Please use this identifier to cite or link to this item: http://localhost:8081/xmlui/handle/123456789/2961
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dc.contributor.authorBegum, Ritu Nazneen-
dc.date.accessioned2014-09-29T13:26:55Z-
dc.date.available2014-09-29T13:26:55Z-
dc.date.issued2012-
dc.identifierM.Techen_US
dc.identifier.urihttp://hdl.handle.net/123456789/2961-
dc.guideSharma, Ambalika-
dc.guideSumathi, P.-
dc.description.abstractThe presented research work analyses and classifies various cardiac abnormalities using three different methods. The arrangement of data is same in all the three methods only the way it has been used or the way, features extracted are different. The first techniqueuses the whole waveform of each beat for training the network. Thus, here literally no features are extracted, only classification is done. The second technique, extracts P and QRS complex using an ANN and then Classifies the beats to their respective classes thus the ANN acts as a detector as well as a classifier. The third technique has been used for verifying the results of the first two methods. It extracts features from the data using wavelet transforms and then classifies the beats with the help of the features extracted with the same ANN used in the other two methods. The results found were quite satisfactory, although the first method performed best; all the three methods had overall accuracies above 97%.en_US
dc.language.isoenen_US
dc.subjectELECTRICAL ENGINEERINGen_US
dc.subjectANNen_US
dc.subjectECG WAVE ANALYSISen_US
dc.subjectWAVEFORMen_US
dc.titleANN BASED ECG WAVE ANALYSIS AND CLASSIFICATIONen_US
dc.typeM.Tech Dessertationen_US
dc.accession.numberG22054en_US
Appears in Collections:MASTERS' THESES (Electrical Engg)

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