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Detacting heart murmur in phonocardiograms

Primož Kocuvan (2015) Detacting heart murmur in phonocardiograms. EngD thesis.

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    Heart auscultation is one of the oldest non-invasive method for detection valvular heart disease. In thesis we have focused on the analysis of phonocardiograms with digital signal processing methods and methods of artificial intelligence for classification. We have divided the signal obtained from electronic stethoscope in to segments where one of the segment corresponds to one cardiac cycle. After that we calculate MFCC features on one of the segments. The features serve as an input to machine learning algorithms in system Orange. Target classification class is the condition of a patient. We have distinguish the phonocardiograms with a heart murmur and without it. The best classification accuracy that we achieved is with naive Bayes classificator of 92.4 %. The expected accuracy of majority class was 75.2 %. The best achieved sensitivity and specificity was 76.9 % and 95.4 % respectively, also with naive Bayes classificator. In our opinion such system could be used by physicians to help diagnose heart valve diseases. In theoretical part of the thesis we have described algorithms that we used and what are the limitations of processing a signal.

    Item Type: Thesis (EngD thesis)
    Keywords: auscultation phenomena, heart valve disease, electronic stethoscope, MFCC, digital signal processing
    Number of Pages: 50
    Language of Content: Slovenian
    Mentor / Comentors:
    Name and SurnameIDFunction
    prof. dr. Neža Mramor Kosta242Mentor
    viš. pred. dr. Robert Rozman277Comentor
    Link to COBISS: http://www.cobiss.si/scripts/cobiss?command=search&base=51012&select=(ID=1536464579)
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Item ID: 3025
    Date Deposited: 21 Aug 2015 09:13
    Last Modified: 15 Sep 2015 11:17
    URI: http://eprints.fri.uni-lj.si/id/eprint/3025

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