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

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

Multi-Objective Optimization of Human Gait With a Discomfort Function

2016 ◽  
Author(s):  
Hyun-Jung Kwon ◽  
Hyun-Joon Chung ◽  
Yujiang Xiang
Keyword(s):  
Joint Torque ◽  
Upper Body ◽  
Whole Body ◽  
Human Gait ◽  
Multi Objective Optimization ◽  
Joint Angles ◽  
Backward Walking ◽  
Multi Objective ◽  
Body Model ◽  
Neutral Angle

The objective of this study was to develop a discomfort function for including a high DOF upper body model during walking. A multi-objective optimization (MOO) method was formulated by minimizing dynamic effort and the discomfort function simultaneously. The discomfort function is defined as the sum of the squares of deviation of joint angles from their neutral angle positions. The dynamic effort is the sum of the joint torque squared. To investigate the efficacy of the proposed MOO method, backward walking simulation was conducted. By minimizing both dynamic effort and the discomfort function, a 3D whole body model with a high DOF upper body for walking was demonstrated successfully.

scholarly journals Digital Natives and Dual Task: Handling It But Not Immune Against Cognitive-Locomotor Interferences

2019 ◽  
Author(s):  
Dierick Frédéric ◽  
Buisseret Fabien ◽  
Renson Mathieu ◽  
Luta Adèle Mae
Keyword(s):  
Long Range ◽  
Dual Task ◽  
Digital Natives ◽  
Safety Index ◽  
Dual Tasks ◽  
Dual Tasking ◽  
Stride Interval ◽  
Task Conditions ◽  
Relative Change ◽  
Raven’S Matrices

AbstractDigital natives developed in an electronic dual tasking world. This paper addresses two questions. Do digital natives respond differently under a cognitive load realized during a locomotor task in a dual-tasking paradigm and how does this address the concept of safety? We investigate the interplay between cognitive (talking and solving Raven’s matrices) and locomotor (walking on a treadmill) tasks in a sample of 17 graduate level participants. The costs of dual-tasking on gait were assessed by studying changes in stride interval time and its variability at long-range. A safety index was designed and computed from total relative change between the variability indices in the single walking and dual-task conditions. As expected, results indicate high Raven’s scores with gait changes found between the dual task conditions compared to the single walking task. Greater changes are observed in the talking condition compared to solving Raven’s matrices, resulting in high safety index values observed in 5 participants. We conclude that, although digital natives are efficient in performing the dual tasks when they are not emotional-based, modification of gait are observable. Due to the variation within participants and the observation of high safety index values in several of them, individuals that responded poorly to low cognitive loads should be encouraged to not perform dual task when executing a primate task of safety to themselves or others.

The Effects of Aging and Dual Tasking on Human Gait Complexity During Treadmill Walking: A Comparative Study Using Quantized Dynamical Entropy and Sample Entropy

2017 ◽  
Vol 140 (1) ◽  
Author(s):  
Samira Ahmadi ◽  
Christine Wu ◽  
Nariman Sepehri ◽  
Anuprita Kantikar ◽  
Mayur Nankar ◽  
...  
Keyword(s):  
Complexity Analysis ◽  
Center Of Pressure ◽  
Age Groups ◽  
Sample Entropy ◽  
Human Gait ◽  
Secondary Tasks ◽  
Dual Tasking ◽  
Dynamical Entropy ◽  
Dynamical Features ◽  
Effects Of Aging

Quantized dynamical entropy (QDE) has recently been proposed as a new measure to quantify the complexity of dynamical systems with the purpose of offering a better computational efficiency. This paper further investigates the viability of this method using five different human gait signals. These signals are recorded while normal walking and while performing secondary tasks among two age groups (young and older age groups). The results are compared with the outcomes of previously established sample entropy (SampEn) measure for the same signals. We also study how analyzing segmented and spatially and temporally normalized signal differs from analyzing whole data. Our findings show that human gait signals become more complex as people age and while they are cognitively loaded. Center of pressure (COP) displacement in mediolateral direction is the best signal for showing the gait changes. Moreover, the results suggest that by segmenting data, more information about intrastride dynamical features are obtained. Most importantly, QDE is shown to be a reliable measure for human gait complexity analysis.

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.

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

Arm Swing during Human Gait Studied by EMG of Upper Limb Muscles

2014 ◽  
pp. 129-160 ◽  
Author(s):  
Johann P. Kuhtz-Buschbeck ◽  
Antonia Frendel ◽  
Bo Jing
Keyword(s):  
Muscle Activity ◽  
Normal Subjects ◽  
Load Carriage ◽  
Human Gait ◽  
Emg Activity ◽  
Active Components ◽  
Arm Swing ◽  
Kinematic Data ◽  
Backward Walking ◽  
Clinical Investigations

Arm swing during human gait has both passive and active components. The chapter presents a study conducted with normal subjects using electromyography (EMG) to describe patterns of arm and shoulder muscle activity in different gait conditions. These included normal forward walking, walking with immobilized arms, backward walking, power walking with accentuated arm swing, running, and load carriage. Complementary kinematic data are presented, too. Rhythmic muscle activity persists to some extent when both arms are immobilized during walking. Forward and backward walking involve dissimilar patterns of muscle activity, although the limb movements are very similar in both conditions. Likewise, power walking and running are characterized by different curves of EMG activity. Unimanual load carriage during walking affects muscle activities of both the loaded and the non-loaded arm. Research on normal arm swing provides a basis for clinical investigations of gait disorders.

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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