High Speed Approach for Detecting QRS Complex Characteristics in Single Lead Electrocardiogram Signal

Conference proceedings article

Authors/Editors

Yahya, Abid

Research Areas

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Publication Details

Author list: Salih SK, Aljunid SA, Aljunid SM, Maskon O, Yahya A

Publisher: IEEE

Place: NEW YORK

Publication year: 2013

Start page: 391

End page: +

ISBN: 978-1-4799-1508-8

eISBN: 978-1-4799-1506-4

Languages: English-Great Britain (EN-GB)

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Abstract

The extracted features from the QRS complex in the electrocardiogram (ECG) signal are considered mainly in the heart rate evaluation and cardiac disease diagnosis. In this paper, high speed approach named "Rising Falling Transition Method (RFTM)" is proposed to detect the characteristics of QRS complex in single lead ECG signal. The proposed approach applies single straight forward algorithm with two stages. The first stage takes the advantage of the transition from rising to falling edge inside each QRS complex as a base to determine the time locations of the vertices in a triangle that composes from the Q-wave end, R-wave peak, and S-wave onset. The second stage determines the time location of Q-wave onset and S-wave end (J-point) using a linear scan along short period which starts from Q-wave end and S-wave onset towards the target end points at Q-wave onset and S-wave end, respectively. The detector approach is able to detect QRS complex of different morphologies (wide/small interval, high/low amplitude, and negative polarities). The detection performance of the proposed approach is evaluated on a single channel of some annotated records from the QT database which collected from seven ECG categories and 48 annotated records from MIT-BIH database. Simulation results show that the average detection rates of sensitivity (Se) and specificity (Sp) are 99.84% and 99.94%, respectively for MIT-BIH Arrhythmia database. The validation results prove the reliability and accuracy of proposed RFTM approach.

Keywords

MIT-BIH Arrhythmia, QRS complex detection, QT databases, RFTM, Rising and Falling edge transition

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