Journal of Soft Computing Paradigm
IRO Journals
Volume 1 — Issue 1 — September 2019

PERFORMANCE ANALYSIS OF GRANULAR COMPUTING MODEL IN SOFT COMPUTING PARADIGM FOR MONITORING OF FETAL ECHOCARDIOGRAPHY

https://doi.org/10.36548/jscp.2019.1.002
A. Sathesh
Professor, Department of Electronics and Communication Engineering, Eritrea Institute of Technology
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How to Cite

Sathesh, A. 2019. “PERFORMANCE ANALYSIS OF GRANULAR COMPUTING MODEL IN SOFT COMPUTING PARADIGM FOR MONITORING OF FETAL ECHOCARDIOGRAPHY”. Journal of Soft Computing Paradigm 1 (1): 14-23. https://doi.org/10.36548/jscp.2019.1.002.
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Keywords

— Granular computing
— Soft computing
— Fuzzy sets
— Training data set
— Fetal heart rate
— Prediction accuracy and Detection accuracy
Published: 30-09-2019

Abstract

The monitoring of fetal heart being essential in the second trimester of the prenatal periods. The abnormalities in the child heart rate has to be identified in the early stages, so as to take essential remedies for the babies in the womb, or would enable the physician to be ready for he complication on the delivery and the further treatment after the baby is received. The traditional methodologies being ineffective in detecting the abnormalities leading to fatalities, paves way for the granular computing based fuzzy set, that requires only a limited set of data for training, and helps in the eluding of the unwanted data set that are far beyond the optimal. Further the methods performance is analyzed to evident the improvement in the fetal heart rate detection in terms of prediction accuracy and the detection accuracy.

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