Neural Network Analysis and Evaluation of the Fetal Heart Rate

Algorithms

Yasuaki Noguchi¹  Fujihiko Matsumoto¹  Kazuo Maeda² 

[1] Department of Applied Physics, National Defense Academy, 1-10-20 Hashirimizu, Yokosuka, Kanagawa 239-8686, Japan. E-mail:;Professor Emeritus, Department of Obstetrics and Gynecology, Tottori University.  Home: 3-125, Nadamachi, Yonago, Tottori, 683-0835, Japan. E-mail:

关键词: Neural network;    fetus;    neonate;    fetal heart rate (FHR);    sinusoidal FHR;    non-reassuring fetal status;    neonatal asphyxia;   

DOI  :  10.3390/a2010019

来源: mdpi

【 摘 要 】

The aim of the present study is to obtain a highly objective automatic fetal heart rate (FHR) diagnosis. The neural network software was composed of three layers with the back propagation, to which 8 FHR data, including sinusoidal FHR, were input and the system was educated by the data of 20 cases with a known outcome. The output was the probability of a normal, intermediate, or pathologic outcome. The neural index studied prolonged monitoring. The neonatal states and the FHR score strongly correlated with the outcome probability. The neural index diagnosis was correct. The completed software was transferred to other computers, where the system function was correct.

【 授权许可】

CC BY   
© 2009 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.