Neural Network Analysis and Evaluation of the Fetal Heart Rate

• Main Authors: Yasuaki Noguchi, Fujihiko Matsumoto, Kazuo Maeda, Takashi Nagasawa
• Format: Article
• Language: English
• Published: MDPI AG 2009-01-01
• Series: Algorithms
• Subjects: Neural network; fetus; neonate; fetal heart rate (FHR); sinusoidal FHR; non-reassuring fetal status; neonatal asphyxia
• Online Access: http://www.mdpi.com/1999-4893/2/1/19/

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.