NDLI: Recognition of heart sounds and murmurs for cardiac diagnosis

Content Provider	IEEE Xplore Digital Library
Author	Mohamed, A.S.A. Raafat, H.M.
Copyright Year	1988
Description	Author affiliation: Dept. of Comput. Sci., Regina Univ., Sask., Canada (Mohamed, A.S.A.; Raafat, H.M.)
Abstract	A pattern recognition system, able to classify the heart sounds and murmurs perfectly for cardiac diagnosis is presented. A mathematical model to describe the heart sounds and murmurs (HSAM) by a finite number of parameters was developed. The autoregressive model (AR) is selected to represent the HSAM at principal locations of cardiac auscultation and for different heart diseases. Feature extraction of the pre-emphasized signal, based on fourth-order linear prediction of the cardiac cycle frames, is performed. Pattern classification, based on an optimal dynamic time warping algorithm that minimizes the Euclidean distance between the features of the measured pattern and reference patterns, is verified. A decision, based on a minimum-distance criterion is then made. Furthermore, a bank consisting of 20 reference types of cardiac diseases has been generated.
Starting Page	1009
Ending Page	1011
File Size	235641
Page Count	3
File Format	PDF
ISBN	0818608781
DOI	10.1109/ICPR.1988.28425
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1988-05-14
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Signal processing Predictive models Discrete event simulation Linear predictive coding Timing Electrical capacitance tomography Erbium Heart rate variability Cardiac disease Cardiovascular diseases
Content Type	Text
Resource Type	Article

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