Journal ArticleDOI
An improved cardiac arrhythmia classification using an RR interval-based approach
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TLDR
An improved RR interval-based cardiac arrhythmia classification approach that is significantly better and more accurate than the other classifiers used in this method.About:
This article is published in Biocybernetics and Biomedical Engineering.The article was published on 2021-04-01. It has received 35 citations till now. The article focuses on the topics: Cardiac arrhythmia & QRS complex.read more
Citations
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Journal ArticleDOI
Automatic cardiac arrhythmia classification based on hybrid 1-D CNN and Bi-LSTM model
Jagdeep Rahul,Lakhan Dev Sharma +1 more
TL;DR: In this article , a novel combination of Stationary Wavelet transforms (SWT) and a two-stage median filter with Savitzky-Golay (SG) filter were used for preprocessing of the ECG signal followed by segmentation and z-score normalisation process.
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A Hybrid Deep Learning Approach for ECG-Based Arrhythmia Classification
TL;DR: A robust approach has been introduced where 2D scalogram images of ECG signals are trained over the CNN-LSTM model and the results obtained are better as compared to the other existing techniques and will greatly reduce the amount of intervention required by doctors.
Journal ArticleDOI
Artificial intelligence-based approach for atrial fibrillation detection using normalised and short-duration time-frequency ECG
Jagdeep Rahul,Lakhan Dev Sharma +1 more
TL;DR: In this article, a novel approach for the detection of atrial fibrillation using both 1-D electrocardiogram signal and its time-frequency representation as an image was presented.
Journal ArticleDOI
Artificial intelligence-based approach for atrial fibrillation detection using normalised and short-duration time-frequency ECG
TL;DR: In this article , an artificial intelligence-based approach for atrial fibrillation detection using normalised and short-duration time-frequency ECG was proposed, which achieved an accuracy of 98.85% in the 2-dimensional image representation.
Journal ArticleDOI
Detection of cardiac arrhythmias from ECG signals using FBSE and Jaya optimized ensemble random subspace K-nearest neighbor algorithm
TL;DR: In this paper , the Fourier-Bessel series expansion (FBSE) is used to transform the sequences of each heartbeat into more meaningful ones that can characterize the structural integrity of arrhythmia.
References
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Journal ArticleDOI
PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals.
Ary L. Goldberger,Luís A. Nunes Amaral,Leon Glass,Jeffrey M. Hausdorff,Plamen Ch. Ivanov,Roger G. Mark,Joseph E. Mietus,George B. Moody,Chung-Kang Peng,H. Eugene Stanley +9 more
TL;DR: The newly inaugurated Research Resource for Complex Physiologic Signals (RRSPS) as mentioned in this paper was created under the auspices of the National Center for Research Resources (NCR Resources).
Journal ArticleDOI
Random Forests for Classification in Ecology
D. Richard Cutler,Thomas C. Edwards,Thomas C. Edwards,Karen H. Beard,Adele Cutler,Kyle Hess,Jacob Gibson,Joshua J. Lawler +7 more
TL;DR: High classification accuracy in all applications as measured by cross-validation and, in the case of the lichen data, by independent test data, when comparing RF to other common classification methods are observed.
Journal ArticleDOI
The impact of the MIT-BIH Arrhythmia Database
George B. Moody,Roger G. Mark +1 more
TL;DR: The history of the database, its contents, what is learned about database design and construction, and some of the later projects that have been stimulated by both the successes and the limitations of the MIT-BIH Arrhythmia Database are reviewed.
Journal ArticleDOI
Random Forests for land cover classification
TL;DR: The Random Forest classifier uses bagging, or bootstrap aggregating, to form an ensemble of classification and regression tree (CART)-like classifiers, which is computationally much lighter than methods based on boosting and somewhat lighter than simple bagging.
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Cardiac and arrhythmic complications in patients with COVID-19.
TL;DR: This review focus on COVID‐19 cardiac and arrhythmic manifestations and makes an appraisal of other virus epidemics as SARS‐CoV, Middle East respiratory syndrome coronavirus, and H1N1 influenza.