Spectral analysis and LDB based classification of heart sounds with mechanical prosthetic heart valves / 生物医学工程学杂志
J. biomed. eng
; Sheng wu yi xue gong cheng xue za zhi;(6): 1207-1212, 2011.
Article
en Zh
| WPRIM
| ID: wpr-274925
Biblioteca responsable:
WPRO
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.
Texto completo:
1
Índice:
WPRIM
Asunto principal:
Fonocardiografía
/
Fisiología
/
Análisis Espectral
/
Cirugía General
/
Algoritmos
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Procesamiento de Señales Asistido por Computador
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Prótesis Valvulares Cardíacas
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Reconocimiento de Normas Patrones Automatizadas
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Ruidos Cardíacos
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Enfermedades de las Válvulas Cardíacas
Límite:
Humans
Idioma:
Zh
Revista:
J. biomed. eng
/
Sheng wu yi xue gong cheng xue za zhi
Año:
2011
Tipo del documento:
Article