Abstract
The infant mortality rate is the number of newborns death under 1 year of age occurring among the live births in a given region during a given year. Electrocardiogram is generally used for finding the cardiovascular variation. The infant mortality rate can be drastically reduced by adopting this proposed diagnosis technique for fetus. This proposed work provides an indication of fetal health and heart information. Sometimes newborn babies will be affected by heart diseases like tachycardia and bradycardia. By diagnosing these diseases, we could reduce the death rate of the newborns. This method proposes an early detection of fetal ECG and the arrhythmia of the fetus. So this will dynamically reduce the infant mortality rate. It brings amazing changes in the fields of medical industries and medical research fields. The main aim of this work is to detect the variations in the heart rate. The variations in the heart can be detected by using feature vector that is extracted from the signal and a classification method is also used to classify the signal as abnormal and normal. This work shows a result of accuracy about 94.11% and sensitivity of 88.88%.
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Surya, K., Abdul Majeed, K.K. (2021). Multichannel Probabilistic Framework for Prenatal Diagnosis of Fetal Arrhythmia Using ECG. In: Palesi, M., Trajkovic, L., Jayakumari, J., Jose, J. (eds) Second International Conference on Networks and Advances in Computational Technologies. Transactions on Computational Science and Computational Intelligence. Springer, Cham. https://doi.org/10.1007/978-3-030-49500-8_13
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DOI: https://doi.org/10.1007/978-3-030-49500-8_13
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