Title :
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
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;
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
Print_ISBN :
0-7803-5674-8
DOI :
10.1109/IEMBS.1999.804090
