A hybrid approach of a deep learning technique for real-time ECG beat detection - Patro, Kiran Kumar; Prakash, Allam Jaya; Samantray, Saunak; Pławiak, Joanna; Tadeusiewicz, Ryszard (1947- ); Pławiak, Paweł (Zielona Góra: Uniwersytet Zielonogórski)
This paper presents a new customized hybrid approach for early detection of cardiac abnormalities using an electrocardiogram (ECG). The ECG is a bio-electrical signal that helps monitor the heart`s electrical activity. It can provide health information about the normal and abnormal physiology of the heart. Early diagnosis of cardiac abnormalities is critical for cardiac patients to avoid stroke or sudden cardiac death. The main aim of this paper is to detect crucial beats that can damage the functioning of the heart. Initially, a modified Pan-Tompkins algorithm identifies the characteristic points, followed by heartbeat segmentation.
Keywords: cardiac abnormalities; CAD; convolutional neural network (CNN); deep learning; ECG; supra-ventricular ectopic beats (SVE)