Modeling of a System for fECG Extraction from abdECG

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Abstract

The objective of this paper is to move a step ahead in investigation and create a feasible, cost effective fetal ECG analysis tool for clinical practice which will be easy for usage by any non-skilled personal and provide actionable medical information such as the QRS complex of fetal ECG, fetal HR etc. In this method, a composite abdominal ECG is subjected to a pre-processing stage which involves filtering and normalization, then fed into the ‘thresholding and peak finding’ stage to detect the maternal ECG peaks. The next stage involves construction of the MLE of maternal ECG embedded in the abdominal ECG. After this, the constructed MLE which represent the maternal ECG is subtracted from the abdominal ECG to obtain fetal ECG along with a smidgen of noise. This noise which adulterates the fetal ECG is removed by filtering, done at the post processing stage. Thresholding and peak finding is done at the post processed signal to calculate the fetal HR. This paper puts forth a promising possibility of implementing the proposed algorithm in any suitable hardware model, since an average Accuracy of 76.8% and average Sensitivity of 90.7% is attained.

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John, R. G., Deepan Chakravarthy, P., Ramachandran, K. I., & Anand, P. (2018). Modeling of a System for fECG Extraction from abdECG. In Advances in Intelligent Systems and Computing (Vol. 736, pp. 568–579). Springer Verlag. https://doi.org/10.1007/978-3-319-76348-4_55

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