Applications of complexity analysis in clinical heart failure

@inproceedings{Liu2017ApplicationsOC,
  title={Applications of complexity analysis in clinical heart failure},
  author={C. Liu and A. Murray},
  year={2017}
}
Heart failure is known to influence heart rhythm in patients. Complexity analysis techniques, including techniques associated with entropy, have great potential for providing a better understanding of cardiac rhythms, and for helping research in this area. We review the analysis principles of conventional time-domain analysis, frequency-domain analysis and of newer complexity analysis. We then illustrate the techniques using real clinical data, allowing a comparison of the techniques, and also… Expand

Topics from this paper

Improving Accuracy of Heart Failure Detection Using Data Refinement
TLDR
This study proposes a set of data refinement procedures, which can automatically extract heart failure segments and yield better detection of heart failure, and shows that these procedures can significantly improve the accuracy in heart failure detection. Expand
Enhancing Detection Accuracy for Clinical Heart Failure Utilizing Pulse Transit Time Variability and Machine Learning
TLDR
When combined the HRV, PTTV indices, and the predicted probabilities generated from the distance distribution matrix-based convolutional neural network models, the highest classification performances were achieved by a support vector machine classifier. Expand
A New Physically Meaningful Threshold of Sample Entropy for Detecting Cardiovascular Diseases
TLDR
A new tolerance threshold with physical meaning (rp) was proposed, which was based on the sampling resolution of physiological signals, which demonstrated that the proposed rp had better stability than rt, hence more adaptive to detect cardiovascular diseases of CHF and AF. Expand
Deep Learning Methods for Heart Sounds Classification: A Systematic Review
TLDR
An in-depth systematic review and an analysis of existing deep learning methods were performed, with an emphasis on the convolutional neural network (CNN) and recurrent neuralnetwork (RNN) methods developed over the last five years. Expand

References

SHOWING 1-10 OF 61 REFERENCES
Clinical applicability of heart rate variability analysis by methods based on nonlinear dynamics.
TLDR
A relatively large body of data indicate that altered scaling properties of R-R intervals are physiologically deleterious, which supports the notion that some nonlinear methods, such as scaling and complexity measures, give clinically valuable information for risk stratification among various patient populations. Expand
Application of the Poincaré plot to heart rate variability: a new measure of functional status in heart failure.
TLDR
The Poincaré plot pattern has potential advantages in that it allows assessment of data which are grossly non-Gaussian in distribution, and is a simple and easily implemented method which can be used in a clinical setting to augment the standard electrocardiogram to provide 'real time' visualisation of data. Expand
Linear and non-linear 24 h heart rate variability in chronic heart failure
TLDR
The information content present in spectral and non-linear analysis ofHRV in CHF patients has prognostic relevance independently from the time domain measures of HRV, and the reduction of LF power seems the best indicator among those considered. Expand
Very low frequency power of heart rate variability is a powerful predictor of clinical prognosis in patients with congestive heart failure.
TLDR
VLF power is an independent risk predictor in patients with CHF and predicted cardiac events independently of LF power, TP, DM, BNP and NYHA functional class in multivariate analysis. Expand
Clinical impact of evaluation of cardiovascular control by novel methods of heart rate dynamics
TLDR
Although the concepts of nonlinear dynamics, fractal mathematics and complexity measures of heart rate behaviour, heart rate turbulence, deceleration capacity in relation to cardiovascular physiology or various cardiovascular events are still far away from clinical medicine, they are a fruitful area for research to expand knowledge concerning the behaviour of cardiovascular oscillations in normal healthy conditions as well as in disease states. Expand
Complex heart rate variability and serum norepinephrine levels in patients with advanced heart failure.
TLDR
Complex Poincaré plots are associated with marked sympathetic activation and may provide additional prognostic information and insight into autonomic alterations and sudden cardiac death in patients with heart failure. Expand
Predicting survival in heart failure case and control subjects by use of fully automated methods for deriving nonlinear and conventional indices of heart rate dynamics.
TLDR
It is demonstrated that HRV analysis of ambulatory ECG recordings based on fully automated methods can have prognostic value in a population-based study and that nonlinear HRV indices may contribute prognosticvalue to complement traditional HRV measures. Expand
Methods derived from nonlinear dynamics for analysing heart rate variability
Methods from nonlinear dynamics (NLD) have shown new insights into heart rate (HR) variability changes under various physiological and pathological conditions, providing additional prognosticExpand
[Heart rate variability in chronic heart failure and its role in prognosis of the disease.].
TLDR
In CHF parameters of HRV are lowered compared to normal values and correlate with functional heart failure severity, and NYHA class III-IV and lowered HRV allow to identify patients with high risk of death. Expand
Decrease in the heart rate complexity prior to the onset of atrial fibrillation.
  • V. Tuzcu, Selman Nas, Tülay Börklü, A. Ugur
  • Medicine
  • Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
  • 2006
TLDR
The heart rate complexity is reduced with a significant decreasing trend as assessed by R-R interval entropy prior to the onset of AF. Expand
...
1
2
3
4
5
...