Spectral analysis and LDB based classification of heart sounds with mechanical prosthetic heart valves.
- Author:
Di ZHANG
1
;
Yuequan WU
;
Jianping YAO
;
Song YANG
;
Minghui DU
Author Information
1. 1 (Department of Computer Science, Shaoguan University, Shaoguan 512005, China.
- Publication Type:Journal Article
- MeSH:
Algorithms;
Heart Sounds;
physiology;
Heart Valve Diseases;
physiopathology;
surgery;
Heart Valve Prosthesis;
Heart Valves;
physiopathology;
Humans;
Pattern Recognition, Automated;
Phonocardiography;
Signal Processing, Computer-Assisted;
Spectrum Analysis;
methods
- From:
Journal of Biomedical Engineering
2011;28(6):1207-1212
- CountryChina
- Language:Chinese
-
Abstract:
Auscultation, the act of listening for heart sounds to aid in the diagnosis of various heart diseases, is a widely used efficient technique by cardiologists. Since the mechanical prosthetic heart valves are widely used today, it is important to develop a simple and efficient method to detect abnormal mechanical valves. The study on five different mechanical valves showed that only the case of perivalvular leakage could be detected by spectral estimation. Though it is possible to classify different mechanical valves by using time-frequency components of the signal directly, the recognition rate is merely 84%. However, with the improved local discriminant bases (LDB) algorithm to extract features from heart sounds, the recognition rate is 97.3%. Experimental results demonstrated that the improved LDB algorithm could improve classification rate and reduce computational complexity in comparison with original LDB algorithm.
