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find Keyword "Euclidean distance" 1 results
  • Automatical Assessment of Fetal Status Based on Fuzzy Theory and Euclidean Distance

    Computer analysis of cardiotocography (CTG) is very significant to evaluate fetal status. However, current computer analysis based on traditional classification criteria is not ideal. In order to improve the accuracy of fetal status assessment, we proposed a new method. The new method improves the classification criteria and uses fuzzy set to represent the CTG parameters. And then feature vector is formed by that set to represent the CTG signal. By calculating and comparing the Euclidean distance between the signal feature vector and the standard state feature vector, the corresponding fetal status of the signal can be determined. Experiments showed that compared to the results of the first expert, the accuracy rate of new method was 88.3% which was higher than that (69.9%) of the traditional method, and the false positive rate of new method was 7.2% which was much lower than that (34.9%) of traditional methods. While compared to the results of the second expert, the accuracy of new method was 90.3% which was higher than that (66.0%) of the traditional method, and the false positive rate of new method was 9.0% which was well below the 38.2% of the traditional method. Thus the new method is reliable and effective.

    Release date:2017-01-17 06:17 Export PDF Favorites Scan
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