R Peak Detection Algorithm based on Continuous Wavelet Transform and Shannon Energy

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Vol 10, No 2 (2016) Cover
PDF turnitin report R Peak Detection Algorithm based on Continuous Wavelet Transform and Shannon Energy
Published: Mar 6, 2017
DOI: https://doi.org/10.37936/ecti-cit.2016102.64837
Keywords:
R peak detection algorithm Wavelet transform Shannon energy Electrocardiography (ECG)

Main Article Content

Nantarika Thiamchoo
Department of Electrical Engineering, Faculty of Engineering, Prince of Songkla University, Thailand
Pornchai Phukpattaranont
Department of Electrical Engineering, Faculty of Engineering, Prince of Songkla University, Thailand

Abstract

The R peak detection algorithm is a necessary tool for monitoring and diagnosing the cardiovascular disease. This paper presents the R peak detection algorithm based on continuous wavelet transform (CWT) and Shannon energy. We evaluate the proposed algorithm with the 48 record of ECG data from MIT-BIH arrhythmia database. Results show that the proposed algorithm gives very good DER (0.48%-0.50%) compared to those from previous publications (0.168%-0.87%). We demonstrated that the use of the CWT with a single scaling parameter is capable of removing noises. In addition, we found that Shannon energy cannot improve the DER value but it can highlight the R peak from the low QRS complex in ECG beat leading to the improvement in the robustness of the R peak detection algorithm.

Article Details

How to Cite
[1]
N. Thiamchoo and P. Phukpattaranont, “R Peak Detection Algorithm based on Continuous Wavelet Transform and Shannon Energy”, ECTI-CIT Transactions, vol. 10, no. 2, pp. 167–175, Mar. 2017.
Issue
Vol. 10 No. 2 (2016): ECTI Transaction on CIT (Nov 2016)
Section
Artificial Intelligence and Machine Learning (AI)
Author Biographies

Nantarika Thiamchoo, Department of Electrical Engineering, Faculty of Engineering, Prince of Songkla University, Thailand

Department of Electrical Engineering,
Faculty of Engineering, Prince of Songkla University

Pornchai Phukpattaranont, Department of Electrical Engineering, Faculty of Engineering, Prince of Songkla University, Thailand

Department of Electrical Engineering,
Faculty of Engineering, Prince of Songkla University

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