DocumentCode :
2940118
Title :
Computer-aided analysis and classification of heart sounds based on neural networks and time analysis
Author :
Wu, Chung-Hsien ; Lo, Ching-Wen ; Wang, Jhing-Fa
Author_Institution :
Inst. of Inf. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
Volume :
5
fYear :
1995
fDate :
9-12 May 1995
Firstpage :
3455
Abstract :
This paper describes a computer-aided heart sound analysis and classification system (CHACS) based on neural networks and time analysis. In this system, two subsystems in both time and frequency domains are proposed. In the first subsystem, a multilayer perceptron neural network is adopted to classify heart sound patterns. In the second subsystem, a set of heuristic rules is used to characterize heart sounds. The individual classification results of these two subsystems are combined to give the final suggestion. Using this system, heart sounds can be selectively stored, retrieved, enhanced, and replayed. Besides, the CHACS provides an online display of the heart beat rate and allows an objective and reliable classification of heart sounds. Experimental results show that a classification rate of 95.6% is obtained
Keywords :
computer aided analysis; echocardiography; frequency-domain analysis; medical diagnostic computing; medical signal processing; multilayer perceptrons; time-domain analysis; CHACS; classification rate; classification results; computer-aided heart sound analysis; computer-aided heart sound classification system; experimental results; frequency domain; heart beat rate; heart sound patterns; heart sounds; heuristic rules; multilayer perceptron neural network; neural networks; time analysis; time domain; Acoustical engineering; Cardiac disease; Cardiology; Computer aided analysis; Computer networks; Frequency domain analysis; Heart beat; Information analysis; Neural networks; Stethoscope;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location :
Detroit, MI
ISSN :
1520-6149
Print_ISBN :
0-7803-2431-5
Type :
conf
DOI :
10.1109/ICASSP.1995.479729
Filename :
479729
Link To Document :
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