Philip Langley
Abnormal heart sounds detected from short duration unsegmented phonocardiograms by wavelet entropy
Langley, Philip; Murray, Alan
Authors
Alan Murray
Abstract
© 2016 CCAL. Segmentation of the characteristic heart sounds is thought to be an essential requirement for the automatic classification of phonocardiograms. The aim of this work was to test the feasibility of classification using short duration, unsegmented recordings. Recordings from the 2016 PhysioNet/Computing in Cardiology Challenge were analysed. Wavelet entropy of unsegmented 5 s duration recordings was calculated and the optimum wavelet scale and wavelet entropy threshold determined from the training set. The algorithm was validated on the test set. At a wavelet scale of 1.7 wavelet entropy was significantly reduced in abnormal recordings (median (IQR), 6.3 (1.8) vs 8.0 (1.8) p
Citation
Langley, P., & Murray, A. Abnormal heart sounds detected from short duration unsegmented phonocardiograms by wavelet entropy
Presentation Conference Type | Conference Paper (published) |
---|---|
Acceptance Date | Apr 1, 2016 |
Publication Date | Mar 1, 2016 |
Deposit Date | Apr 21, 2022 |
Publicly Available Date | Aug 1, 2022 |
Journal | Computing in Cardiology |
Print ISSN | 2325-8861 |
Peer Reviewed | Not Peer Reviewed |
Volume | 43 |
Pages | 545-548 |
ISBN | 9781509008964 |
DOI | https://doi.org/10.22489/cinc.2016.156-268 |
Public URL | https://hull-repository.worktribe.com/output/3590849 |
Files
Published article
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PDF
Publisher Licence URL
http://creativecommons.org/licenses/by/2.5/
Copyright Statement
©2016 The authors.
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