Title: Estimating the perspicacious features of ECG recording based on template classification for detecting atrial fibrillation

Authors: V.R. Vimal; P. Anandan; V. Induja

Addresses: Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Avadi, Chennai, India ' Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Avadi, Chennai, India ' Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Avadi, Chennai, India

Abstract: Atrial fibrillation (AF) is the most extreme basic managed cardiovascular arrhythmia, happening in 1-2% of the overall public and is related with generous demise. The available AF distinguishing techniques are here and there unfit to segregate AF from some different arrhythmias and may misclassify other unpredictable rhythms or uproarious electrocardiograms (ECGs) as AF, bringing about false cautions. The focal point of our exploration work is to build up a calculation to recognise AF with high precision, vigour to commotion, and low false caution rate. Since AF influences both the heart rate inconstancy and ECG morphology, the proposed strategy joins characterisation in view of heart rate fluctuation highlights and layouts of the ECG waveforms. Methodologies considered a structure in which ECG signals are addressed under the kind of CS straight estimations. Then QRS territories are evaluated from compacted space by handling the relationship with pressed ECG, based on QRS design.

Keywords: wireless body sensor networks; atrial fibrillation; compressive sensing.

DOI: 10.1504/IJAIP.2024.141524

International Journal of Advanced Intelligence Paradigms, 2024 Vol.29 No.1, pp.17 - 27

Received: 16 May 2018
Accepted: 07 Dec 2018
Published online: 23 Sep 2024 *

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