In this pa per, a decision s up port system is
presented for interpretation of the Doppler signals of
the heart valve diseases based on the pattern
recognition. This paper especially deals with the
feature extraction from measured Doppler signal
waveforms at the heart valve using the Doppler
Ultrasound. Wavelet transforms and power spectrum
estimate by Yule-Walker AR method are used to
feature extract from the Doppler signals on the time
frequency domain. Wavelet entropy method is
applied to these features. The back-propagation
neural network is used to classify the extracted
features. The performance of the developed system
has been evaluated in 215 samples. The test results
showed that this system was effective to detect
Doppler heart sounds. The correct classification rate
was about 84°/o for normal subjects and 95.9°/o for
abnormal subjects.
Primary Language | TR |
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Subjects | Engineering |
Journal Section | Research Articles |
Authors | |
Publication Date | August 1, 2002 |
Submission Date | May 9, 2002 |
Published in Issue | Year 2002 Volume: 6 Issue: 2 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.