Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/5663
Title: Classification of hierarchically clustered and homomorphic segmented heart sounds using neural networks
Authors: Gupta, Cota Navin.
Keywords: DRNTU::Engineering::Bioengineering
Issue Date: 2005
Abstract: Cardiac auscultation is widely used by physicians to evaluate cardiac functions in patients and detect the presence of abnormalities. Phonocardiogram signals (PCG) are heart signals which contain vital information about the heart and can be used effectively in diagnosing various pathological conditions of heart valves. Computer- based analysis of heart sounds can be used for diagnostic purposes. This present study embarks on the development of an automatic diagnostic system for characterization of phonocardiogram signals which were hierarchically clustered and homomorphically segmented and classified using neural networks. There are three core parts to the system: (1) segmentation, (2) feature extraction, (3) classification.
URI: http://hdl.handle.net/10356/5663
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:MAE Theses

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