Please use this identifier to cite or link to this item: https://repository.sustech.edu/handle/123456789/9529
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dc.contributor.authorAli, Wahiba Hamdan
dc.contributor.authorSupervisor - Eltahir Mohamed Hussein
dc.date.accessioned2015-01-05T12:21:14Z
dc.date.available2015-01-05T12:21:14Z
dc.date.issued2014-05-11
dc.identifier.citationAli,Wahiba Hamdan,Heart Murmur Detection using Artificial Neural Network/Wahiba Hamdan Ali;Eltahir Mohamed Hussein.-khartoum:Sudan University of Science and Technology,College of Engineering,2014.-62p:ill;28cm.-M.Sc.en_US
dc.identifier.urihttp://repository.sustech.edu/handle/123456789/9529
dc.descriptionThesisen_US
dc.description.abstractAccurate detection and classification of pathological heart murmurs by auscultation has been a challenge for physicians for a long time. In this research, we have used a AI techniques rely on converting the heart sounds to electrical signals and processing those signals by matlab tool box for murmur detection and classification. We have designed a heart murmur detection system based upon this approach and have tested this system using simulated heart sounds of various murmur types. Our test results show that the used of multilayer perceptron ANNs improve heart murmur detection accuracy up to (97%).en_US
dc.description.sponsorshipSudan University of Science and Technologyen_US
dc.language.isoenen_US
dc.publisherSudan University of Science and Technologyen_US
dc.subjectSounds of the Hearten_US
dc.subjectArtificial neural networksen_US
dc.subjectpathological hearten_US
dc.subjectconverting the heart soundsen_US
dc.titleHeart Murmur Detection using Artificial Neural Networken_US
dc.title.alternativeكشف اصوات القلب بأستخدام الشبكات العصبیة الاصطناعیةen_US
dc.typeThesisen_US
Appears in Collections:Masters Dissertations : Engineering

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