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Assessment of the Fetal Health Using NI-aECG

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Advanced Computational and Communication Paradigms

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 475))

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Abstract

Accurate extraction of the fetal QRS (FQRS) complex extracted from the maternal abdominal ECG (aECG) has become a very important clinical procedure to evaluate the well-being of the fetus. Fetal heart rate (FHR) obtained from the FQRS indicates fetal hypoxia, fetal distress, and other fetal-related problems that can be easily detected. In this paper, the aECG is preprocessed to remove the low-frequency baseline wandering and power line interference (PLI). In the following step, we proposed a technique to extract maternal QRS (MQRS) and FQRS from the Physionet abdominal ECG (aECG) database. The computed maternal and fetal QRS templates were optimized and fine-tuned for each of the Physionet noninvasive aECG databases. Our proposed synthesized QRS pulse template method was also compared with the Independent Component Analysis (ICA) method for performance. The proposed system correctly evaluated and estimated the FECG signal for most records for the Physionet abdominal and direct fetal ECG database (adfecgdb) with the fetal QRS annotations. Using cross-correlation techniques, the MQRS and FQRS were estimated while the FHR was also correctly computed for most records.

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Author information

Authors and Affiliations

  1. Padre Conceicao College of Engineering, Goa, India

    Niyan Marchon

  2. Electronics Department, Goa University, Goa, India

    Gourish Naik

Authors
  1. Niyan Marchon
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  2. Gourish Naik
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Corresponding author

Correspondence to Niyan Marchon .

Editor information

Editors and Affiliations

  1. Department of Computer Application, RCC Institute of Information Technology, Kolkata, West Bengal, India

    Siddhartha Bhattacharyya

  2. Department of Electrical Engineering, Indian Institute of Technology Delhi, New Delhi, Delhi, India

    Tapan Gandhi

  3. Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology, Rangpo, Sikkim, India

    Kalpana Sharma

  4. Department of Computer and System Sciences, Visva-Bharati University, Santiniketan, West Bengal, India

    Paramartha Dutta

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Marchon, N., Naik, G. (2018). Assessment of the Fetal Health Using NI-aECG. In: Bhattacharyya, S., Gandhi, T., Sharma, K., Dutta, P. (eds) Advanced Computational and Communication Paradigms. Lecture Notes in Electrical Engineering, vol 475. Springer, Singapore. https://doi.org/10.1007/978-981-10-8240-5_40

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  • DOI: https://doi.org/10.1007/978-981-10-8240-5_40

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8239-9

  • Online ISBN: 978-981-10-8240-5

  • eBook Packages: EngineeringEngineering (R0)

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