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The Improvement of ECG Parameter Estimation Obtained by Up-sampling 500 Hz Data

Chinese Journal of Biomedical Engineering(English Edition) 2017年第1期26卷 38-46页

作者： YU Si-si LIU Hong-xing SUN Xing-guo Nanjing University Fuwai Hospital

Nowadays, numerous commercial electrocardiographs(ECG) have500 Hz output sampling rate, i.e., 2 ms corresponding sampling interval. Medical workers who have no background of signal processing may worry about whether such low 500 Hz output sampling rate data could support high-precision estimation of electrocardiogram parameters by being up-sampled. With intention to clarify the problem to the medical workers, this paper takes some simulating experiment to illustrate *** experiment chose the rr interval and R peak amplitude as representative parameters to be estimated. The obtained results were as follows: for rr interval parameter,its estimation error can be lowered to below 0.3 ms by up-sampling; for R peak amplitude, its estimation error can be reduced to below 2.0 μV by up-sampling. It is believed that other ECG parameter estimation can also be improved similarly by up-sampling 500 Hz data.

关键词： electrocardiograph output data rr interval R peak amplitude estimation up-sampling

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Investigation of Support Vector Machine To Assess Cardiac Arrhythmia

Investigation of Support Vector Machine To Assess Cardiac Ar...

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International Conference on Advances in Computer and Electrical Engineering(ICACEE’2012);International Conference on Electronics Engineering & Its Applications(ICEEA’2012);International Conference on Trends in Mechanical and Production Engineering(ICTMPE’2012);International Conference on Agriculture Technology and Food Sciences(ICATFS’2012);International Conference on Chemical,Environment and Civil engineering(ICCECE’2012);International Conference on Literature,Management and Education(ICLME’2012)

作者： R Ganesh Kumar Y S Kumaraswamy Department of Computer Science & Engineering Sathyabama Universit Department of MCA (VTU) Dayananda Sagar College of Engineering

Cardiac Arrhythmia is irregular heartbeat caused by irregular rhythms. The heartbeat is either slowed down or increased causing irregular rhythm. Electrocardiogram （ECG） is used to assess the heart arrhythmia. Different types of arrhythmia which are relevant to diagnosis of heart disease are accurately detected using ECG. Automatic assessment of arrhythmia from ECG is widely researched. Features in the form of rr interval extracted from the ECG and used for classifying the arrhythmia. In this paper, a new approach for cardiac arrhythmia classification is proposed. The proposed method incorporates Support Vector Machine （SVM） approach with Polynomial kernel and Radial Basis Function （RBF）. First, the features are extracted from the time series ECG data using Discrete Cosine Transform （DCT） and the distance between rr wave computed. Experiments were conducted using MIT-BIH arrhythmia database.

关键词： Cardiac Arrhythmia Electrocardiogram (ECG) rr interval Discrete Cosine Transform (DCT) Support Vector Machine (SVM).

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Application of Nonlinear Dynamics to the Study of Congestive Heart Failure

Application of Nonlinear Dynamics to the Study of Congestive...

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第十七届国际生物物理大会;第十二届中国生物物理大会

作者： Swati P. Alok Mishra

The heart is part of a large feedback system whose dynamics are nonlinear,nonstationary,and multiscale. Nonlinear dynamics provides a deeper understanding of the mechanisms of patterns and differences of oscillations ... 详细信息

关键词： ECG Time Series Congestive Heart Failure Normal Sinus Rhythm rr interval PCA

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