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Portable Fetal ECG Extractor from abdECG

Publication Type : Conference Proceedings

Publisher : 2016 International Conference on Communication and Signal Processing (ICCSP)

Source : 2016 International Conference on Communication and Signal Processing (ICCSP), p.0698 – 0701 (2016)

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Keywords : Abdominal ECG, Abdominal ECG (abdECG), Biomedical monitoring, C language, congenital disorder diagnosis, culled out signal, Electrocardiography, Feature extraction, fECG extractor, Fetal ECG (fECG), Fetal heart rate, Fetal Heart Rate (fHR), fetal peaks, fetus, fetus health, fetus heart rate, fetus QRS complex, Filtering, filtering theory, first order differentiation, high level language C, invasive fECG extraction, Maternal ECG (mECG), maternal peak, mECG QRS complex, medical signal processing, Monitoring, Normalization, obstetrics, patient diagnosis, portable fetal ECG extractor, Prenatal, preprocessed abdECG signal, Raspberry Pi, Sensitivity, Signal processing algorithms, Thresholding

Campus : Coimbatore

School : School of Engineering

Center : Computational Engineering and Networking

Department : Mechanical Engineering

Year : 2016

Abstract : This paper aims at creating an affordable fECG extractor by simplifying the process of fECG extraction from abdECG. Even though invasive fECG extraction is more accurate, noninvasive method of extraction has been preferred during prenatal considering the fetus's health. This makes the noninvasive fECG extraction an emerging and required field of research. This paper gives a fundamental idea to create a prototype for extracting the fetal ECG from abdominal ECG. The abdECG has been preprocessed by normalization and filtering. Based on thresholding and first order differentiation, the maternal peak has been identified from the preprocessed abdECG signal. Using the identified maternal peaks, QRS complex of mECG has been identified and the same has been cancelled out from abdECG to cull out the fECG. The resultant signal has been a combination of fECG and noise. The fetal peaks have been identified from the culled out signal. The identified fetal peaks provide information like the QRS complex of the fetus, fetus heart rate, diagnosis of any congenital disorder and other anomalies. This simplified algorithm has been implemented with high level language C and executed using Raspberry Pi. The execution results with a second delay and Raspberry Pi can create a standalone platform at any place and is handy. The system resulted in 100% accuracy when the selected channel happened to be near the fetus's heart. Even in other cases, it has proven to be good and effective. This shows that the system is affordable and practically useable.

Cite this Research Publication : R. J. Gini, Dr. K. I. Ramachandran, Nair, R. H., and Anand, P., “Portable Fetal ECG Extractor from abdECG”, 2016 International Conference on Communication and Signal Processing (ICCSP). pp. 0698 – 0701, 2016.

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