Abstract
We propose an extension of independent component analysis when applied for fetal ECG extraction. Before using the classical ICA method, we multiply the number of measured signals using the technique of delays (each signal channel delayed by a proper time interval is regarded as a new measured signal). After this duplication of the measured signal channels, the classical JADE algorithm is applied to perform blind separation of independent source signals. Then we use a simple algorithm to select the estimated source signal that contains the fetal ECG of the best quality. We compare the results obtained using the classical ICA and the approach proposed. The experiments performed on 4-channel maternal abdominal ECG signals confirm the superior performance of this approach.
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Acknowledgement
This work was partially supported by the Ministry of Science and Higher Education funding for statutory activities of young researchers (BKM- BKM-510/RAu-3/2017). The work was performed using the infrastructure supported by POIG.02.03.01-24-099/13 grant: GeCONiI–Upper Silesian Center for Computational Science and Engineering.
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Piela, M., Moroń, T. (2019). Spatio-Temporal Extension of Independent Component Analysis for Fetal ECG Extraction. In: Pietka, E., Badura, P., Kawa, J., Wieclawek, W. (eds) Information Technology in Biomedicine. ITIB 2018. Advances in Intelligent Systems and Computing, vol 762. Springer, Cham. https://doi.org/10.1007/978-3-319-91211-0_28
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DOI: https://doi.org/10.1007/978-3-319-91211-0_28
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