Fractal and multifractal analysis: a review
R Lopes, N Betrouni - Medical image analysis, 2009 - Elsevier
Over the last years, fractal and multifractal geometries were applied extensively in many
medical signal (1D, 2D or 3D) analysis applications like pattern recognition, texture analysis …
medical signal (1D, 2D or 3D) analysis applications like pattern recognition, texture analysis …
State‐of‐the‐art machine learning techniques aiming to improve patient outcomes pertaining to the cardiovascular system
With the digitization of all records and processes, and prevalence of cloud-driven services
and Internet of Things, today's era can truly be considered as an era of data. Machine …
and Internet of Things, today's era can truly be considered as an era of data. Machine …
Ventricular fibrillation and tachycardia classification using a machine learning approach
Q Li, C Rajagopalan, GD Clifford - IEEE Transactions on …, 2013 - ieeexplore.ieee.org
Correct detection and classification of ventricular fibrillation (VF) and rapid ventricular
tachycardia (VT) is of pivotal importance for an automatic external defibrillator and patient …
tachycardia (VT) is of pivotal importance for an automatic external defibrillator and patient …
Approximate entropy as a diagnostic tool for machine health monitoring
This paper presents a new approach to machine health monitoring based on the
Approximate Entropy (ApEn), which is a statistical measure that quantifies the regularity of a …
Approximate Entropy (ApEn), which is a statistical measure that quantifies the regularity of a …
Interpretation of the Lempel-Ziv complexity measure in the context of biomedical signal analysis
Lempel-Ziv complexity (LZ) and derived LZ algorithms have been extensively used to solve
information theoretic problems such as coding and lossless data compression. In recent …
information theoretic problems such as coding and lossless data compression. In recent …
Detection of life-threatening arrhythmias using feature selection and support vector machines
F Alonso-Atienza, E Morgado… - IEEE Transactions …, 2013 - ieeexplore.ieee.org
Early detection of ventricular fibrillation (VF) and rapid ventricular tachycardia (VT) is crucial
for the success of the defibrillation therapy. A wide variety of detection algorithms have been …
for the success of the defibrillation therapy. A wide variety of detection algorithms have been …
[KNIHA][B] Applied nonlinear time series analysis: applications in physics, physiology and finance
M Small - 2005 - books.google.com
Nonlinear time series methods have developed rapidly over a quarter of a century and have
reached an advanced state of maturity during the last decade. Implementations of these …
reached an advanced state of maturity during the last decade. Implementations of these …
Feature extraction for ECG heartbeats using higher order statistics of WPD coefficients
This paper describes feature extraction methods using higher order statistics (HOS) of
wavelet packet decomposition (WPD) coefficients for the purpose of automatic heartbeat …
wavelet packet decomposition (WPD) coefficients for the purpose of automatic heartbeat …
IoT-based ECG monitoring for arrhythmia classification using Coyote Grey Wolf optimization-based deep learning CNN classifier
An electrocardiogram (ECG) is extensively used to evaluate the heart condition that can lead
to further investigate heart ailments detection of heart diseases. The process is simple …
to further investigate heart ailments detection of heart diseases. The process is simple …
Analysis of EEG background activity in Alzheimer's disease patients with Lempel–Ziv complexity and central tendency measure
In this study we have investigated the electroencephalogram (EEG) background activity in
patients with Alzheimer's disease (AD) using non-linear analysis methods. We calculated …
patients with Alzheimer's disease (AD) using non-linear analysis methods. We calculated …