Diffusion entropy analysis on the stride interval fluctuation of human gait

Cai, Shi-Min; Zhou, Pei-Ling; Yang, Huijie; Zhou, Tao; Wang, Bing–Hong; Zhao, Fangcui

doi:10.1016/j.physa.2006.10.027

Cited by 14 publications

(2 citation statements)

References 26 publications

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“…One methodology is to calculate the entropy of linear accelerations measured approximately at the center of mass [9][10][11]. A number of other studies use entropy measures like a statistical tool to assess variations in spatial-temporal variables like stride interval [12][13][14] and mini mum toe clearance [15,16], Although these studies seem to sug gest that lower complexity may correlate with healthier walking, the methodologies used are not well established, and the strength of the findings are not highly convincing.…”

Section: Introductionmentioning

confidence: 99%

Using Entropy Measures to Characterize Human Locomotion

Leverick

Szturm

2014

Journal of Biomechanical Engineering

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Entropy measures have been widely used to quantify the complexity of theoretical and experimental dynamical systems. In this paper, the value of using entropy measures to characterize human locomotion is demonstrated based on their construct validity, predictive validity in a simple model of human walking and convergent validity in an experimental study. Results show that four of the five considered entropy measures increase meaningfully with the increased probability of falling in a simple passive bipedal walker model. The same four entropy measures also experienced statistically significant increases in response to increasing age and gait impairment caused by cognitive interference in an experimental study. Of the considered entropy measures, the proposed quantized dynamical entropy (QDE) and quantization-based approximation of sample entropy (QASE) offered the best combination of sensitivity to changes in gait dynamics and computational efficiency. Based on these results, entropy appears to be a viable candidate for assessing the stability of human locomotion.

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Section: Introductionmentioning

confidence: 99%

Using Entropy Measures to Characterize Human Locomotion

Leverick

Szturm

2014

Journal of Biomechanical Engineering

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“…This suggested that when the subjects were under sound or reflexologic stimuli, the number of parallel functional processes active in the brain was less and the brain went to a more relaxed state. Shi-Min Cai et al [9] applied the DFA to investigate the scaling behavior of stride interval fluctuations of human gait. The scaling behaviors of the stride interval of human walking at norm, slow, and fast rate were similar and the long-range correlations were observed during the spontaneous walking by removal of the trend in the time series with Fourier filter.…”

Section: Related Workmentioning

confidence: 99%

Computing nonlinear features of skin conductance to build the affective detection model

Cheng

Liu

2013

2013 International Conference on Communications, Circuits and Systems (ICCCAS)

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Skin conductance (SC) is one of most important physiological signal, which has been proven to contain reliable affective information. In the paper three kinds of affective status are induced by movie clips in laboratory environments, which are happiness, sadness and fear, and the corresponding affective SC signal is collected by Biopac MP150. After preprocessing the original SC signal, several nonlinear features are computed, which include largest Lyapunov exponent, correlation dimension, approximate entropy, and Hurst exponent. Finally based on these features the classifier SVM is used to setup model of affect detection. The experimental results show it is feasible to build affective model based on SC's nonlinear features.

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Retracted: Mathematical‐based modeling and prediction of the effect of external stimuli on human gait

Namazi

Kulish

2016

Numer Methods Biomed Eng

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Human gait is defined as human locomotion that is achieved through the movement of limbs. Different limb movement patterns result in different gait patterns. Different internal and external stimuli can affect the human gait. During the years, scientists have worked on the analysis of the effect of external stimuli on human gait, but no work has been reported yet that suggests a mathematical model for analysis of this effect by linking to the nervous system. Considering the diffusion of external stimuli to the nervous system on one side and fractality of human gait on another side, in this research, for the first time, we develop a model for prediction of human gait using fractional diffusion equation. Using this model, we will predict the effect of auditory stimuli on human gait. The model developed in this research is useful not only for analysis of the effect of auditory stimuli on human gait but can be used also for analysis of different types of stimuli on subjects with healthy conditions or having some types of diseases. Copyright © 2016 John Wiley & Sons, Ltd.

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Diffusion entropy analysis on the stride interval fluctuation of human gait

Cited by 14 publications

References 26 publications

Using Entropy Measures to Characterize Human Locomotion

Using Entropy Measures to Characterize Human Locomotion

Computing nonlinear features of skin conductance to build the affective detection model

Retracted: Mathematical‐based modeling and prediction of the effect of external stimuli on human gait

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