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SPLINE ACTIVATED NEURAL NETWORK FOR CLASSIFYING CARDIAC ARRHYTHMIA

Kumar
2014 Journal of Computer Science  
RR interval are extracted from time series of the ECG and used as feature for arrhythmia classification.  ...  Electro Cardiogram's (ECG) biomedical signals characterizing cardiac anomalies are used for identifying cardiac arrhythmia. Irregular heartbeat-Arrhythmia-affects heart rate causing problems.  ...  Cosine Transform was used and RR interval extracted and used as a feature in this study.  ... 
doi:10.3844/jcssp.2014.1582.1590 fatcat:g4j5mgt2kne57lc5ipgknwfu6q

CARDIAC AND STRESS ASSESSMENT USING SVM CLASSIFIER

K.R. INDIRA
2022 INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT  
Initial filtering of the noise is done using wavelet transform.  ...  The obtained ECG signals are noisy, due to the loss of signal values, problems in the electrodes and natural addition of noises in the image.  ...  Rajendra Acharya, Choo Min Lim , Jasjit S.Suri, " Characterization of ECG beats from cardiac rrhythmia using discrete cosine transform in PCA framework " Elsevier-Knowledge-Based System 45 (2013). [3].  ... 
doi:10.55041/ijsrem11630 fatcat:x3mtqq2anfgvfpuw76oleyepj4

A Review Study for Electrocardiogram Signal Classification

Lana Abdulrazaq Abdulla, Muzhir Shaban Al-Ani
2020 UHD Journal of Science and Technology  
The analysis of the ECG signal has been interested in more than a decade to build a model to make automatic ECG classification.  ...  The main goal of this work is to study and review an overview of utilizing the classification methods that have been recently used such as Artificial Neural Network, Convolution Neural Network (CNN), discrete  ...  Feature extraction techniques used by researchers are discrete wavelet transform (DWT), continuous wavelet transform, discrete cosine transform (DCT), discrete Fourier transform, principal component analysis  ... 
doi:10.21928/uhdjst.v4n1y2020.pp103-117 fatcat:7gpxdwtbonczxm6ojdofhzarma

Classification of ECG Heartbeat Arrhythmia: A Review

Jagadeeswara Rao Annam, Srinivas Kalyanapu, Sureshbabu Ch., Jayaprada Somala, S. Bapi Raju
2020 Procedia Computer Science  
Abstract Manual identification of ECG heart-beat classes by cardiologists is time consuming and cumbersome.  ...  Manual identification of ECG heart-beat classes by cardiologists is time consuming and cumbersome. These professionals rely on computer based methods for determination of these heart-disease types.  ...  Introduction The cardiac rhythm abnormalities are different in shape from the normal rhythm of the heart-beat cycle and are known as heart-beat arrhythmia.  ... 
doi:10.1016/j.procs.2020.04.074 fatcat:lwihpqvmujgzrclt4uph6cdsra

Computational techniques for ECG analysis and interpretation in light of their contribution to medical advances

Aurore Lyon, Ana Mincholé, Juan Pablo Martínez, Pablo Laguna, Blanca Rodriguez
2018 Journal of the Royal Society Interface  
Widely developed for clinical screening, electrocardiogram (ECG) recordings capture the cardiac electrical activity from the body surface.  ...  This review describes the computational methods in use for ECG analysis, with a focus on machine learning and 3D computer simulations, as well as their accuracy, clinical implications and contributions  ...  Interface 15: 20170821 features from the RR interval and characterized the morphology of the ECG by discrete wavelet transform.  ... 
doi:10.1098/rsif.2017.0821 pmid:29321268 pmcid:PMC5805987 fatcat:eztpsijglzaobl4hphm2ul23yi

Arrhythmia detection using deep convolutional neural network with long duration ECG signals

Özal Yıldırım, Paweł Pławiak, Ru-San Tan, U Rajendra Acharya
2018 Figshare  
Described research are based on 1000 ECG signal fragments from the MIT - BIH Arrhythmia database for one lead (MLII) from 45 persons.  ...  This article presents a new deep learning approach for cardiac arrhythmia (17 classes) detection based on long-duration electrocardiography (ECG) signal analysis.  ...  ; (ii) testing the efficiency of developed 1D-CNN using other physiological signals, (iii) classifying fragments of the ECG signal that containing more than one class, and (iv) testing the performance  ... 
doi:10.6084/m9.figshare.7272371.v2 fatcat:tpkix7hs7zeoxlqkpabgj63qmq

Electrocardiogram Pattern Recognition and Analysis Based on Artificial Neural Networks and Support Vector Machines: A Review

Mario Sansone, Roberta Fusco, Alessandro Pepino, Carlo Sansone
2013 Journal of Healthcare Engineering  
This paper reviews methods of ECG processing from a pattern recognition perspective. In particular, we focus on features commonly used for heartbeat classification.  ...  Computer systems for Electrocardiogram (ECG) analysis support the clinician in tedious tasks (e.g., Holter ECG monitored in Intensive Care Units) or in prompt detection of dangerous events (e.g., ventricular  ...  This work was conducted partially under the financial support of the FARO (Finanziamento per l'Avvio di Ricerche Originali) Programme in the framework of the project "Un sistema elettronico di elaborazione  ... 
doi:10.1260/2040-2295.4.4.465 pmid:24287428 fatcat:z373jqpajjai7lbovclm46nmfe

