An Exploration of ECG Signal Feature Selection and Classification using Machine Learning Techniques

Author:

Abstract

This effort examines and likens a collection of active methods to dimensionally reduction and select salient features since the electrocardiogram database. ECG signal classification and feature selection plays a vital part in identifies of cardiac illness. An accurate ECG classification could be a difficult drawback. This effort also examines of ECG classification into arrhythmia kinds. This effort discusses the problems concerned in Classification ECG signal and exploration of ECG databases (MIT-BIH), pre-processing, dimensionally reduction, Feature selection techniques, classification and optimization techniques. Machine learning techniques give offers developed classification accurateness with imprecation of dimensionality.

Publisher

Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP

Subject

Electrical and Electronic Engineering,Mechanics of Materials,Civil and Structural Engineering,General Computer Science

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