QRS complex detection based on primitive
The detection of the QRS complex is one of the most important issues in electrocardiogram (ECG) signal analysis. Although research on the detection of the R-peak has demonstrated a high detection rate through a diverse number of studies, research on the detection of the onset and offset boundaries o...
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Published in | Journal of communications and networks Vol. 19; no. 5; pp. 442 - 450 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Seoul
Editorial Department of Journal of Communications and Networks
01.10.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 한국통신학회 |
Subjects | |
Online Access | Get full text |
ISSN | 1229-2370 1976-5541 |
DOI | 10.1109/JCN.2017.000076 |
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Abstract | The detection of the QRS complex is one of the most important issues in electrocardiogram (ECG) signal analysis. Although research on the detection of the R-peak has demonstrated a high detection rate through a diverse number of studies, research on the detection of the onset and offset boundaries of the QRS complex has proven to be difficult, as the locations of these endpoints are often unclear, and the detection results are difficult to interpret. Hence, detection research through improved algorithms continues to be an important component of the ECG signal analysis, especially given the importance of the QRS complexs role in the diagnosis of arrhythmia through measuring the length of the onset and offset of the QRS complex. This paper proposes an improved algorithm that focuses on the primitive of the QRS complex for detecting the onset and offset of the complex based on the morphological characteristics of the QRS complex. The proposed algorithm was tested through experiments based on QT database (QT-DB) data provided by Physionet, and the outcome revealed not only the reliable detection of the QRS complex boundaries but also results that were superior to the location information recorded in the QT-DB. |
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AbstractList | The detection of the QRS complex is one of the most important issues in electrocardiogram (ECG) signal analysis. Although research on the detection of the R-peak has demonstrated a high detection rate through a diverse number of studies, research on the detection of the onset and offset boundaries of the QRS complex has proven to be difficult, as the locations of these endpoints are often unclear, and the detection results are difficult to interpret. Hence, detection research through improved algorithms continues to be an important component of the ECG signal analysis, especially given the importance of the QRS complexs role in the diagnosis of arrhythmia through measuring the length of the onset and offset of the QRS complex. This paper proposes an improved algorithm that focuses on the primitive of the QRS complex for detecting the onset and offset of the complex based on the morphological characteristics of the QRS complex. The proposed algorithm was tested through experiments based on QT database (QT-DB) data provided by Physionet, and the outcome revealed not only the reliable detection of the QRS complex boundaries but also results that were superior to the location information recorded in the QT-DB. The detection of the QRS complex is one of the mostimportant issues in electrocardiogram (ECG) signal analysis. Althoughresearch on the detection of the R-peak has demonstrated ahigh detection rate through a diverse number of studies, researchon the detection of the onset and offset boundaries of the QRS complexhas proven to be difficult, as the locations of these endpointsare often unclear, and the detection results are difficult to interpret. Hence, detection research through improved algorithms continuesto be an important component of the ECG signal analysis, especiallygiven the importance of the QRS complexs role in the diagnosisof arrhythmia through measuring the length of the onset andoffset of the QRS complex. This paper proposes an improved algorithmthat focuses on the primitive of the QRS complex for detectingthe onset and offset of the complex based on the morphologicalcharacteristics of the QRS complex. The proposed algorithm wastested through experiments based on QT database (QT-DB) dataprovided by Physionet, and the outcome revealed not only the reliabledetection of the QRS complex boundaries but also results thatwere superior to the location information recorded in the QT-DB. KCI Citation Count: 7 |
Author | Seungmin Lee Kil Houm Park Daejin Park |
Author_xml | – sequence: 1 givenname: Seungmin surname: Lee fullname: Lee, Seungmin organization: School of Electronics Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daebu, Republic of Korea – sequence: 2 givenname: Daejin surname: Park fullname: Park, Daejin organization: School of Electronics Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daebu, Republic of Korea – sequence: 3 givenname: Kil Houm surname: Park fullname: Park, Kil Houm organization: School of Electronics Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daebu, Republic of Korea |
BackLink | https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002284179$$DAccess content in National Research Foundation of Korea (NRF) |
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Copyright | Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2017 |
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Snippet | The detection of the QRS complex is one of the most important issues in electrocardiogram (ECG) signal analysis. Although research on the detection of the... The detection of the QRS complex is one of the mostimportant issues in electrocardiogram (ECG) signal analysis. Althoughresearch on the detection of the R-peak... |
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SubjectTerms | Algorithms Arrhythmia Boundaries electrocardiogram (ECG) Electrocardiography primitive QRS complex QRS duration QT database (QT-DB) Shape Signal analysis Signal processing algorithms Wavelet transforms 전자/정보통신공학 |
Title | QRS complex detection based on primitive |
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