{"title":"EMD method for automatic ECG fiducial points detection","authors":"Dhouha Rezgui, Z. Lachiri","doi":"10.1109/IPAS.2016.7880064","DOIUrl":null,"url":null,"abstract":"The automatic detection of electrocardiogram waves presents an important step for cardiac disease diagnosis. In this work, we developed an algorithm for locating the waveform boundaries by using the empirical mode decomposition which has interesting properties concerning the pseudo periodic signals. The introduced method allows identifying an appropriate and optimum set of intrinsic mode functions (IMFs) to reconstruct a wave from ECG signal. Firstly, the R wave is detected from each heartbeat using the first tree IMFs of empirical mode decomposition (EMD) analysis. Then, the Q wave and T wave of each QRS complex are delineated. Next, the determination of P wave and T wave was performed employing a set of higher order IMFs. We tested the reliability of our algorithm on the QT Database, the manually annotated database. A comparison is also made with other delineation algorithms for the assessment of system performance. The obtained results showed a better performance and accurate detection of ECG fiducial points.","PeriodicalId":283737,"journal":{"name":"2016 International Image Processing, Applications and Systems (IPAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Image Processing, Applications and Systems (IPAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPAS.2016.7880064","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The automatic detection of electrocardiogram waves presents an important step for cardiac disease diagnosis. In this work, we developed an algorithm for locating the waveform boundaries by using the empirical mode decomposition which has interesting properties concerning the pseudo periodic signals. The introduced method allows identifying an appropriate and optimum set of intrinsic mode functions (IMFs) to reconstruct a wave from ECG signal. Firstly, the R wave is detected from each heartbeat using the first tree IMFs of empirical mode decomposition (EMD) analysis. Then, the Q wave and T wave of each QRS complex are delineated. Next, the determination of P wave and T wave was performed employing a set of higher order IMFs. We tested the reliability of our algorithm on the QT Database, the manually annotated database. A comparison is also made with other delineation algorithms for the assessment of system performance. The obtained results showed a better performance and accurate detection of ECG fiducial points.
心电图波形的自动检测是心脏疾病诊断的重要一步。在这项工作中,我们开发了一种利用经验模态分解定位波形边界的算法,该算法对伪周期信号具有有趣的特性。所引入的方法可以确定一组适当的最佳固有模式函数(IMF),从而从心电图信号中重建波形。首先,利用经验模式分解(EMD)分析的第一树 IMF 从每次心跳中检测出 R 波。然后,划定每个 QRS 波群的 Q 波和 T 波。接着,使用一组高阶 IMF 确定 P 波和 T 波。我们在人工标注的 QT 数据库上测试了我们算法的可靠性。为了评估系统性能,我们还与其他划界算法进行了比较。结果表明,该算法性能更佳,能准确检测到心电图靶点。