Fuzzified Evaluation of Cardiotocography Data for Real Medical Data

Abstract

Level evaluation system in cardiotocography (CTG) taken in the real medical practice is constructed for the use of e-learning materials. The system consists of 3 parts, preprocessing for FHR by particle filter, extraction process of deceleration information, and level evaluation. The extraction and evaluation processes are executed by fuzzy inference. To check the effectiveness of the proposed system, level evaluation experiments are executed for the real CTG data extracted from records at the Kochi Medical School hospital. The experimental results show that the extracted CTG features are suitable for the material, and that the calculated level of the patients with abnormal pH value is evaluated as abnormal situations. The proposed system can provide the possible data for the materials for evaluation learning of real CTG.