Publication 2020 OCTOBER VOL 1 Issue 1

Fetal Cardiac Arrhythmia Detection using enhanced Blind Source Separation Technique

Gayathri Krishnan S, Sajeer M  

 

Abstract - — The welfare of fetus in the womb of mother during pregnancy can be monitor by inspecting the fetal electrocardiogram waveform. In signal processing field, there are various techniques for analysing this purpose. Tracking fetal ECG (fECG) can provide important details for detecting fetal cardiac arrhythmia, thus treatment can be done as early as possible and hence we can diminish the mortality rate of babies. In this paper, a novel method for detecting cardiac arrhythmia in fetus in early stages of pregnancy and to classify the cardiac arrhythmia into five classes using enhanced blind source separation technique (BSS) is proposed. The scheme is based on WASOBI based BSS for pre-processing and extraction of fetal ECG. Feature selection is manipulated using the Peak detection algorithm and Multi-class Support Vector Machine (SVM), is employed for the classification of fetal cardiac arrhythmia. .

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Keywords –

Abdominal ECG Recordings, Fetal Cardiac Arrhythmia, Fetal ECG, WASOBI based BSS, EFICA, Multi-class SVM.


 

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    Authors :

    Gayathri Krishnan S

    PG Scholar, Department of ECE Sree Chitra Thirunal College of Engineering Thiruvananthapuram, Kerala gaya3666gks@gmail.com

    Sajeer M

    Assistant Professor, Department of ECE Sree Chitra Thirunal College of Engineering Thiruvananthapuram, Kerala sajeer@sctce.ac.in

      


    CITATION FORMAT

    Gayathri Krishnan S, Sajeer M " Fetal Cardiac Arrhythmia Detection using enhanced Blind Source Separation Technique " International Journal of Innovations and Implementations in Engineering(ISSN 2454- 3489) , OCTOBER 2020 vol 1

     


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