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Comparison of real beat-to-beat signals with commercially available 4 Hz sampling on the evaluation of foetal heart rate variability

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Abstract

Evaluation of foetal heart rate (FHR) variability is an essential part of foetal monitoring, but a precise quantification of this parameter depends on the quality of the signal. In this study, we compared real FHR beat-to-beat signals with 4 Hz sampling provided by commercial foetal monitors on linear and nonlinear indices and analysed their clinical implications. Simultaneous acquisition of beat-to-beat signals and their 4 Hz sampling rate counterparts was performed using a scalp electrode, during the last hour of labour in 21 fetuses born with an umbilical artery blood (UAB) pH ≥ 7.20 and 6 born with an UAB pH < 7.20. For each case, the first and last 10 min segments were analysed, using time and frequency domain linear, and nonlinear FHR indices, namely mean FHR, low frequency, high frequency, approximate, sample and multiscale entropy. Significant differences in variability indices were found between beat-to-beat and 4 Hz sampled signals, with a lesser effect seen with 2 Hz sampling. These differences did not affect physiological changes observed during labour progression, such as decreased entropy and linear time domain indices, and increased frequency domain indices. However, significant differences were found in the discrimination between fetuses born with different UAB pHs, with beat-to-beat sampling providing better results in linear indices and 4 Hz sampling better results in entropy indices. In conclusion, different FHR sampling frequencies can significantly affect the quantification of variability indices. This needs to be taken into account in the interpretation of FHR variability and in the development of new equipment.

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References

  1. American College of Obstetricians and Gynecologists (2005) ACOG Practice Bulletin. Clinical Management Guidelines for Obstetrician-Gynecologists, Number 70, December 2005. Obstet Gynecol 106:1453–1460

    Article  Google Scholar 

  2. Ayres-de-Campos D, Bernardes J, Reynolds A, Saraiva JP, Santos C, Pereira-Leite L (2000) Computer evaluation of internal versus external FHR monitoring in the minutes preceding delivery. Int J Gynecol Obstet 70:B60–B61

    Article  Google Scholar 

  3. Ayres-de-Campos D, Santos C, Bernardes J (2005) Prediction of neonatal state by computer analysis of fetal heart rate tracings: the antepartum arm of the SisPorto® multicentre validation study. Eur J Obstet Gynecol Reprod Biol 118:52–60

    Article  PubMed  Google Scholar 

  4. Ayres-de-Campos D, Sousa P, Costa A, Bernardes J (2008) Omniview-SisPorto 3.5—a central fetal monitoring station with online alerts based on computerized cardiotocogram+ ST event analysis. J Perinat Med 36:260–264

    Article  PubMed  Google Scholar 

  5. Bernardes J, Moura C, de Sá JPM, Pereira-Leite L (1991) The Porto system for automated cardiotocographic signal analysis. J Perinat Med 19:61–65

    Article  PubMed  CAS  Google Scholar 

  6. Bernardes J, Garrido A (1995) Computerized fetal heart rate analysis in labour based on 2-s sampling. Can it proceed with confidence? Eur J Obstet Gynecol Reprod Biol 63:105–107

    Article  PubMed  CAS  Google Scholar 

  7. Bernardes J, Costa-Pereira A (1997) The effect of different sampling intervals on the measurement of intrapartum fetal heart rate variability. Obstet Gynecol 90:318–319

    Article  PubMed  CAS  Google Scholar 

  8. Bernardes J, Ayres-de-Campos D, Costa-Pereira A, Pereira-Leite L, Garrido A (1998) Objective computerized fetal heart rate analysis. Int J Gynecol Obstet 62:141–147

    Article  CAS  Google Scholar 

  9. Bernardes J, Ayres-de-Campos D (2010) The persistent challenge of fetal heart rate monitoring. Curr Opin Obstet Gynecol 22:104–109

    Article  PubMed  Google Scholar 

  10. Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1:307–310

    Article  PubMed  CAS  Google Scholar 

  11. Boog G (2004) Analyse informatisée du rythme cardiaque foetal au cours de la grosssesse et de l’accouchement. EMC-Gynécologie Obstétrique 1:7–21 (publication in French)

    Article  Google Scholar 

  12. Boos A, Jagger MH, Paret GW, Hausmann JW (1995) A new, lightweight fetal telemetry system. Hewlett-Packard J 46(6):82–93

    Google Scholar 

  13. Carter MC (1993) Signal processing and display—cardiotocographs. Br J Obstet Gynecol 100:21–23

    Google Scholar 

  14. Chang A, Sahota DS, Reed NN, James DK, Mohajer MP (1995) Computerised fetal heart rate analysis in labour-effect of sampling rate. Eur J Obstet Gynecol Reprod Biol 59:125–129

    Article  PubMed  CAS  Google Scholar 

  15. Costa A, Ayres-de-Campos D, Costa F, Santos C, Bernardes J (2009) Prediction of neonatal acidemia by computer analysis of fetal heart rate and ST event signals. Am J Obstet Gynecol 201:464.e1–464.e6

    Article  Google Scholar 

  16. Costa M, Goldberger AL, Peng CK (2002) Multiscale entropy analysis of complex physiologic time series. Phys Rev Lett 89(6):068102

