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Recovery of signal loss adopting the residual bootstrap method in fetal heart rate dynamics

  • Sun-Kyung Lee , Young-Sun Park and Kyung-Joon Cha EMAIL logo
Published/Copyright: March 19, 2018
Biomedical Engineering / Biomedizinische Technik
From the journal Biomedical Engineering / Biomedizinische Technik Volume 64 Issue 2

Abstract

Fetal heart rate (FHR) data obtained from a non-stress test (NST) can be presented in a type of time series, which is accompanied by signal loss due to physical and biological causes. To recover or estimate FHR data, which is subjected to a high rate of signal loss, time series models [second-order autoregressive (AR(2)), first-order autoregressive conditional heteroscedasticity (ARCH(1)) and empirical mode decomposition and vector autoregressive (EMD-VAR)] and the residual bootstrap method were applied. The ARCH(1) model with the residual bootstrap technique was the most accurate [root mean square error (RMSE), 2.065] as it reflects the nonlinearity of the FHR data [mean absolute error (MAE) for approximate entropy (ApEn), 0.081]. As a result, the goal of predicting fetal health and identifying a high-risk pregnancy could be achieved. These trials may be effectively used to save the time and cost of repeating the NST when the fetal diagnosis is impossible owing to a large amount of signal loss.

Keywords: fetal heart rate; nonlinear dynamics; residual bootstrap; signal loss

  1. Funding: This research was supported by the Bio & Medical Technology Development Program of the National Research Foundation (NRF) funded by the Ministry of Science & ICT (No. 2017M3A9G8084539).

References

[1] Acharya UR, Joseph KP, Kannathal N, Lim CM, Suri JS. Heart rate variability: a review. Med Biol Eng Comput 2006; 44: 1031–1051.10.1007/s11517-006-0119-0Search in Google Scholar PubMed

[2] Cheng C, Sa-Ngasoongsong A, Beyca O, et al. Time series forecasting for nonlinear and non-stationary processes: a review and comparative study. IIE Trans 2015; 47: 1053–1071.10.1080/0740817X.2014.999180Search in Google Scholar

[3] Dampney RAL, Coleman MJ, Fontes MAP, et al. Central mechanisms underlying short-and long-term regulation of the cardiovascular system. Clin Exp Pharmacol Physiol 2002; 29: 261–268.10.1046/j.1440-1681.2002.03640.xSearch in Google Scholar PubMed

[4] Efron B, Tibshirani RJ. An introduction to the bootstrap. New York: CRC Press 1994.10.1201/9780429246593Search in Google Scholar

[5] Frank B, Frasch MG, Schneider U, Roedel M, Schwab M, Hoyer D. Complexity of heart rate fluctuations in near-term sheep and human fetuses during sleep. Biomed Tech 2006; 51: 233–236.10.1515/BMT.2006.044Search in Google Scholar PubMed

[6] Gonçalves H, Rocha AP, Ayres-de-Campos D, Bernardes J. Internal versus external intrapartum foetal heart rate monitoring: the effect on linear and nonlinear parameters. Physiol Meas 2006; 27: 307–319.10.1088/0967-3334/27/3/008Search in Google Scholar PubMed

[7] Jarisch W, Detwiler JS. Statistical modeling of fetal heart rate variability. IEEE T Bio-med Eng 1980; 27: 582–589.10.1109/TBME.1980.326580Search in Google Scholar PubMed

[8] Krupa N, Ali M, Zahedi E, Ahmed S, Hassan FM. Antepartum fetal heart rate feature extraction and classification using empirical mode decomposition and support vector machine. Biomed Eng Online 2011; 10: 6.10.1186/1475-925X-10-6Search in Google Scholar PubMed PubMed Central

[9] Park YS, Ryu KY, Shim SS, Hoh JK, Park MI. Comparison of fetal heart rate patterns using nonlinear dynamics in breech versus cephalic presentation at term. Early Hum Dev 2013; 89: 101–106.10.1016/j.earlhumdev.2012.08.006Search in Google Scholar PubMed

[10] Pincus SM, Viscarello RR. Approximate entropy: a regularity measure for fetal heart rate analysis. Obstet Gynecol 1992; 79: 249–255.Search in Google Scholar

[11] Politis DN. The impact of bootstrap methods on time series analysis. Stat Sci 2003; 18: 219–230.10.1214/ss/1063994977Search in Google Scholar

[12] Signorini MG, Magenes G, Cerutti S, Arduini D. Linear and nonlinear parameters for the analysis of fetal heart rate signal from cardiotocographic recordings. IEEE T Bio-med Eng 2003; 50: 365–374.10.1109/TBME.2003.808824Search in Google Scholar PubMed

[13] Spilka J, Chudacek V, Koucky M, et al. Using nonlinear features for fetal heart rate classification. Biomed Signal Process Control 2012; 7: 350–357.10.1016/j.bspc.2011.06.008Search in Google Scholar

[14] Van Leeuwen P, Cysarz D, Lange S, Gronemeyer D. Increase in regularity of fetal heart rate variability with age. Biomed Tech 2006; 51: 244–247.10.1515/BMT.2006.047Search in Google Scholar PubMed

Received: 2017-06-26
Accepted: 2017-10-04
Published Online: 2018-03-19
Published in Print: 2019-04-24

©2019 Walter de Gruyter GmbH, Berlin/Boston

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https://doi.org/10.1515/bmt-2017-0203
Keywords for this article
fetal heart rate; nonlinear dynamics; residual bootstrap; signal loss

Articles in the same Issue

  1. Frontmatter
  2. Review
  3. The peripheral cannulas in extracorporeal life support
  4. Research articles
  5. Determination of optimal positive end-expiratory pressure based on respiratory compliance and electrical impedance tomography: a pilot clinical comparative trial
  6. Simulation of personalised haemodynamics by various mounting positions of a prosthetic valve using computational fluid dynamics
  7. Recovery of signal loss adopting the residual bootstrap method in fetal heart rate dynamics
  8. Optimal level and order detection in wavelet decomposition for PCG signal denoising
  9. Simple gastric motility assessment method with a single-channel electrogastrogram
  10. Analysis of on-surface and in-air movement in handwriting of subjects with Parkinson’s disease and atypical parkinsonism
  11. Wavelet-enhanced convolutional neural network: a new idea in a deep learning paradigm
  12. Digital microscopic evaluation of vertical marginal discrepancies of CAD/CAM fabricated zirconia cores
  13. Modelling the degree of porosity of the ceramic surface intended for implants
  14. How Hedstrom files fail during clinical use? A retrieval study based on SEM, optical microscopy and micro-XCT analysis
  15. A novel measurement strategy to evaluate the human head as a transition medium for inductive ear-to-ear communication
  16. Short communication
  17. Force plates may be used for dynamic analyses of endoprostheses explantation procedures
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