Nimmala Mangathayaru1,*, Padmaja Rani2, Vinjamuri Janaki3, Kalyanapu Srinivas4, B. Mathura Bai1, G. Sai Mohan1, B. Lalith Bharadwaj1
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2425-2443, 2021, DOI:10.32604/cmc.2021.016534
Abstract Arrhythmia is ubiquitous worldwide and cardiologists tend to provide solutions from the recent advancements in medicine. Detecting arrhythmia from ECG signals is considered a standard approach and hence, automating this process would aid the diagnosis by providing fast, cost-efficient, and accurate solutions at scale. This is executed by extracting the definite properties from the individual patterns collected from Electrocardiography (ECG) signals causing arrhythmia. In this era of applied intelligence, automated detection and diagnostic solutions are widely used for their spontaneous and robust solutions. In this research, our contributions are two-fold. Firstly, the Dual-Tree Complex Wavelet Transform (DT-CWT) method is implied… More >
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