Automatic classifiers for medical data from doppler unit
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Date
2007
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Czech Technical University
Technická Univerzita v Liberci
Technical university of Liberec, Czech Republic
Technická Univerzita v Liberci
Technical university of Liberec, Czech Republic
Abstract
Nowadays, hand-held ultrasonic Doppler units are often used for noninvasive screening of atherosclerosis in arteries of the lower limbs. The mean velocity of blood flow in time and blood pressures are measured on several positions on each lower limb. This project presents soft-ware that is able to analyze such data and classify it in real time into selected diagnostic classes. It is also capable of giving a notice of some errors encountered during meas-uring. At the Department of Functional Diagnostics in the Regional Hospital of Liberec a database of several hun-dreds signals was collected. In cooperation with the spe-cialist, the signals were manually classified into four classes. Consequently selected signal features were ex-tracted and used for training a distance and a Bayesian classifier. Another set of signals was used for evaluating and optimizing the parameters of the classifiers. This paper compares the results of the software with those provided by a human expert. They agreed in 89 % cases.
Description
Subject(s)
Hand-held ultrasonic Doppler unit, Medical data recognition, Peripheral arterial disease
Citation
ISSN
1210-2512