Date of Award
12-2015
Degree Name
Master of Science in Engineering
Department
Electrical and Computer Engineering
First Advisor
Dr. Ikhlas Abdel-Qader
Second Advisor
Dr. Raghe Gejji
Third Advisor
Dr. Azim Houshyar
Keywords
Cardiac sounds, phonocardiogram, wavelet, Hilbert-Huang transform, Support Vector Machine
Access Setting
Masters Thesis-Open Access
Abstract
The Phonocardiogram (PCG) signal contains valuable information about the cardiac condition and is a useful tool in recognizing dysfunction and heart failure. By analyzing the PCG, early detection and diagnosis of heart diseases can be accomplished since many pathological conditions of the cardiovascular system cause murmurs or abnormal heart sounds. This thesis presents an algorithm to classify normal and abnormal heart sound signals using PCG. The proposed analysis is based on a framework composed of several statistical signal analysis techniques such as wavelet based de-noising, energy-based segmentation, Hilbert-Huang transform based feature extraction, and Support Vector Machine based classification. The MATLAB test results using PCG recordings validate the model used in the proposed system with very high classification accuracy averaged at 90.5%.
Recommended Citation
Tong, Zichun, "An Integrated Framework for Cardiac Sounds Diagnosis" (2015). Masters Theses. 671.
https://scholarworks.wmich.edu/masters_theses/671