Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Development of Diagnostic System for FHR Monitering by Using Neural Networks

  • Cha Kyung-Joon (Dept. of Mathematics, Hanyang University) ;
  • Park Moon-Il (Dept. of Obstetrics & Gynecology, Hanyang University) ;
  • Oh Jae-Eung (Dept. of Mechanical Engineering, Hanyang University) ;
  • Han Hyun-Ju (Dept. of Obstetrics & Gynecology, Hanyang University) ;
  • Lee Hae-Jin (Dept. of Mechanical Engineering, Hanyang University) ;
  • Park Young-Sun (Dept. of Mechanical Engineering, Hanyang University)
  • Published : 2006.04.01
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Abstract

In this paper, we construct data-base for fetal heart rate (FHR) data and develop the FHR Monitering system to diagnose fetus, HYFM-III. For diagnostic system, a few statistical decision making mechanism are adopted, such as approximate entropy, neural networks, and logistic discrimination. Since FHR data is very chaotic, we mostly adopt nonlinear statistical methods. On the basis of this system, we expect to develop expert system for early detection of abnormal fetus.

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References

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