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4 results for “Arrhythmia Classification”

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Research ArticleOpen accessIn the keywordsHybrid BiGRU-BiLSTM Model for Real-Time ECG Arrhythmia Detection Using Wearable SensorsPrem Narayan Singh, Rajendra Prasad MahapatraAccurate and real-time detection of cardiac arrhythmias is essential for timely medical intervention. Advances in wearable devices and deep learning have made it feasible to continuously monitor electrocardiogram (ECG) signals, facilitating early identification of abnormal heart rhythms. For arrhythmia detection, this study presents a hybrid deep learning architecture combining Bidirectional Gated Recurrent Units (Bi-GRU) and Bidirectional Long Short-Term Memory (Bi-LSTM). … …Journal of Computer Science, Vol. 22, Issue 5 · 5 Jun 2026 · 1,331 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSPLINE ACTIVATED NEURAL NETWORK FOR CLASSIFYING CARDIAC ARRHYTHMIAY. S. Kumaraswamy, R. Ganesh KumarElectro Cardiogram’s (ECG) biomedical signals characterizing cardiac anomalies are used for identifying cardiac arrhythmia. Irregular heartbeat-Arrhythmia-affects heart rate causing problems. Many methods, trying to simplify arrhythmia monitoring through automated detection, were developed over the years. ECG classification for arrhythmia is investigated in this paper based on soft computing techniques. RR interval are extracted from time series of the ECG and … …Journal of Computer Science, Vol. 10, Issue 8 · 9 Apr 2014 · 6,968 accessesView PDFCite
Research ArticleOpen accessIn the abstractCardiovascular Diseases Identification Using Wavelet Optimization and Modify Cuckoo Search AlgorithmBanit Negi, Abhilekh Bartwal, Agya Ram Verma et al.The problem the author aims to solve is the extraction of discriminatory features in ECG (Electrocardiogram) signals for classification purposes. The scope of the work is to propose a new method for building wavelets that best reflect the discriminatory capacity of ECG signals. The approach involves optimizing the wavelets specifically for the classification function under consideration. To address the problem, … …Journal of Computer Science, Vol. 19, Issue 8 · 3 Aug 2023 · 5,403 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA New Ventricular Late Potential Classification System Using Ant Colony OptimizationA. Sankara Subramanian, G. Gurusamy, G. SelvakumarProblem statement: Ventricular Late Potentials (VLPs) are low-level high frequency signals that are usually found within the terminal part of the QRS complex from patients after myocardial infarction. Patients with VLPs are at risk of developing ventricular tachycardia, which is the major cause of death if patients suffering from heart disease. Approach: Discrete Wavelet Transform was used to detect VLPs … …Journal of Computer Science, Vol. 8, Issue 2 · 30 Nov 2011 · 6,883 accessesView PDFCite