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ECG Classification using Dynamic High Pass Filtering and Statistical Framework (HRV)
Vaishali Vijay Ingale, Sanjay Nalbalwar
Pages - 12 - 19     |    Revised - 31-07-2016     |    Published - 31-08-2016
Volume - 10   Issue - 2    |    Publication Date - August 2016  Table of Contents
MMSE, Normal Sinus Rhythm (NSR), Supraventricular Tachycardia (SVT).
This paper presents a technique for detection of R peak from ECG using statistics of the input signal. In this method, high pass filter is derived from the statistics of given signal. Using Minimum Mean Square Error (MMSE) approach, filter parameters are estimated. For estimation of filter parameters, autocorrelation is used. Then further processing is done on the output of high pass filter to detect R peaks and analysis is carried out from the series of R-R intervals to estimate the time domain and frequency domain parameters. From these parameters, ECG classification is done as Normal Sinus Rhythm and Supraventricular tachycardia (SVT).
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Mrs. Vaishali Vijay Ingale
College of Engineering, Pune - India
Dr. Sanjay Nalbalwar
DR Babasaheb Ambedkar Technological University, Lonere, Dist Raigad - India

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