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1.
Journal of Biomedical Engineering ; (6): 756-761, 2008.
Artículo en Chino | WPRIM | ID: wpr-342749

RESUMEN

Heart sounds are highly valuable to the clinical diagnoses of most cardiovascular diseases, so the analysis of phonocardiographic signals is helpful to diagnosing cardiovascular diseases clinically. Phonocardiographic signals are non-stable, so it is necessary to choose appropriate method in time-frequency analysis. The traditional method such as Fourier Transform is dissatisfactory. Continuous Wavelet Transform (CWT) and Matching (MPM) Pursuit Method are both effective methods. They can be used to extract and cluster the characteristics of the signals. By analysis and comparison, the two methods showed the advantages over traditional methods. Additionally, their respective merits and demerits are indicated.


Asunto(s)
Humanos , Algoritmos , Análisis de Fourier , Ruidos Cardíacos , Fonocardiografía , Procesamiento de Señales Asistido por Computador
2.
Journal of Biomedical Engineering ; (6): 766-769, 2008.
Artículo en Chino | WPRIM | ID: wpr-342747

RESUMEN

Independent component analysis (ICA) is a novel method developed in recent years for Blind Source Separation. In this paper, the phonocardiogram (PCG) was separated into three components by applying ICA. The basic principle of ICA was introduced in this paper. A fast and robust fixed-point algorithm for ICA was used to analyze PCG signals in this study. The experiments showed that ICA could separate the components of heart sounds from PCG signals successfully.


Asunto(s)
Humanos , Algoritmos , Ruidos Cardíacos , Fonocardiografía , Métodos , Análisis de Componente Principal , Procesamiento de Señales Asistido por Computador
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