Detection of normal and pathological fetal states by means of neural and fuzzy classifiers applied to CTG parameters

Author

Magenes, Giovanni ; Signorini, M.G. ; Arduini, Domenico

Author_Institution

Dipt. di Inf. e Sistemistica, Pavia Univ., Italy

Volume

2

fYear

1999

fDate

36434

Abstract

One neural and one fuzzy classifier are proposed to discriminate among normal and pathological fetal conditions during pregnancy. Both classifiers are based on linear and nonlinear indexes extracted from cardiotocographic fetal monitoring. Results low very promising performance on the set of collected fetal heart rate signals

Keywords

backpropagation; cardiology; feature extraction; fuzzy set theory; medical signal processing; multilayer perceptrons; obstetrics; patient monitoring; pattern classification; CTG parameters; adaptive backpropagation algorithm; cardiotocographic fetal monitoring; fetal heart rate signals; fuzzy classifiers; linear indexes; multilayer perceptron; neural classifiers; nonlinear indexes; normal fetal states; pathological fetal states; pregnancy; Acceleration; Cardiography; Diabetes; Fetal heart rate; Frequency domain analysis; Heart rate detection; Pathology; Pregnancy; Resonant frequency; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

[Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint

Conference_Location

Atlanta, GA

ISSN

1094-687X

Print_ISBN

0-7803-5674-8

Type

conf

DOI

10.1109/IEMBS.1999.804090

Filename

804090