A Review of Feature Extraction from ECG Signals and Classification/ Detection for Ventricular Arrhythmias

Author(s): Rajeshwari M. R*, Kavitha K. S

Journal Name: Recent Advances in Computer Science and Communications
Formerly Recent Patents on Computer Science

Volume 14 , Issue 1 , 2021

Become EABM
Become Reviewer
Call for Editor

Graphical Abstract:


High cholesterol, high blood pressure, diabetes, depression, obesity, smoking, poor diet, alcohol consumption, and no exercise are literally the major causes which have taken the life of many people in the world. All the parameters effect is the major slow points for Sudden Cardiac Death (SCD). As per the surveys conducted, there are 1 in 4 deaths caused due to a heart attack in the U.S alone. Ventricular Tachycardia (VT) is the deadly arrhythmias which can lead to SCD. Prediction of SCD using ECG signal derivative is a popular area of research. There are many papers published in this research. The recent development of a new algorithm on this topic helps to further research. In this work, we perform the overview of the ECG signal which is a way of measuring heartbeat rate and other features. Feature extraction of content areas in ECG and Classification algorithms for VF. We would see technique and methods based on ECG signal derivative by research in order to detect and predict SCD.

Keywords: Electrocardiogram (ECG), Sudden Cardiac Death (SCD), Ventricular Tachycardia (VT), Power Line Interference (PLI), Ventricular Fibrillation (VF), Fractional Power Pole (FPP).

Rights & PermissionsPrintExport Cite as

Article Details

Year: 2021
Published on: 08 August, 2019
Page: [227 - 235]
Pages: 9
DOI: 10.2174/2213275912666190809104907
Price: $25

Article Metrics

PDF: 5