Di Giuliomaria C, Capponi M, D'Alessio T, Sacco R, Zanette E
Biotronix srl, Lungotevere dei Mellini, Roma, Italy.
Med Biol Eng Comput. 1990 Jan;28(1):54-9. doi: 10.1007/BF02441678.
In assessing the level of stenosis in extracranial Doppler analysis, spectral analysis has until now been used qualitatively, for the most part. Owing to the many variables affecting the measurements (mainly noise level and instrument setting made subjectively by the operator), the reliability of the inferences on the degree of stenosis is not clearly definable. Under such conditions the need arises for algorithms and systems that can estimate spectral parameters with a higher degree of accuracy, to verify whether reliable inferences can indeed by made or if this technique is only a qualitative one. In the paper a real-time spectral analysis system is described. The system relies on a new spectral estimation algorithm which gives estimates with good robustness with respect to noise. Moreover, a clear measurement procedure which eliminates the many subjective factors affecting the estimates has also been proposed and used. The system has been evaluated with simulated signals and in clinical trials and has shown better performance than the commonly used commercial analysers.
在评估颅外多普勒分析中的狭窄程度时,到目前为止,频谱分析大多是定性使用的。由于影响测量的变量众多(主要是噪声水平和操作员主观设置的仪器参数),关于狭窄程度的推断的可靠性无法明确界定。在这种情况下,就需要能够更精确地估计频谱参数的算法和系统,以验证是否真的能够做出可靠的推断,或者该技术是否仅仅是定性的。本文描述了一种实时频谱分析系统。该系统依赖于一种新的频谱估计算法,该算法在噪声方面具有良好的稳健性。此外,还提出并采用了一种明确的测量程序,该程序消除了许多影响估计的主观因素。该系统已通过模拟信号和临床试验进行了评估,结果表明其性能优于常用的商业分析仪。