Carotid artery blood flow: single factor classification of Doppler waveforms.

The usefulness of principal components factor analysis as a way of classifying Doppler waveforms from the carotid artery has been established. The waveform is first reduced to a small set of coefficients which capture, via their associated principal components, the essential shape of the waveform. The vector of these coefficients can be used to classify the waveform by finding the position of this vector in a classification space relative to one or more classifying surfaces. This short communication will show how these two steps may be combined to produce a single factor for classification.

[1]  T. R. P. Martin,et al.  Use of principal component factor analysis in the detection of carotid artery disease from Doppler ultrasound , 2006, Medical and Biological Engineering and Computing.

[2]  D H Evans,et al.  The effect of proximal stenosis on Doppler waveforms: a comparison of three methods of waveform analysis in an animal model. , 1981, Clinical physics and physiological measurement : an official journal of the Hospital Physicists' Association, Deutsche Gesellschaft fur Medizinische Physik and the European Federation of Organisations for Medical Physics.

[3]  T. R. P. Martin,et al.  Objective feature extraction applied to the diagnosis of carotid artery disease using a Doppler ultrasound technique , 1980 .

[4]  Julius T. Tou,et al.  Pattern Recognition Principles , 1974 .

[5]  D H Evans,et al.  Common femoral artery Doppler wave‐forms: A comparison of three methods of objective analysis with direct pressure measurements , 1984, The British journal of surgery.