Kim S H, Lee H J, Huh J M, Chang B C
Yonsei Med J. 1998 Aug;39(4):302-8. doi: 10.3349/ymj.1998.39.4.302.
The spectral analysis of heart valve sound is a noninvasive diagnostic method known to be useful in evaluating the state of the heart valve function. This may provide early detection of valve calcification, thrombus or destruction, since previous studies have shown that the dominant frequency peak moved to a high frequency area when natural heart valve leaflets were calcified, stiffened or destroyed. However, it is important for a heart valve sound diagnostic system to find a proper spectral analysis method on phonocardiography. Until now, conventional frequency analyses such as the Fourier transform or autoregressive spectral estimation technique have been used to estimate spectral components of a phonocardiogram, but they are inappropriate because the signal frequency is assumed to remain constant during the transform interval. To overcome this problem, in this study, FOS (Fast Orthogonal Search) & MUSIC (MUltiple SIgnal Classification), which both appeared suitable for the analysis of biological data, were applied to prosthetic heart valve sound as the new heart valve sound spectral analysis methods. Five subjects with normally functioning mechanical heart valves and a patient with a malfunctioning one were selected to collect the heart valve sound signals. As a result, the second dominant peak frequency proved to be important along with the first dominant peak frequency in identifying the valve function. This study showed that the new heart valve sound spectral analysis method presented in this paper may be an effective method in heart valve sound analysis. Further study using this system in a large population of patients will aid in providing a diagnostic method in the early detection of valve failure.
心脏瓣膜音的频谱分析是一种无创诊断方法，已知对评估心脏瓣膜功能状态有用。这可能有助于早期发现瓣膜钙化、血栓或破坏，因为先前的研究表明，当天然心脏瓣膜小叶发生钙化、硬化或破坏时，主导频率峰值会移向高频区域。然而，对于心脏瓣膜音诊断系统来说，在心音图上找到一种合适的频谱分析方法很重要。到目前为止，传统的频率分析方法，如傅里叶变换或自回归谱估计技术，已被用于估计心音图的频谱成分，但它们并不合适，因为在变换区间内信号频率被假定为保持恒定。为了克服这个问题，在本研究中，FOS（快速正交搜索）和MUSIC（多重信号分类）这两种似乎都适用于生物数据分析的方法，被作为新的心脏瓣膜音频谱分析方法应用于人工心脏瓣膜音。选择了五名机械心脏瓣膜功能正常的受试者和一名功能异常的患者来收集心脏瓣膜音信号。结果表明，在识别瓣膜功能方面，第二主导峰值频率与第一主导峰值频率同样重要。本研究表明，本文提出的新的心脏瓣膜音频谱分析方法可能是一种有效的心脏瓣膜音分析方法。使用该系统对大量患者进行进一步研究将有助于提供一种早期检测瓣膜功能衰竭的诊断方法。
