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Content Provider | IEEE Xplore Digital Library |
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Author | Ahlstrom, C. Ask, P. Rask, P. Karlsson, J.-E. Nylander, E. Dahlstrom, U. Hult, P. |
Copyright Year | 2007 |
Description | Author affiliation: Linkoping Univ., Linkoping (Ahlstrom, C.; Ask, P.) |
Abstract | Mild sclerotic thickening of the aortic valve affects 25% of the population, and the condition causes aortic valve stenosis (AS) in 2% of adults above 65 years. Echocardiography is today the clinical standard for assessing AS. However, a cost effective and uncomplicated technique that can be used for decision support in the primary health care would be of great value. In this study, recorded phonocardiographic signals were analyzed using the first local minimum of the auto mutual information (AMI) function. The AMI method measures the complexity in the sound signal, which is related to the amount of turbulence in the blood flow and thus to the severity of the stenosis. Two previously developed phonocardiographic methods for assessing AS severity were used for comparison, the murmur energy ratio and the sound spectral averaging technique. Twenty-nine patients with suspected AS were examined with Doppler echocardiography. The aortic jet velocity was used as a reference of AS severity, and it was found to correlate with the AMI method, the murmur energy ratio and the sound spectral averaging technique with the correlation coefficient R = 0.82, R = 0.73 and R = 0.76, respectively. |
Starting Page | 1945 |
Ending Page | 1948 |
File Size | 497975 |
Page Count | 4 |
File Format | |
ISBN | 9781424407873 |
ISSN | 1557170X |
DOI | 10.1109/IEMBS.2007.4352698 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2007-08-22 |
Publisher Place | France |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Mutual information Information analysis Ambient intelligence Valves Echocardiography Costs Medical services Signal analysis Fluid flow measurement Blood flow |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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