scholarly journals Multiscale Entropy Technique Discriminates Single Lead ECG’s With Normal Sinus Rhythm and Sleep Apnea

Author(s):  
Suganti Shivaram ◽  
Anjani Muthyala ◽  
Zahara Z. Meghji ◽  
Susan Karki ◽  
Shivaram Poigai Arunachalam

Sleep apnea is characterized by abnormal interruptions in breathing during sleep due to partial or complete airway obstructions affecting middle-aged men and women on an estimated ∼4% of the population [1]. While the disorder is clinically manageable to relieve patients, the challenge occurs with diagnosis, with many patients going undiagnosed leading to further complications such as ischemic heart diseases, stroke etc. Sleep apnea also significantly affects the quality of day to day life causing sleepiness and fatigue. Polysomnography (PSG) technique is currently a used for detecting sleep apnea which is a comprehensive sleep test to diagnose sleep disorders by recording brain waves, the oxygen level in the blood, heart rate, breathing, eye and leg movements during the study. However, PSG test is very expensive, requires patients to stay overnight and is known to cause inconvenience to the patients.

Entropy ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. 531
Author(s):  
Jieun Lee ◽  
Yugene Guo ◽  
Vasanth Ravikumar ◽  
Elena G. Tolkacheva

Paroxysmal atrial fibrillation (Paro. AF) is challenging to identify at the right moment. This disease is often undiagnosed using currently existing methods. Nonlinear analysis is gaining importance due to its capability to provide more insight into complex heart dynamics. The aim of this study is to use several recently developed nonlinear techniques to discriminate persistent AF (Pers. AF) from normal sinus rhythm (NSR), and more importantly, Paro. AF from NSR, using short-term single-lead electrocardiogram (ECG) signals. Specifically, we adapted and modified the time-delayed embedding method to minimize incorrect embedding parameter selection and further support to reconstruct proper phase plots of NSR and AF heart dynamics, from MIT-BIH databases. We also examine information-based methods, such as multiscale entropy (MSE) and kurtosis (Kt) for the same purposes. Our results demonstrate that embedding parameter time delay ( τ ), as well as MSE and Kt values can be successfully used to discriminate between Pers. AF and NSR. Moreover, we demonstrate that τ and Kt can successfully discriminate Paro. AF from NSR. Our results suggest that nonlinear time-delayed embedding method and information-based methods provide robust discriminating features to distinguish both Pers. AF and Paro. AF from NSR, thus offering effective treatment before suffering chaotic Pers. AF.


Medicina ◽  
2019 ◽  
Vol 55 (10) ◽  
pp. 660 ◽  
Author(s):  
Giuseppe Coppola ◽  
Girolamo Manno ◽  
Antonino Mignano ◽  
Mirko Luparelli ◽  
Antonino Zarcone ◽  
...  

Atrial fibrillation the most common cardiac arrhythmia. Its incidence rises steadily with each decade, becoming a real “epidemic phenomenon”. Cardioversion is defined as a rhythm control strategy which, if successful, restores normal sinus rhythm. This, whether obtained with synchronized shock or with drugs, involves a periprocedural risk of stroke and systemic embolism which is reduced by adequate anticoagulant therapy in the weeks before or by the exclusion of left atrial thrombi. Direct oral anticoagulants are safe, manageable, and provide rapid onset of oral anticoagulation; they are an important alternative to heparin/warfarin from all points of view, with a considerable reduction in bleedings and increase in the safety and quality of life of patients.


2014 ◽  
Vol 556-562 ◽  
pp. 2728-2731
Author(s):  
Ji Ae Park ◽  
Seok Min Hwang ◽  
Ji Won Baek ◽  
Yoon Nyun Kim ◽  
Jong Ha Lee

Supraventricular tachycardia (SVT) is the most common arrhythmia and can be found in not only heart disease patients, but also healthy persons. However, the occurrence of SVT in heart disease patients implies that the potential of the heart diseases worsening, and it causes cardiac arrest when it evolves into ventricular tachycardia or the ventricular fibrillation. Therefore, the detection of SVT arrhythmia, as a first stage, has significant implications for the prevention of cardiac arrests. In this paper, we propose the automatic diagnosis system for cardiac arrhythmias detection with great accuracy. To validate the algorithm, SVT and normal sinus rhythm are classified by the proposed algorithm.


2020 ◽  
Vol 48 ◽  
Author(s):  
André Braga de Souza ◽  
Renan Paraguassu de Sá Rodrigues ◽  
Gerson Tavares Pessoa ◽  
Andrezza Braga Soares da Silva ◽  
Laecio Da Silva Moura ◽  
...  

