Automation of ECG heart beat detection using Morphological filtering and Daubechies wavelet transform

Gayani K.S
<span title="">2014</span> <i title="IOSR Journals"> <a target="_blank" rel="noopener" href="" style="color: black;">IOSR Journal of Engineering</a> </i> &nbsp;
The most specific diagnostic test for heart diseases is the Electrocardiogram (ECG). ECG is a graphical representation of the electrical activity of the heart. Analysis of an ECG signal starts with the detection of QRS complex. Detection of QRS complex is a difficult task as the signal is frequently corrupted by powerline interference, baseline drift, motion artifact and electromyographic interference. Therefore, reliable and accurate detection of QRS complex is gaining momentum nowadays. A
more &raquo; ... l QRS detection algorithm based on Mathematical Morphological (MM) filtering and Daubechies wavelet transform has been developed in this work. MM uses its hybrid opening-closing operations for impulsive noise suppression and baseline wander removal. Daubechies3 WT is used for signal analysis since it has a shape similar to the ECG signal. R peak is extracted as a first in the feature extraction since it is having highest amplitude, followed by Q peak and S peak extraction. Heart beat rate was calculated from the R-R peak interval. From the heart rate and R-R peak interval the diagnosis of the cardiac ailments is done.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.9790/3021-041215358</a> <a target="_blank" rel="external noopener" href="">fatcat:xhfmpmejtbdlxfsti7mn2ef2si</a> </span>
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