Multifractal analysis of electronic cardiogram taken from healthy and unhealthy adult subjects

Wang, Jun; Ning, Xinbao; Chen, Ying

doi:10.1016/s0378-4371(03)00045-1

Cited by 46 publications

(27 citation statements)

References 12 publications

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“…Amaral et al [72] also reported the multifractal behavior of HRV. Wang et al [73] too analyzed ECG signals of healthy young adult subjects and old ones and characterized their multifractality.…”

Section: Translational Biomedicine Issn 2172-0479mentioning

confidence: 99%

Epileptic Seizure: A New Approach for Quantification of Autonomic Deregulation with Chaos Based Technique

Ghosh¹,

Dutta²,

Chakraborty³

et al. 2017

Transl Biomed

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Background: Epileptic seizures can lead to changes in autonomic function affecting the sympathetic, parasympathetic and enteric nervous systems. Changes in cardiac signals are potential biomarkers that may provide an extracerebral indicator of ictal onset in some patients. Patients suffering from epilepsy experience some significant cardiac changes during seizure, causing some serious cardiac malfunctions which may lead to sudden unexpected death (SUDEP). The fluctuations observed in the heart rate during the process are non-linear and extremely complex. Chaos based non-linear methodology has become a very powerful tool in recent years in analysing such complex systems. Although a few papers on effect of seizure have been reported where study was done to assess the dynamics of cardiac systems for post-ictal patients not using non-linear technique, this paper reports the analysis of ECG signals of post-ictal patients using a modern and rigorous non-linear technique.

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Section: Translational Biomedicine Issn 2172-0479mentioning

confidence: 99%

Epileptic Seizure: A New Approach for Quantification of Autonomic Deregulation with Chaos Based Technique

Ghosh¹,

Dutta²,

Chakraborty³

et al. 2017

Transl Biomed

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“…SD2 is defined as the standard deviation of the projection of the Poincaré plot on the line of identify (y=x) and SD1 is the standard deviation of projection of the Poincaré plot on the line perpendicular to the line of identify. These parameters can be defined by (11), (12) and (13 …”

Section: Poincaré Plotmentioning

confidence: 99%

“…Each record contains information of around 100,000 heartbeats. The first problem is based on the fact that fluctuation of the physiological signals possesses hidden information in the form of self-similarity, scale structure, monofractality and multifractality, through the application of these methods [8][9][10][11][12][13]. The fractal, multifractal and wavelet-based multifractal analysis of the fluctuations is useful not only for getting the comprehensive information for physiological signals of patients, but also provide a possibility for foresight, prognosis and prevention of the pathological statuses.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Heart Rate Variability by Applying Nonlinear Methods with Different Approaches for Graphical Representation of Results

Gospodinova¹,

Gospodinov²,

Domuschiev³

et al. 2015

ijacsa

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Abstract-There is an open discussion over nonlinear properties of the Heart Rate Variability (HRV) which takes place in most scientific studies nowadays. The HRV analysis is a noninvasive and effective tool that manages to reflect the autonomic nervous system regulation of the heart. The current study presents the results of HRV analysis based on 24-hour Holter ECG signals of healthy and unhealthy subjects. Analysis of heart intervals is performed with the use of original algorithms and software, developed by the authors, to quantify the irregularity of the heart rate. The main aim is the formation of the parametric estimate of patients' health status, based on mathematical methods that are applied on cardiac physiology. The obtained results show that the analysis of Holter recordings by nonlinear methods may be appropriate for diagnostic, forecast and prevention of the pathological cardiac statuses. Different approaches of graphical representation and visualization of these results are used in order to verify this.

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“…The problem of chaotic systems (CSs) investigation while their temporal evolution simulated on data measured or obtained from respective differential equations has become a problem of great significance in various fields of physics [1], as well as in medicine and engineering [1][2][3]. Time series (TS) obtained from a CS are essentially nonlinear [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

“…Time series (TS) obtained from a CS are essentially nonlinear [1][2][3]. and often lead to a multidimensional attractor in a relevant phase space [3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Localized Approaches for Nonlinear Analysis of Chaotic Systems in Multidimensional Phase Space

Dailyudenko¹

2009

TOCSJ

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Abstract:In this paper, we develop algorithms for calculation of fractal measures and characteristic exponents for modeling of chaotic systems evolution. Using temporal localization along phase trajectories of a chaotic attractor reconstructed from nonlinear time series, we achieve the essential reduction of required computer resources that allows the nonlinear analysis algorithms to be realized even for higher-dimensional cases and provides their robustness to enlarging the length of time series. The numerical simulations confirm reliability of the developed algorithms and their high efficiency at calculation of fractal dimension.

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Multifractal analysis of electronic cardiogram taken from healthy and unhealthy adult subjects

Cited by 46 publications

References 12 publications

Epileptic Seizure: A New Approach for Quantification of Autonomic Deregulation with Chaos Based Technique

Epileptic Seizure: A New Approach for Quantification of Autonomic Deregulation with Chaos Based Technique

Analysis of Heart Rate Variability by Applying Nonlinear Methods with Different Approaches for Graphical Representation of Results

Localized Approaches for Nonlinear Analysis of Chaotic Systems in Multidimensional Phase Space

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