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Design and Implementation of Biomedical Device for Monitoring Fetal ECG

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Computational Vision and Bio-Inspired Computing ( ICCVBIC 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1108))

Abstract

Heart disease is one of the critical diseases and World Health Organization (WHO) shows that large parentage of people is dying due to heart disease. But, the timely and accurate monitoring of heart disease still remains as a challenging problem. This paper proposes a portable biomedical device for monitoring fetal ECG signal from the abdominal signal and analysis of the fetal heart rate variability (FHR) to ensure the fetal wellbeing. The portable device for monitoring FECG was implemented using Arduino and AD8232 ECG sensor module. In this work, Fetal ECG extraction is done with a single composite maternal ECG signal. The ECG signal is processed using Wavelet transform for fetal ECG signal extraction. The experimentally observed results show the better extraction of FECG and that could lead towards the appropriate analysis of heart disease.

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References

  1. Jezewski, J., Kupka, T., Horoba, K., Czabanski, R., Wrobel, J.: A problem of maternal and fetal QRS complexes overlapping in Fetal heart rate estimation. In: Fujita, H., Sasaki, J. (eds.) Selected Topics in Applied Computer Science. Applied Computer Science Series, pp. 122–127. WSEAS Press, Athens (2010)

    Google Scholar 

  2. Jezewski, J., Horoba, K., Wróbel, J., Matonia, A., Kupka, T.: Adapting new bedside instrumentation for computer-aided fetal monitoring using efficient tools for system reconfiguration. In: Mastorakis, N., Mladenov, V. (eds.) Recent Advances in Computers, Computing and Communications, pp. 80–85. WSEAS Press, Greace (2002)

    Google Scholar 

  3. De Haan, J., van Bemmel, J.H., Versteeg, B., Veth, A.F.L., Stolte, L.A.M., Janssens, J., Eskes, T.K.A.B.: Quantitative evaluation of fetal heart rate patterns I. processing methods. Eur. J. Obstet. Gynecol. 3, 95–102 (1971)

    Article  Google Scholar 

  4. Hon, E.H.: Instrumentation of fetal heart rate and fetal electrocardiography II a vaginal electrode. Am. J. Obstet. Gynecol. 86, 772–778 (1963)

    Article  Google Scholar 

  5. Yakut, O., Solak, S., Bolat, E.D.: Implementation of a web-based wireless ECG measuring and recording system. In: 17th International Conference on Medical Physics and Medical Sciences, Istanbul, vol. 9, no. 10, pp. 815–818 (2015)

    Google Scholar 

  6. Lin, B.-S., Wong, A.M., Tseng, K.C.: Community based ECG monitoring system for patients with cardiovascular diseases. J. Med. Syst. 40(4), 1–12 (2016)

    Google Scholar 

  7. Spanò, E., Di Pascoli, S., Iannaccone, G.: Lowpower wearable ECG monitoring system for multiple-patient remote monitoring. IEEE Sens. J. 16(13), 5452–5462 (2016)

    Article  Google Scholar 

  8. Kupka, T., Jezewski, J., Matonia, A., Wrobel, J., Horoba, K.: Coincidence of maternal and fetal QRS complexes in view of fetal heart rate determination. J. Med. Inform. Techonol. 4, 49–55 (2002)

    Google Scholar 

  9. Ibrahimy, M.I., Reaz, M.B.I., Mohd Ali, M.A., Khoon, T.H., Ismail, A.F.: Development of an efficient algorithm for fetal heart rate detection: a hardware approach. In: Proceedings of the 5th WSEAS International Conference on Instrumentation, Measurement, Circuits and Systems, China, pp. 12–17, April 16–18 (2006)

    Google Scholar 

  10. Ibrahimy, M.I., Reaz, M.B.I., Ali, M.A.M., Khoon, T.H., Ismail, A.F.: Hardware realization of an efficient fetal QRS complex detection algorithm. WSEAS Trans. Circ. Syst. 5(4), 575–581 (2006)

    Google Scholar 

  11. Jeżewski, M., Czabański, R., Roj, D., Kupka, T.: Influence of input data modification of neural networks applied to the fetal outcome classification. In: Mastorakis, N., Mladenow, V. (eds.) Latest Trends on Computers. Recent Advantage in Computer Engineering Series, pp. 202–207. WSEAS Press, Athens (2010)

    Google Scholar 

  12. Yeh, S.Y., Forsythe, A., Hon, E.H.: Quantification of fetal heart rate beat-to-beat interval differences. J. Obstet. Gynecol. 41, 355–363 (1973)

    Google Scholar 

  13. Yuan, L., Zhou, Z., Yuan, Y., Wu, S.: An improved FastICA method for fetal ECG extraction. Comput. Math. Meth. Med. 2018, 7061456 (2018). https://doi.org/10.1155/2018/7061456

    Article  MathSciNet  MATH  Google Scholar 

  14. Haq, T.M.: Extraction of fetal heart rate from maternal ECG—non invasive approach for continuous monitoring during labor. MDPI Proc. 2(13), 1009 (2018). https://doi.org/10.3390/proceedings2131009

    Article  Google Scholar 

  15. Mariappan, R., Ramasubramanian, M.: Experimental investigation of impact of meditation yoga on mental and physical health parameters using EEG, Springer Briefers on Applied Sciences & Tech, January 2018 (2018)

    Google Scholar 

  16. Gupta, N.: Evaluation of noise cancellation using LMS And NLMS algorithm. Int. J. Sci Tech. Res. 5(04), 69–72 (2016)

    Google Scholar 

  17. Mariappan, R., Ramasubramanian, M.: Design and Implementation of Cognitive Radio Sensor Network for Emergency Communication Using Discrete Wavelet Packet Transform Technique, Springer – LNCS – ISSN: 0302-9743, vol. 11319, January 2019 (2019)

    Google Scholar 

  18. Karthikeyan, C., Ramadoss, B.: Non linear fusion technique based on dual tree complex wavelet transform. Int. J. Appl. Eng. Res. 9(22), 13375–13385 (2014)

    Google Scholar 

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Correspondence to Rama Subramanian .

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✓ No humans/animals involved in this research work.

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Subramanian, R., Karthikeyan, C., Siva Nageswara Rao, G., Mariappan, R. (2020). Design and Implementation of Biomedical Device for Monitoring Fetal ECG. In: Smys, S., Tavares, J., Balas, V., Iliyasu, A. (eds) Computational Vision and Bio-Inspired Computing. ICCVBIC 2019. Advances in Intelligent Systems and Computing, vol 1108. Springer, Cham. https://doi.org/10.1007/978-3-030-37218-7_82

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