Knowledge-based Doppler blood-velocimeter system

Abstract

A scheme of a knowledge-based Doppler blood-velocimeter system using an artificial neural network is proposed. The scheme supports feature extraction from a Doppler ultrasonography periodogram, and comparison with statistical data to make therapeutic studies on that basis. A physical model of blood flow with salient features taken into account, spectral estimation using the time varying autoregressive moving average (ARMA) model, and an artificial neural network (ANN) scheme for the determination of the coefficients of the ARMA model has been presented.