Automatic diagnosis of fetal heart rate: comparison of different methodological approaches
Contributo in Atti di convegno
Data di Pubblicazione:
2001
Citazione:
Automatic diagnosis of fetal heart rate: comparison of different methodological approaches / G. Magenes, M.G. Signorini, R. Sassi - In: Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE. 2[s.l] : IEEE Press, 2001. - ISBN 0780372115. - pp. 1604-1607 (( Intervento presentato al 23. convegno International Conference of the IEEE Engineering in Medicine and Biology Society tenutosi a Istanbul nel 2001.
Abstract:
The cardiotocograpy (CTG) is the clinical, traditional, noninvasive approach to monitor the fetal condition antepartum. CTG analysis is focused on the detection of fetal heart rate parameters from which the clinicians can identify by eye inspection some patterns associated to fetal activity. However this qualitative method rarely can detect the emergence of fetal pathologies. This study aims at finding new algorithms which can enhance the differences among the normal CTG signals and those presenting anomalies due to a pathological status. On a database of more than 500 recordings, we tested different classification methods to identify normals from potential pathological fetuses. A Multilayer Perceptron (MLP) neural network and an Adaptive Neuro-Fuzzy Inference System (ANFIS) were compared with classical statistical methods. Both the neural and neuro-fuzzy approaches seem to give better results than any tested statistical classifier.
Tipologia IRIS:
03 - Contributo in volume
Keywords:
fetal heart rate; neural networks; fuzzy systems; multivariate methods
Elenco autori:
G. Magenes, M.G. Signorini, R. Sassi
Link alla scheda completa:
Titolo del libro:
Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE. 2