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Detection of Fetal Electrocardiogram from Multivariate Abdominal Recordings by using Wavelets and Neuro-Fuzzy Systems


     

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The fetal electrocardiogram (FECG) signal is outcome of the electrical activity of the fetal heart after 21 days of the pregnancy. It contains information about the health status of the fetus and so, an early diagnosis of any cardiac defects before delivery (Specially in case of labour pain) increases the chance of the appropriate treatment. In this paper we consider one signal from the thoracic and another from abdomen of the mother. The artificial neural network fuzzy inference system (ANFIS) is used to obtain the FECG component from abdominal ECG recording and reference thoracic maternal electrocardiogram (MECG) signal. The obtained FECG is being enhanced by using wavelet transform.

Keywords

ECG, MECG, FECG, Neural Network, Fuzzy Logic, Membership Function and Wavelet Transform.
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  • Detection of Fetal Electrocardiogram from Multivariate Abdominal Recordings by using Wavelets and Neuro-Fuzzy Systems

Abstract Views: 214  |  PDF Views: 4

Authors

Abstract


The fetal electrocardiogram (FECG) signal is outcome of the electrical activity of the fetal heart after 21 days of the pregnancy. It contains information about the health status of the fetus and so, an early diagnosis of any cardiac defects before delivery (Specially in case of labour pain) increases the chance of the appropriate treatment. In this paper we consider one signal from the thoracic and another from abdomen of the mother. The artificial neural network fuzzy inference system (ANFIS) is used to obtain the FECG component from abdominal ECG recording and reference thoracic maternal electrocardiogram (MECG) signal. The obtained FECG is being enhanced by using wavelet transform.

Keywords


ECG, MECG, FECG, Neural Network, Fuzzy Logic, Membership Function and Wavelet Transform.