Real-time system for robust spectral parameter estimation in Doppler signal analysis.

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.

On the use of autoregressive time series in the modelling of Doppler signals for diagnostic purposes.

Doppler instruments are widely used in the diagnosis of vascular diseases: however, the physician generally makes the diagnosis from personal experience, and by subjective evaluation of some quantities related to blood flow (e.g., maximum or mean frequency envelope, or zero-crossing density).