Classification of cutaneous microcirculation signals

Author

Hitti, Eric ; Lucus, M.F. ; Saumet, Jean-Louis

Author_Institution

Lab. d´´Autom. de Nantes, Nantes Univ., France

fYear

1997

fDate

11-13 Jun 1997

Firstpage

76

Lastpage

80

Abstract

The aim of our study is to develop a computer aided diagnosis tool, allowing characterization of blood tissues from laser Doppler signals of microcirculation. A learning population of four classes corresponding to various local treatments inducing vasoconstriction or vasodilation is available. Signals are modelled by ARMA processes estimated by maximum likelihood identification. Several distances between signals are presented, and we show the first results obtained with the cepstral distance on a set of real data

Keywords

autoregressive moving average processes; cepstral analysis; haemodynamics; maximum likelihood estimation; medical diagnostic computing; medical signal processing; pattern classification; ARMA process; blood tissue characterization; cepstral distance; computer aided diagnosis tool; cutaneous microcirculation signal classification; laser Doppler signals; learning; maximum likelihood identification; vasoconstriction; vasodilation; Alloying; Blood flow; Cepstral analysis; Electronic mail; Gaussian noise; Hospitals; Ischemic pain; Pathology; Protocols; Signal processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer-Based Medical Systems., 1997. Proceedings., Tenth IEEE Symposium on

Conference_Location

Maribor

ISSN

1063-7125

Print_ISBN

0-8186-7928-X

Type

conf

DOI

10.1109/CBMS.1997.596412

Filename

596412