A Review on the Nonlinear Dynamical System Analysis of Electrocardiogram Signal

Nayak, Suraj Kumar; Bit, Arindam; Dey, Anilesh; Mohapatra, Biswajit; Pal, Kunal

doi:10.1155/2018/6920420

Cited by 85 publications

(66 citation statements)

References 123 publications

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“…16 The most important step is the extraction of the features containing all the relevant information about the system dynamics. 32 Time-domain, frequencydomain, and non-linear methods are generally used for this procedure. While time-domain and frequency-domain methods enable the quantification of heart rate variability on different timescales, non-linear methods provide additional information regarding the dynamics and structure of beat-to-beat time series.…”

Section: Discussionmentioning

confidence: 99%

Non-linear analysis of heart rate variability for evaluating the acute effects of caffeinated beverages in young adults

ÇALIŞKAN

Bilgin

2020

Cardiol Young

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AbstractCaffeinated beverages are the most consumed substances in the world. High rate of uptake of these beverages leads to various cardiovascular disorders ranging from palpitations to coronary failure. The objective of the study is to ascertain how the complexity parameters of heart rate variability are affected by acute consumption of caffeinated beverages in young adults.Electrocardiogram measurements were performed before consuming drinks. After consuming the drinks, measurements were done again at 30 minutes and 60 minutes. Heart rate variability signals were acquired from electrocardiogram signals. Also, the signals were reconstructed in the phase space and largest Lyapunov exponent, correlation dimension, approximate entropy, and detrended fluctuation analysis values were calculated.Heart rate increased for energy drink and cola groups but not in coffee group. Non-linear parameter values of energy drink, coffee, and cola group are increased within 60 minutes after drink consumption. This change is statistically significant just for energy drink group.Energy drink consumption increases the complexity of the cardiovascular system in young adults significantly. Coffee and cola consumption have no significant effect on the non-linear parameters of heart rate variability.

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Section: Discussionmentioning

confidence: 99%

Non-linear analysis of heart rate variability for evaluating the acute effects of caffeinated beverages in young adults

ÇALIŞKAN

Bilgin

2020

Cardiol Young

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“…The ECG signal is nonlinear and non-stationary. ECG signal processing and feature extractions are more robust with nonlinear methods (52). The most important features of an ECG signal (see Figure 14) are (1) Pre-processing:…”

Section: Background Prior Work and Proposed Algorithmmentioning

confidence: 99%

Multichannel ECG Recording from Waist using Textile Sensors

Alizadeh-Meghrazi

Tian

Mahnam³

et al. 2020

Preprint

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Background: The development of wearable health monitoring systems is garnering tremendous interest in research, technology and commercial applications. Their ability of providing unique capabilities in continuous, real-time, and non-invasive tracking of the physiological markers of users can provide insights into the performance and health of individuals. Electrocardiogram (ECG) signals are of particular interest, as cardiovascular disease is the leading cause of death globally. Monitoring heart health and its conditions such as ventricular disturbances and arrhythmias can be achieved through evaluating various features of ECG such as R-peaks, QRS complex, T-wave, and P-wave. Despite recent advances in biosensors for wearable applications, most of the currently available solutions rely solely on a single system attached to the body, limiting the ability to obtain reliable and multi-location biosignals. However, in engineering systems, sensor fusion, which is the optimal integration and processing of data from multiple sensors, has been a common theme and should be considered for wearables. In recent years, due to an increase in the availability and variety of different types of sensors, the possibility of achieving sensor fusion in wearable systems has become more attainable. Sensor fusion in multi-sensing systems results in significant enhancements of information inferences compared to those from systems with a sole sensor. One step towards the development of sensor fusion for wearable health monitoring systems is the accessibility to multiple reliable electrophysiological signals, which can be recorded continuously.Results: In this paper, we develop a textile-based multi-channel ECG band that has the ability to measure ECG from multiple locations on the waist. As a proof of concept, we demonstrate that ECG signals can be reliably obtained from different locations on the waist where the shape of the QRS complex is nearly comparable with recordings from the chest using traditional gel electrodes. In addition, we develop a probabilistic approach – based on prediction and update strategies – to detect R-Peaks from noisy textile data in different statuses, including sitting, standing, and jogging. In this approach, an optimal search method is utilized to detect R-Peaks based on the history of the intervals between previously detected R-Peaks. We show that the performance of our probabilistic approach in R-Peak detection is significantly better than that based on Pan-Tompkins and optimal-threshold methods. Conclusion: A textile-based multi-channel ECG band was developed to track the heart rate changes from multiple locations on the waist. We demonstrated that (i) the ECG signal can be detected from different locations on the waist, and (ii) the accuracy of the detected R-Peaks from textile sensors was improved by using our proposed probabilistic approach.Despite the limitations of the textile sensors that might compromise the quality of ECG signals,we anticipate that the textile-based multi-channel ECG band can be considered as an effective wearable system to facilitate the development of sensor fusion methodology for pervasive and non-invasive health monitoring through continuous tracking of heart rate variability (HRV) from the waist. In addition, from the commercialization point of view, we anticipate that the developed band has the potential to be integrated into garments such as underwear, bras or pants so that individuals can use it on a daily basis.

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“…The features based on nonlinear dynamical systems like the correlation dimension, Lyapunov exponents, and entropy-based parameters explored in the previous studies. A useful review of the work of nonlinear analysis can refer to [41,42]. Typically, the nonlinear dynamic system methods are used in the atrial fibrillation analysis or long term ECG heart rate variability analysis.…”

Section: The Heart As Dynamical Systemsmentioning

confidence: 99%

Persistence Landscape based Topological Data Analysis for Personalized Arrhythmia Classification

Yan¹,

Ivanov²,

Cen³

et al. 2019

Preprint

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Data can be illustrated in shapes, and the shapes could provide insight for data modeling and information extraction. Topological data analysis provides an alternative insight in biomedical data analysis and knowledge discovery with the algebra topology tools. In present work, we study the application of topological data analysis for personalized electrocardiographic signal classification toward arrhythmia analysis. Using phase space reconstruction technique, the signal samples are converted into point clouds for topological analysis facility. With topological techniques the persistence landscapes from the point clouds are extracted as features to perform the arrhythmia classification task. We find that the proposed method is robust to the training set size, with only a training set size of 20% percents, the normal heartbeat class are 100% recognized, ventricular beats for 97.13%, supra-ventricular beats for 94.27% and fusion beats for 94.27% within the corresponding experiments. The property of keeping high performance when using smaller training sample proves that the proposed method is especially applicable to personalized analysis. With the present study, we show that the topological data analysis technique could be a useful tool in biomedical signal analysis, and provide powerful ability in personalized analysis.

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A Review on the Nonlinear Dynamical System Analysis of Electrocardiogram Signal

Cited by 85 publications

References 123 publications

Non-linear analysis of heart rate variability for evaluating the acute effects of caffeinated beverages in young adults

Non-linear analysis of heart rate variability for evaluating the acute effects of caffeinated beverages in young adults

Multichannel ECG Recording from Waist using Textile Sensors

Persistence Landscape based Topological Data Analysis for Personalized Arrhythmia Classification

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