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2021 | OriginalPaper | Chapter

State-of-the-Art Method to Detect R-Peak on Electrocardiogram Signal: A Review

Authors : Anita Miftahul Maghfiroh, Syevana Dita Musvika, Levana Forra Wakidi, Lamidi Lamidi, Sumber Sumber, Muhmmad Ridha Mak’ruf, Andjar Pudji, Dyah Titisari

Published in: Proceedings of the 1st International Conference on Electronics, Biomedical Engineering, and Health Informatics

Publisher: Springer Singapore

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Abstract

The detection of the R peak on the ECG signal is very important to use to see the amount of variability in the heart rate. So that a person’s vital signs can be known if there are heart defects including arrhythmias. Besides, several recent studies suggest that the detection of the R peak in the ECG signal can also be used to detect respiratory rate signals. Therefore, an appropriate algorithm is needed to detect the R peak in the ECG signal so that there is no mistake in diagnosing a person’s physiological state. Several researchers have developed methods for detecting the R peak in the ECG signal with advantages and disadvantages. Therefore, this paper aims to provide a specific description of the R peak detection method to facilitate other authors in developing R peak detection methods in ECG signals. References in this paper are gathered from several journals and procurements regarding the definition of peak R. The results showed that some researchers used an adaptive threshold system with an accuracy rate of 99.41%, while some other researchers used the 99.5% decomposition method, some researchers used the convoluted neural network (CNN) method with an accuracy level of 99.7%. The benefit for the next researcher is to develop a real-time R peak detection tool to use to see the amount of variability in the heart rate by using one of these methods.

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Literature
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go back to reference Mabrouki R, Khaddoumi B, Sayadi M (2014) R peak detection in electrocardiogram signal based on a combination between empirical mode decomposition and Hilbert transform. In: 1st International conference on advanced technologies for signal and image processing ATSIP 2014, pp 183–187. https://doi.org/10.1109/atsip.2014.6834603 Mabrouki R, Khaddoumi B, Sayadi M (2014) R peak detection in electrocardiogram signal based on a combination between empirical mode decomposition and Hilbert transform. In: 1st International conference on advanced technologies for signal and image processing ATSIP 2014, pp 183–187. https://​doi.​org/​10.​1109/​atsip.​2014.​6834603
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go back to reference Thiamchoo N, Phukpattaranont P (2016) Application of wavelet transform and Shannon energy on R peak detection algorithm. In: 13th International conference onelectrical engineering/electronics, computer, telecommunications and information technology ECTI-CON 2016. https://doi.org/10.1109/ecticon.2016.7561280 Thiamchoo N, Phukpattaranont P (2016) Application of wavelet transform and Shannon energy on R peak detection algorithm. In: 13th International conference onelectrical engineering/electronics, computer, telecommunications and information technology ECTI-CON 2016. https://​doi.​org/​10.​1109/​ecticon.​2016.​7561280
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go back to reference Bölümü BT Evri ¸ simsel Sinir A gları ile Elektrokardiogram Sinyalinde R-tepelerinin Tespiti R-peaks Detection with Convolutional Neural Network in Electrocardiogram Signal, no 2, pp 1–4 Bölümü BT Evri ¸ simsel Sinir A gları ile Elektrokardiogram Sinyalinde R-tepelerinin Tespiti R-peaks Detection with Convolutional Neural Network in Electrocardiogram Signal, no 2, pp 1–4
Metadata
Title
State-of-the-Art Method to Detect R-Peak on Electrocardiogram Signal: A Review
Authors
Anita Miftahul Maghfiroh
Syevana Dita Musvika
Levana Forra Wakidi
Lamidi Lamidi
Sumber Sumber
Muhmmad Ridha Mak’ruf
Andjar Pudji
Dyah Titisari
Copyright Year
2021
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-33-6926-9_27