Wavelets for Electrocardiogram: Overview and Taxonomy

Wei Li
2019 IEEE Access  
Finally, this paper has provided an outlook for the developing prospect of "wavelets for ECG" in the future.  ...  In order to manifest the value of these methods, this paper contributes an overview and taxonomy on them.  ...  [101] have acquired the feature subspaces of the ECG heartbeats by applying the PCA to the WCF and the discrete cosine transform coefficient feature, respectively, and also by applying the ICA to each  ... 
doi:10.1109/access.2018.2877793 fatcat:2ijgapgyyrewhphdrxvid23f4e

Automated Detection of ECG Noise Signal and Classification System by Using Modified CEEMD

A.Rajani and B.Prasanna Lakshmi
2020 International journal of modern trends in science and technology  
the proposed framework, ECG signals are first decomposed using the modified CEEMD algorithm for discriminating the ECG components from the noises and artifacts.  ...  Then, the short-term temporal features such as maximum absolute amplitude, number of zerocrossings, and local maximum peak amplitude of the autocorrelation function are computed from the extracted high-frequency  ...  (SVD), discrete cosine transform (DCT), discrete wavelet transform(DWT),switching Kalman filters, empirical mode decomposition (EMD),nonlinear Bayesian filter (NBF), mathematical morphological (MM) operators  ... 
doi:10.46501/ijmtstciet25 fatcat:6hy34k5xq5ahlls32w5rpzhckq

Techniques for Ventricular Repolarization Instability Assessment From the ECG

Pablo Laguna, Juan Pablo Martinez Cortes, Esther Pueyo
2016 Proceedings of the IEEE  
A review of the state-of-the-art is provided, spanning from the electrophysiological basis of ventricular repolarization to its characterization on the surface ECG through a set of temporal and spatial  ...  Index Terms-Electrophysiological basis of the ECG, ECG waves, ECG intervals, repolarization instabilities, spatial and temporal ventricular repolarization dispersion, cardiac arrhythmias, biophysical modeling  ...  Fig. 12(b) shows the PCA transformation of the input signal in (a).  ... 
doi:10.1109/jproc.2015.2500501 fatcat:umayx6hwfnafvjlsevdc3fbfnq

Individual Identification Using Linear Projection of Heartbeat Features

Yogendra Narain Singh
2014 Applied Computational Intelligence and Soft Computing  
The ECG characterization is performed using an automated approach consisting of analytical and appearance methods.  ...  The proposed system utilizing ECG biometric method achieves the best identification rates of 85.7% for the subjects of MIT-BIH arrhythmia database and 92.49% for the healthy subjects of our IIT (BHU) database  ...  Conflict of Interests The author declares that there is no conflict of interests regarding the publication of this paper.  ... 
doi:10.1155/2014/602813 fatcat:7qrhqfvb5vcnbdj2kp5fezwdue

A Hybrid Heartbeats Classification Approach Based on Marine Predators Algorithm and Convolution Neural Networks

Essam H. Houssein, Diaa Salama AbdElminaam, Ibrahim E. Ibrahim, M. Hassaballah, Yaser M. Wazery
2021 IEEE Access  
Early ECG beat classification plays a significant role in diagnosing life-threatening cardiac arrhythmias.  ...  The electrocardiogram (ECG) is a non-invasive tool used to diagnose various heart conditions. Arrhythmia is one of the primary causes of cardiac arrest.  ...  INTRODUCTION Cardiac arrhythmia, a disease characterized by irregular heart activity [1] , [2] , [3] and a cardiac condition associated with the rhythm of the heartbeat or heart rate, is the main source  ... 
doi:10.1109/access.2021.3088783 fatcat:jpuxz4jtjvhndc4okqk5iraqfa

Origins of ECG and Evolution of Automated DSP Techniques: A Review

Neha Arora, Biswajit Mishra
2021 IEEE Access  
This work is supported by Department of Science and Technology (Grant No. :DST SERB Grant CRG/2019/004747), Government of India.  ...  ACKNOWLEDGMENT The authors would like to thank Dhirubhai Ambani Institute of Information and Communication Technology for the research support.  ...  The algorithm was able to expand its dictionary upon the arrival of any unseen pattern and also uses discrete cosine transformation to make it immune to incoming noise.  ... 
doi:10.1109/access.2021.3119630 fatcat:kbxghskiu5f5hc3vrmi6yrysba

Computerized Interpretation of Cardiovascular Physiological Signals [chapter]

Bing Nan, Mang I, Ming Chui
2010 Decision Support Systems Advances in  
Selected arrhythmia ECG beats from MAD The orders of Hermite modeling, relative wavelet energies, wavelet scale maxima and matching pursuits were set as 7, 15, 16 and 7.  ...  In essence, each ECG beat after normalization could be characterized as a 360-dimensional multivariate vector.  ...  The expertise of the chapter writers spans an equally extensive spectrum of researchers from around the globe including universities in Canada, Mexico, Brazil and the United States, to institutes and universities  ... 
doi:10.5772/39395 fatcat:fkcvwhlg3najndnzk7si6uolsm

A Novel Wearable Electrocardiogram Classification System Using Convolutional Neural Networks and Active Learning

Yufa Xia, Yaoqin Xie
2019 IEEE Access  
To further verify the generalization capability of the system, the ECG data that acquired from our wearable device are also used to conduct in the experiments.  ...  Arrhythmias reflect electrical abnormalities of the heart, and they can lead to severe harm to the heart. An electrocardiogram (ECG) is a useful tool to manifest arrhythmias.  ...  ) [7] , discrete cosine transform (DCT) in PCA framework [21] , higher order spectra features with PCA and SVM [22] , [23] .  ... 
doi:10.1109/access.2019.2890865 fatcat:hzf6xwnkhnhc7pkbkrw7coibme
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