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									<identifier>oai:www.peertechzpublications.org:10.17352/abse.000011</identifier>
									<datestamp>2019-01-25</datestamp>
									<setSpec>PTZ.ABSE:VOL5</setSpec>
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									<oai_dc:dc xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
										<dc:title>
										The QRS complex detection using morphological filtering
										</dc:title><dc:creator>Taouli SA</dc:creator><dc:creator>Bereksi-Reguig F</dc:creator><dc:description>&lt;p&gt;This article presents a method of QRS complex detection and more precisely the R wave in an electrocardiogram (ECG) based on the mathematics morphology which calls upon the four operators’ morphology, erosion, dilation, opening and closing. These operators are combined with a window relocated which is called the structuring element. Morphological filtering uses the structuring element to extract the shape information from ECG signal. The effectiveness of the proposed algorithm is tested by using recordings obtained from the MIT-BIH arrhythmia database. Experiment results show that the proposed algorithm outperforms the other algorithms.&lt;/p&gt;</dc:description>
										<dc:publisher>Archive of Biomedical Science and Engineering - Peertechz Publications</dc:publisher>
										<dc:date>2019-01-25</dc:date>
										<dc:type>Research Article</dc:type>
										<dc:identifier>https://doi.org/10.17352/abse.000011</dc:identifier>
										<dc:language>en</dc:language>
										<dc:rights>Copyright © Taouli SA et al.</dc:rights>
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