Background:Peccaries (Tayassu tajacu, Linnaeus, 1758) are wild suiformes that belong to the Tayassuidae family. Electrocardiography is an important technique for cardiovascular evaluation. Analysis of various intervals, segments, complexes and waveforms of electrocardiographic (ECG) traces aids in the diagnosis of cardiac alterations and in the differentiation of congenital and acquired heart diseases from physiological cases. However, in wild animal medicine, the various patterns of normality and the evaluation of electrical traces associated with heart disease have not yet been sufficiently elucidated. The purpose of this study was to characterize the electrocardiographic (ECG) traces of peccaries sedated using ketamine and xylazine.Materials, Methods & Results:Fourteen healthy adult animals that were subjected to digital ECG examination were used. Animals with evidence of systemic diseases, cardiovascular abnormalities (murmurs or arrhythmias), or any degree of valve insufficiency observed on echocardiogram and animals that exhibited excessive stress during the examination were excluded from the study. All animals presented with a normal sinus rhythm. A combination of 15 mg/kg of ketamine hydrochloride and 3 mg/kg of midazolam maleate was applied intramuscularly for chemical immobilization. The animals were manipulated after 15 min, when the onset of the anaesthetic effect was verified, for a duration of 45 min, and no reinforcement dose was necessary to complete the electrocardiographic examination.  No significant differences were observed in the P-wave duration, PR interval and QT interval between genders (P > 0.05). No significant differences were found between the amplitudes of the P and R waves between males and females (P > 0.05). The observed P waves were small, monophasic and positive. The QRS complex was positive in the DI, DII, DIII, aVF, V4 and V10 derivations and negative in the aVR, aVL, V1 and V2 derivations. In 71% of the animals, the T wave showed negative polarity in the DI, DII, DIII, aVL, aVF, and V10 derivations and positive polarity in the aVR, V1, V2 and V4 derivations. The ST segment was isoelectric in 100% of the animals. GraphPad Prism 7 (La Jolla, CA, USA) software was used to analyze the data, with non-parametric tests used to test for differences in the variables between the sexes. In these tests, a P-value of 0.05 was considered to indicate statistical significance.Discussion:Although studies on the cardiac electrophysiology of wild animals have previously shown good results for several species, this is the first study concerning the standardization ECG traces for peccaries. However, due to the wild nature of these animals, their manipulation for handling and data collection purposes is only feasible under chemical containment, although other studies have used non-anaesthetized agoutis. It is not known to what extent these results may have been influenced by the effects of stress. Drugs used for this function may have direct effects on cardiac function. Therefore, the presumed normal ECG values, as well as the recognition of changes due to drug or iatrogenic interactions, are of fundamental importance.  This protocol provided high-quality anaesthetized peccary ECG traces, allowing reliable measurements of waves and intervals and assessment of the cardiac rhythm and heart rate. The surface registry digital ECG recording technique used with chemical containment allowed good monitoring and rapid acquisition and was well tolerated by the animals.  


Author(s):  
Rashidah Funke Olanrewaju ◽  
S. Noorjannah Ibrahim ◽  
Ani Liza Asnawi ◽  
Hunain Altaf

According to World Health Organization (WHO) report an estimated 17.9 million lives are being lost each year due to cardiovascular diseases (CVDs) and is the top contributor to the death causes. 80% of the cardiovascular cases include heart attacks and strokes. This work is an effort to accurately predict the common heart diseases such as arrhythmia (ARR) and congestive heart failure (CHF) along with the normal sinus rhythm (NSR) based on the integrated model developed using continuous wavelet transform (CWT) and deep neural networks. The proposed method used in this research analyses the time-frequency features of an electrocardiogram (ECG) signal by first converting the 1D ECG signals to the 2D Scalogram images and subsequently the 2D images are being used as an input to the 2D deep neural network model-AlexNet. The reason behind converting the ECG signals to 2D images is that it is easier to extract deep features from images rather than from the raw data for training purposes in AlexNet. The dataset used for this research was obtained from Massachusetts Institute of Technology-Boston's Beth Israel Hospital (MIT-BIH) arrhythmia database, MIT-BIH normal sinus rhythm database and Beth Israel Deaconess Medical Center (BIDMC) congestive heart failure database. In this work, we have identified the best fit parameters for the AlexNet model that could successfully predict the common heart diseases with an accuracy of 98.7%. This work is also being compared with the recent research done in the field of ECG Classification for detection of heart conditions and proves to be an effective technique for the classification.


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