Detecting high-dimensional determinism in time series with application to human movement data

Ramdani, Sofiane; Bouchara, Frédéric; Caron, Olivier

doi:10.1016/j.nonrwa.2011.12.017

Cited by 5 publications

(3 citation statements)

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“…The mean frequencies of the successive components were 0.5 Hz, 1–1.5 Hz, 3-4 Hz, and 6–8 Hz. The age related differences were observed in the parameters “area of Hilbert transform” and “average rotation frequency.” A similar decomposition was also presented by Ramdani et al [ 9 ]. Amoud et al [ 8 ] showed the differences between age groups both using basic-EMD with separate analysis for x and y components and using complex-EMD where the interdependence between x and y components is not removed.…”

Section: The Posturographic Signalsupporting

confidence: 81%

The Filtering of the Posturographic Signals Shows the Age Related Features

Michalak

Przekoracka-Krawczyk

Nawrot

et al. 2014

The Scientific World Journal

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Objective. Lower frequencies of slow oscillations of the posturographic signals can be removed using high-pass filtering. This procedure releases postural reflexes possessing higher frequencies and lower amplitude range. Mutual dependence between the x and y components of posturographic signals was analyzed using principal component analysis (PCA). The posturographic signals of old patients with idiopathic gait disturbance were compared with the control group of similar age and with younger patients. There was also the analysis of the influence of the eyes state (open versus closed) and the head position (normal or bent back). The statistically significant differences in the mutual dependence between x and y components between the groups of patients were analyzed using MANOVA. The significant differences were observed mainly in the range of filter frequencies f = 0.1–1.5 Hz and f = 2.2–5.5 Hz with a maximum effect at approximately 4-5 Hz. A detailed post-hoc analysis is also presented. The differences in the higher frequency range suggest the main disturbance to be connected with the spinal reflexes. Visual and vestibular support appear insufficient for postural stability control in the idiopathic gait disturbance group. The results suggest that idiopathic gait disturbance is the final stage of the aging process of postural system.

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Section: The Posturographic Signalsupporting

confidence: 81%

The Filtering of the Posturographic Signals Shows the Age Related Features

Michalak

Przekoracka-Krawczyk

Nawrot

et al. 2014

The Scientific World Journal

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“…Second, Thelen ( 1981 ) observed that infants produce rhythmical movements whenever there is a change of stimulus, so this variable should be explored in a way that takes the time sequencing of tasks into account (e.g. Ramdani, Bouchara, & Caron, 2012 ).…”

Section: Discussionmentioning

confidence: 99%

Social interaction is associated with changes in infants’ motor activity

Scola

Bourjade

Jover

2015

Socioaffective Neuroscience & Psychology

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BackgroundIn developmental research, infants are commonly assumed to be early stakeholders in interactions with their caregivers. The tools that infants can use to interact with others vary from visual contact to smiling or vocalizing, and also include motor activity. However, surprisingly few studies have explored how the nature and context of social interactions affect infants’ engagement in motor activity.MethodsWe investigated the kinematic properties of foot and face movements produced by 11 infants aged between 5 and 9 months during six contrasting dyadic episodes (i.e. passive presence of a stranger or the infant's mother, weak or intense interaction with the stranger/mother as she sings a nursery play song).ResultsThe infants’ face and foot motor activity was significantly reduced during the interactive episodes, compared with the episodes without any interaction, in both the mother and stranger conditions. Furthermore, the level of their motor activity was significantly lower in the stranger condition than in the mother one for some parameters.ConclusionThese results are in line with those reported by previous studies and confirm the relevance of using motor activity to delineate the early forms of interactive episodes in infants.

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“…Consequently, many realworld applied systems that may seem to have random nature can possess a nonlinear deterministic and potentially chaotic behavior. In this line, with the introduction of the ability to model and predict the future of chaotic time series through nonlinear deterministic system theory, many researchers have attempted to study and detect chaos in time series of multidisciplinary fields [12,13]. Also, complex nonlinear dynamical modeling and analysis have recently become more important in advanced science approaches [14][15][16] and [17].…”

Section: Introductionmentioning

confidence: 99%

Identification of Chaos in Financial Time Series to Forecast Nonperforming Loan

Ahmadi

Aghababa

Kalbkhani

2022

Mathematical Problems in Engineering

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This paper discusses the importance of modeling financial time series as a chaotic dynamic rather than a stochastic system. The dynamical properties of a financial time series of an economic institution in Iran were analyzed to identify the potential occurrence of the low-dimensional deterministic chaos. This paper applies several classic nonlinear techniques for detecting the chaotic nature of the time series of loan payment portion and proposes a modified nonlinear predictor scheme for forecasting the future levels of the nonperforming loan. The auto mutual information was implemented to estimate the delay time dimension, and Cao’s approach, along with correlation dimension methodology, quantified the embedding dimension of the time series. The results reveal a low embedding dimension implying the chaotic nature exists in the financial data. The maximum Lyapunov exponent measure is also adopted to investigate the divergence or convergence of the trajectories. Since positive Lyapunov exponents are revealed, the long-term unpredictability of the time series is proved. Lastly, a modified nonlinear local approximator is developed to forecast the short-term history of the time series. Numerical simulations are provided to illustrate the adopted nonlinear techniques. The results reported in this paper could have implications for commercial bank managers who could use the nonlinear models for early detection of the possible nonperforming loans before they become uncontrollable.

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Detecting high-dimensional determinism in time series with application to human movement data

Cited by 5 publications

References 73 publications

The Filtering of the Posturographic Signals Shows the Age Related Features

The Filtering of the Posturographic Signals Shows the Age Related Features

Social interaction is associated with changes in infants’ motor activity

Identification of Chaos in Financial Time Series to Forecast Nonperforming Loan

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