WAVELET SAMPLE ENTROPY OPTIMIZATION THROUGH OPTIMAL MOTHER FUNCTION SELECTION FOR ATRIAL FIBRILLATION ANALYSIS

2010 ◽  
Keyword(s):  
Atrial Fibrillation ◽  
Sample Entropy ◽  
Entropy Optimization ◽  
Selection For ◽  
Function Selection

RULES AND PRINCIPLES OF PATIENT SELECTION FOR SURGICAL TREATMENT OF ACQUIRED HEART DISEASES COMPLICATED BY ATRIAL FIBRILLATION

2017 ◽  
Vol 32 (3) ◽  
pp. 29-34 ◽  
Author(s):  
V. V. Evtushenko ◽  
I. S. Makogonchuk ◽  
A. V. Evtushenko
Keyword(s):  
Atrial Fibrillation ◽  
Surgical Treatment ◽  
Patient Selection ◽  
Heart Diseases ◽  
Rules And Principles ◽  
Selection For

scholarly journals Sample Entropy Analysis of Noisy Atrial Electrograms during Atrial Fibrillation

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Eva María Cirugeda-Roldán ◽  
Antonio Molina Picó ◽  
Daniel Novák ◽  
David Cuesta-Frau ◽  
Vaclav Kremen
Keyword(s):  
Atrial Fibrillation ◽  
Heart Rhythm ◽  
Heart Tissue ◽  
Sample Entropy ◽  
Mapping Technique ◽  
Atrial Electrograms ◽  
Invasive Method ◽  
Atrial Electrogram ◽  
Focal Atrial Tachycardia ◽  
Class Segmentation

Most cardiac arrhythmias can be classified as atrial flutter, focal atrial tachycardia, or atrial fibrillation. They have been usually treated using drugs, but catheter ablation has proven more effective. This is an invasive method devised to destroy the heart tissue that disturbs correct heart rhythm. In order to accurately localise the focus of this disturbance, the acquisition and processing of atrial electrograms form the usual mapping technique. They can be single potentials, double potentials, or complex fractionated atrial electrogram (CFAE) potentials, and last ones are the most effective targets for ablation. The electrophysiological substrate is then localised by a suitable signal processing method. Sample Entropy is a statistic scarcely applied to electrograms but can arguably become a powerful tool to analyse these time series, supported by its results in other similar biomedical applications. However, the lack of an analysis of its dependence on the perturbations usually found in electrogram data, such as missing samples or spikes, is even more marked. This paper applied SampEn to the segmentation between non-CFAE and CFAE records and assessed its class segmentation power loss at different levels of these perturbations. The results confirmed that SampEn was able to significantly distinguish between non-CFAE and CFAE records, even under very unfavourable conditions, such as 50% of missing data or 10% of spikes.

scholarly journals Sample Entropy in Electrocardiogram During Atrial Fibrillation

2018 ◽  
Vol 61 (1) ◽  
pp. 049-057 ◽  
Author(s):  
Takuya Horie ◽  
Naoto Burioka ◽  
Takashi Amisaki ◽  
Eiji Shimizu
Keyword(s):  
Atrial Fibrillation ◽  
Sample Entropy

Atrial activity selection for atrial fibrillation ECG recordings

2013 ◽  
Vol 43 (10) ◽  
pp. 1628-1636 ◽  
Author(s):  
Felipe I. Donoso ◽  
Rosa L. Figueroa ◽  
Eduardo A. Lecannelier ◽  
Esteban J. Pino ◽  
Alejandro J. Rojas
Keyword(s):  
Atrial Fibrillation ◽  
Atrial Activity ◽  
Selection For

Adaptive service function selection for Network Function Virtualization networking

2019 ◽  
Vol 91 ◽  
pp. 108-123 ◽  
Author(s):  
Yi-Wei Ma ◽  
Jiann-Liang Chen ◽  
Jia-Yi Jhou
Keyword(s):  
Network Function Virtualization ◽  
Service Function ◽  
Network Function ◽  
Selection For ◽  
Function Selection

scholarly journals An Automatic Subject Specific Intrinsic Mode Function Selection for Enhancing Two-Class EEG-Based Motor Imagery-Brain Computer Interface

2019 ◽  
Vol 19 (16) ◽  
pp. 6938-6947 ◽  
Author(s):  
Pramod Gaur ◽  
Ram Bilas Pachori ◽  
Hui Wang ◽  
Girijesh Prasad
Keyword(s):  
Motor Imagery ◽  
Brain Computer Interface ◽  
Intrinsic Mode Function ◽  
Computer Interface ◽  
Mode Function ◽  
Subject Specific ◽  
Selection For ◽  
Function Selection

scholarly journals Model Selection for Univariable Fractional Polynomials

2017 ◽  
Vol 17 (3) ◽  
pp. 619-629 ◽  
Author(s):  
Patrick Royston
Keyword(s):  
Test Procedure ◽  
Selection Procedure ◽  
Real Data ◽  
Parametric Modeling ◽  
Royal Statistical Society ◽  
Fractional Polynomials ◽  
Fractional Polynomial ◽  
Polynomial Models ◽  
Selection For ◽  
Function Selection

Since Royston and Altman's 1994 publication ( Journal of the Royal Statistical Society, Series C 43: 429–467), fractional polynomials have steadily gained popularity as a tool for flexible parametric modeling of regression relationships. In this article, I present fp_select, a postestimation tool for fp that allows the user to select a parsimonious fractional polynomial model according to a closed test procedure called the fractional polynomial selection procedure or function selection procedure. I also give a brief introduction to fractional polynomial models and provide examples of using fp and fp_select to select such models with real data.

scholarly journals Selection for atrial fibrillation ablation: Importance of diastolic function grading

2015 ◽  
Vol 65 (6) ◽  
pp. 479-486 ◽  
Author(s):  
Thomas Pezawas ◽  
Thomas Binder ◽  
Robin Ristl ◽  
Barbara Schneider ◽  
Stefan Stojkovic ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Diastolic Function ◽  
Atrial Fibrillation Ablation ◽  
Selection For
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