.974, respectively), despite slower gait speeds ( P = 0.008) and increased stride time variability ( P = 0.036) among the neuropathy patients. All subjects in both groups exhibited long-range correlations. These findings demonstrate that the normal long-range correlation structure of stride intervals is unaltered by significant peripheral sensory loss. This further supports the hypothesis that the central nervous system is involved in the regulation of long-range correlations.

The Speed-Accuracy Trade-Off in Human Gait Control When Running Towards Targets

2000 ◽  
Vol 16 (4) ◽  
pp. 331-341 ◽  
Author(s):  
Elizabeth J. Bradshaw ◽  
W.A. Sparrow
Keyword(s):  
Linear Relationship ◽  
Human Gait ◽  
Target Area ◽  
Gait Control ◽  
Trade Off ◽  
Infra Red ◽  
Run Up ◽  
Stride Duration ◽  
Speed Accuracy ◽  
Approach Time

The study examined adjustments to gait when positioning the foot within a narrow target area at the end of an approach or “run-up” similar to the take-off board in long jumping. In one task, participants (n = 24) sprinted toward and placed their foot within targets of four different lengths for 8-m and 12-m approach distances while “running through” the target. In a second task, participants (n = 12) sprinted toward and stopped with both feet in the target area. Infra-red timing lights were placed along the approach strip to measure movement times, with a camera positioned to view the whole approach to measure the total number of steps, and a second camera placed to view the final stride, which was analyzed using an in-house digitizing system to calculate the final stride characteristics. In the run-through task, a speed-accuracy trade-off showing a linear relationship (r = 0.976, p < .05) between target length and approach time was found for the 8-m amplitude. An accelerative sub-movement and a later targeting or “homing-in” sub-movement were found in the approach kinematics for both amplitudes. Final stride duration increased, and final stride velocity decreased with a decrease in target length.

Is walking a random walk? Evidence for long-range correlations in stride interval of human gait

1995 ◽  
Vol 78 (1) ◽  
pp. 349-358 ◽  
Author(s):  
J. M. Hausdorff ◽  
C. K. Peng ◽  
Z. Ladin ◽  
J. Y. Wei ◽  
A. L. Goldberger
Keyword(s):  
Time Series ◽  
Random Walk ◽  
Long Range ◽  
Power Law ◽  
Unknown Origin ◽  
Power Spectral Analysis ◽  
Gait Pattern ◽  
Human Gait ◽  
Long Range Correlations ◽  
Stride Interval

Complex fluctuations of unknown origin appear in the normal gait pattern. These fluctuations might be described as being 1) uncorrelated white noise, 2) short-range correlations, or 3) long-range correlations with power-law scaling. To test these possibilities, the stride interval of 10 healthy young men was measured as they walked for 9 min at their usual rate. From these time series, we calculated scaling indexes by using a modified random walk analysis and power spectral analysis. Both indexes indicated the presence of long-range self-similar correlations extending over hundreds of steps; the stride interval at any time depended on the stride interval at remote previous times, and this dependence decayed in a scale-free (fractallike) power-law fashion. These scaling indexes were significantly different from those obtained after random shuffling of the original time series, indicating the importance of the sequential ordering of the stride interval. We demonstrate that conventional models of gait generation fail to reproduce the observed scaling behavior and introduce a new type of central pattern generator model that successfully accounts for the experimentally observed long-range correlations.

Does human gait exhibit comparable and reproducible long-range autocorrelations on level ground and on treadmill?

2010 ◽  
Vol 32 (3) ◽  
pp. 369-373 ◽  
Author(s):  
Benjamin Bollens ◽  
Frédéric Crevecoeur ◽  
Virginie Nguyen ◽  
Christine Detrembleur ◽  
Thierry Lejeune
Keyword(s):  
Long Range ◽  
Human Gait

Effects of age and walking speed on long-range autocorrelations and fluctuation magnitude of stride duration

Neuroscience ◽  
2012 ◽  
Vol 210 ◽  
pp. 234-242 ◽  
Author(s):  
B. Bollens ◽  
F. Crevecoeur ◽  
C. Detrembleur ◽  
E. Guillery ◽  
T. Lejeune
Keyword(s):  
Long Range ◽  
Walking Speed ◽  
Stride Duration

Variability of Human Gait: Effect of Backward Walking and Dual-Tasking on the Presence of Long-Range Autocorrelations

2013 ◽  
Vol 42 (4) ◽  
pp. 742-750 ◽  
Author(s):  
Benjamin Bollens ◽  
Frédéric Crevecoeur ◽  
Christine Detrembleur ◽  
Thibault Warlop ◽  
Thierry M. Lejeune
Keyword(s):  
Long Range ◽  
Human Gait ◽  
Dual Tasking ◽  
Backward Walking

Fractal dynamics of human gait: stability of long-range correlations in stride interval fluctuations

1996 ◽  
Vol 80 (5) ◽  
pp. 1448-1457 ◽  
Author(s):  
J. M. Hausdorff ◽  
P. L. Purdon ◽  
C. K. Peng ◽  
Z. Ladin ◽  
J. Y. Wei ◽  
...  
Keyword(s):  
Long Range ◽  
Healthy Subjects ◽  
Fractal Property ◽  
Dynamical Analysis ◽  
Human Gait ◽  
Locomotor System ◽  
Long Range Correlations ◽  
Power Law Decay ◽  
Stride Interval ◽  
The Stability

Fractal dynamics were recently detected in the apparently “noisy” variations in the stride interval of human walking. Dynamical analysis of these step-to-step fluctuations revealed a self-similar pattern: fluctuations at one time scale are statistically similar to those at multiple other time scales, at least over hundreds of steps, while healthy subjects walk at their normal rate. To study the stability of this fractal property, we analyzed data obtained from healthy subjects who walked for 1 h at their usual, slow, and fast paces. The stride interval fluctuations exhibited long-range correlations with power-law decay for up to 1,000 strides at all 3 walking rates. In contrast, during metronomically paced walking, these long-range correlations disappeared; variations in the stride interval were random (uncorrelated) and nonfractal. The long-range correlations observed during spontaneous walking were not affected by removal of drifts in the time series. Thus the fractal dynamics of spontaneous stride interval are normally quite robust and intrinsic to the locomotor system. Furthermore, this fractal property of neural output may be related to the higher nervous centers responsible for the control of walking rhythm.

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