Multifractality in time series of human gait

Muñoz-Diosdado, Alejandro; Correa, J. L. del Río; brown, atlas

doi:10.1109/iembs.2003.1279763

Cited by 12 publications

(17 citation statements)

References 8 publications

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“…Unlike the results reported we found that the multifractality degree in series from CHF patients was bigger than the series from healthy subjects, this happened because Muñoz and colls [4] analyzed only a subsample of the series from Physionet and not all the database. Figure 3a shows the multifractality degrees of complete series.…”

Section: -3contrasting

confidence: 55%

“…Multifractal spectra of the heartbeat interval series of healthy people show a tendency to be right skewed and in the spectra of diseased subjects there is a tendency to be left skewed [4]. The results show the possibility of characterizing the health status of an individual as compared with parameters obtained through the analysis with nonlinear dynamics techniques, so this kind of analysis can be useful as a prediagnosis tool.…”

Section: Introductionmentioning

confidence: 75%

“…From multifractal spectrum (MSp) the multifractality degree can be obtained, it is defined as the multifractal spectrum width and can be interpreted as a measure of the system complexity, it provides how nonlinear and non-stationary the time series is. This is important because it has been found [4] that the heartbeat interval series of healthy people are very complex. However, for ill and old people the complexity of this series is decreased.…”

Section: Introductionmentioning

confidence: 99%

“…There have been several studies [1 -5] that involve the analysis of heart rate variability by using nonlinear dynamics methods; particularly, multifractal analysis has been used to study time series obtain from physiological variables [3,4]. From multifractal spectrum (MSp) the multifractality degree can be obtained, it is defined as the multifractal spectrum width and can be interpreted as a measure of the system complexity, it provides how nonlinear and non-stationary the time series is.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Acquisition software development for monitor Holter prototype signals and its use for pre-diagnosis of cardiac damage based on nonlinear dynamic techniques

Justo¹,

Calleja²,

Muñoz-Diosdado³

2016

AIP Conference Proceedings

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Section: -3contrasting

confidence: 55%

Section: Introductionmentioning

confidence: 75%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Acquisition software development for monitor Holter prototype signals and its use for pre-diagnosis of cardiac damage based on nonlinear dynamic techniques

Justo¹,

Calleja²,

Muñoz-Diosdado³

2016

AIP Conference Proceedings

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“…Another parameter of interest is the width of the singularity spectrum W = α max − α min , can be obtained from a quadratic fit to the f (α) versus α data and then extrapolating it to f (α max ) = f (α min ) = 0. Parameters α 0 , B and W are used as a measure of "complexity" of the process under consideration [34], and hence they are called the "complexity parameters". Roughly specking, a smaller value of α 0 implies the underlying process is more regular in appearance.…”

Section: Results Of Mf-dfa Analysismentioning

confidence: 99%

Long-range memory and multifractality in gold markets

Mali

Mukhopadhyay

2015

Phys. Scr.

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Abstract. Long-range correlation and fluctuation in the gold market time series of world's two leading gold consuming countries, namely China and India, are studied. For both the market series during the period 1985-2013 we observe a long-range persistence of memory in the sequences of maxima (minima) of returns in successive time windows of fixed length, but the series as a whole are found to be uncorrelated. Multifractal analysis for these series as well as for the sequences of maxima (minima) is carried out in terms of the multifractal detrended fluctuation analysis (MF-DFA) method. We observe a weak multifractal structure for the original series that is mainly originated from the fat-tailed probability distribution function of the values, and the multifractal nature of the original time series is enriched into their sequences of maximal (minimal) returns. A quantitative measure of multifractality is provided by using a set of "complexity parameters".

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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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Multifractality in time series of human gait

Cited by 12 publications

References 8 publications

Acquisition software development for monitor Holter prototype signals and its use for pre-diagnosis of cardiac damage based on nonlinear dynamic techniques

Acquisition software development for monitor Holter prototype signals and its use for pre-diagnosis of cardiac damage based on nonlinear dynamic techniques

Long-range memory and multifractality in gold markets

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

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