将快速傅里叶变换（FFT）分析的心脏多普勒信号应用于模糊算法。

Application of FFT analyzed cardiac Doppler signals to fuzzy algorithm.

作者信息

Güler Inan, Hardalaç Firat, Barişçi Necaattin

机构信息

Department of Electronics and Computer Education, Faculty of Technical Education, Gazi University, 06500, Ankara, Teknikokullar, Turkey.

出版信息

Comput Biol Med. 2002 Nov;32(6):435-44. doi: 10.1016/s0010-4825(02)00021-5.

DOI:10.1016/s0010-4825(02)00021-5

PMID:12356493

Abstract

Doppler signals, recorded from the output of tricuspid, mitral, and aorta valves of 60 patients, were transferred to a personal computer via 16-bit sound card. The fast Fourier transform (FFT) method was applied to the recorded signal from each patient. Since FFT method inherently cannot offer a good spectral resolution at highly turbulent blood flows, it sometimes leads to wrong interpretation of cardiac Doppler signals. In order to avoid this problem, firstly six known diseased heart signals such as hypertension, mitral stenosis, mitral failure, tricuspid stenosis, aorta stenosis, aorta insufficiency were introduced to fuzzy algorithm. Then, the unknown heart diseases from 15 patients were applied to the same fuzzy algorithm in order to detect the kinds of diseases. It is observed that the fuzzy algorithm gives true results for detecting the kind of diseases.

摘要

从60名患者的三尖瓣、二尖瓣和主动脉瓣输出端记录的多普勒信号，通过16位声卡传输到个人计算机。对每位患者记录的信号应用快速傅里叶变换（FFT）方法。由于FFT方法在高湍流血流情况下本质上无法提供良好的频谱分辨率，有时会导致对心脏多普勒信号的错误解读。为避免此问题，首先将六种已知的患病心脏信号，如高血压、二尖瓣狭窄、二尖瓣衰竭、三尖瓣狭窄、主动脉狭窄、主动脉瓣关闭不全，引入模糊算法。然后，将15名患者的未知心脏疾病应用于同一模糊算法以检测疾病种类。观察发现，模糊算法在检测疾病种类方面给出了正确结果。