Three-Bits Linear Interpolation Error Signal Based ECG Beat Classification

Anwar Mohammad Alshrouf; Sofiene Mansouri; Yousef Alharbi

doi:10.1002/tee.23658

Three-Bits Linear Interpolation Error Signal Based ECG Beat Classification

Anwar Mohammad Alshrouf, Sofiene Mansouri, Yousef Alharbi

Biomedical Technology

Research output: Contribution to journal › Article › peer-review

Abstract

About three million people die from sudden cardiac arrest (SCA) or infarction each year. It is the biggest killer on the planet and it can happen to anyone, anywhere, and anytime. Early and effective diagnosis from ECG signals can help save a large part of these SCAs. Premature ventricular contraction (PVC) detection and classification was performed with different methods. A new method of automatic classification of PVC based on a three-bit linear interpolation error signal (LIES) is proposed in this paper. We start by a QRS detection, a nonlinear transformation and then a sliding window. This method was tested on normal and abnormal beats obtained from MIT-BIH and AHA databases. The proposed algorithm with a sensitivity 94.8% and a specificity was 98.6%. is accurate. This algorithm is also automatic, robust, and fast.

Original language	English
Pages (from-to)	1478-1484
Number of pages	7
Journal	IEEJ Transactions on Electrical and Electronic Engineering
Volume	17
Issue number	10
DOIs	https://doi.org/10.1002/tee.23658
State	Published - Oct 2022

Keywords

autocorrelation
PVC classification
QRS detection
sliding window
three-bit linear interpolation

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10.1002/tee.23658

Cite this

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title = "Three-Bits Linear Interpolation Error Signal Based ECG Beat Classification",

abstract = "About three million people die from sudden cardiac arrest (SCA) or infarction each year. It is the biggest killer on the planet and it can happen to anyone, anywhere, and anytime. Early and effective diagnosis from ECG signals can help save a large part of these SCAs. Premature ventricular contraction (PVC) detection and classification was performed with different methods. A new method of automatic classification of PVC based on a three-bit linear interpolation error signal (LIES) is proposed in this paper. We start by a QRS detection, a nonlinear transformation and then a sliding window. This method was tested on normal and abnormal beats obtained from MIT-BIH and AHA databases. The proposed algorithm with a sensitivity 94.8\% and a specificity was 98.6\%. is accurate. This algorithm is also automatic, robust, and fast.",

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Three-Bits Linear Interpolation Error Signal Based ECG Beat Classification

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Keywords

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