    Article  PubMed  Google Scholar 

  17. Costa M, Goldberger AL, Peng CK (2005) Multiscale entropy analysis of biological signals. Phys Rev E 71:021906

    Article  Google Scholar 

  18. Costa-Santos C, Antunes L, Souto A, Bernardes J (2010) Assessment of disagreement: a new information-based approach. Ann Epidemiol 20:555–561

    Article  PubMed  Google Scholar 

  19. Dawes GS, Moulden M, Redman CW (1990) Criteria for the design of fetal heart rate analysis systems. Int J Biomed Comput 25:287–294

    Article  PubMed  CAS  Google Scholar 

  20. Dawes G (1994) Computerized fetal heart rate analysis. In: van Geijn HP, Copray FJA (eds) A critical appraisal of fetal surveillance. Elsevier Science, Amsterdam, pp 311–314

    Google Scholar 

  21. Devoe L, Golde S, Kilman Y, Morton D, Shea K, Waller J (2000) A comparison of visual analyses of intrapartum fetal heart rate tracings according to the new National Institute of Child Health and Human Development guidelines with computer analyses by an automated fetal heart rate monitoring system. Am J Obstet Gynecol 183:361–366

    Article  PubMed  CAS  Google Scholar 

  22. Fukushima T, Flores CA, Hon EH, Davidson ECJr (1985) Limitations of autocorrelation in fetal heart rate monitoring. Am J Obstet Gynecol 153:685–692

    PubMed  CAS  Google Scholar 

  23. Fusheng Y, Bo H, Qingyu T (1998) Approximate entropy and its application in biosignal analysis. In: Akay M (ed) Nonlinear biomedical signal processing—volume II: dynamical analysis and modelling. IEEE Press, New York, pp 72–91

    Google Scholar 

  24. García-González MA, Fernández-Chimeno M, Ramos-Castro J (2009) Errors in the estimation of approximate entropy and other recurrence-plot-derived indices due to the finite resolution of RR time series. IEEE Trans Biomed Eng 56(2):345–351

    Article  PubMed  Google Scholar 

  25. Georgoulas G, Stylios CD, Groumpos PP (2006) Predicting the risk of metabolic acidosis for newborns based on fetal heart rate signal classification using support vector machines. IEEE Trans Biomed Eng 53:875–884

    Article  PubMed  Google Scholar 

  26. Gonçalves H, Rocha AP, Ayres-de-Campos D, Bernardes J (2006) Internal versus external intrapartum foetal heart rate monitoring: effect on linear and nonlinear parameters. Physiol Meas 27:307–319

    Article  PubMed  Google Scholar 

  27. Gonçalves H, Rocha AP, Ayres-de-Campos D, Bernardes J (2006) Linear and nonlinear fetal heart rate analysis of normal and acidemic fetuses in the minutes preceding delivery. Med Biol Eng Comput 44:847–855

    Article  PubMed  Google Scholar 

  28. Gonçalves H, Bernardes J, Rocha AP, Ayres-de-Campos D (2007) Linear and nonlinear analysis of heart rate patterns associated with fetal behavioral states in the antepartum period. Early Hum Dev 83:585–591

    Article  PubMed  Google Scholar 

  29. Govindan RB, Wilson JD, Eswaran H, Lowery CL, Preissl HP (2007) Revisiting sample entropy analysis. Phys A Stat Mech Appl 376:158–164

    Article  Google Scholar 

  30. Hewlett-Packard Series 50 Service Manual, M1351A and 1353A, Hewlett-Packard, Germany (1993)

  31. Keith RDF, Beckley S, Garibaldi JM, Westgate JA, Ifeachor E, Greene KR (1995) A multicentre comparative study of 17 experts and an intelligent computer system for managing labour using the cardiotocogram. Br J Obstet Gynecol 102:688–700

    Article  CAS  Google Scholar 

  32. Lawson GW, Belcher R, Dawes GS, Redman CW (1983) A comparison of ultrasound (with autocorrelation) and direct electrocardiogram fetal heart rate detector systems. Am J Obstet Gynecol 147:721–722

    PubMed  CAS  Google Scholar 

  33. Lu S, Chen X, Kanters JK, Solomon IC, Chon KH (2008) Automatic selection of the threshold value r for approximate entropy. IEEE Trans Biomed Eng 55(8):1966–1972

    Article  PubMed  Google Scholar 

  34. Martinez WL, Martinez AR (2002) Computational statistics handbook with MATLAB. CRC Press, Boca Raton

    Google Scholar 

  35. Pincus S (1991) Approximate entropy as a measure of system complexity. Proc Natl Acad Sci USA 88:2297–2301

    Article  PubMed  CAS  Google Scholar 

  36. Pincus S, Viscarello R (1992) Approximate entropy: a regularity measure for fetal heart rate analysis. Obstet Gynecol 79:249–255

    PubMed  CAS  Google Scholar 

  37. Richman JS, Moorman JR (2000) Physiological time-series analysis using approximate entropy and sample entropy. Am J Physiol Heart Circ Physiol 278:H2039–H2049

    PubMed  CAS  Google Scholar 

  38. Richman JS (2007) Sample entropy statistics and testing for order in complex physiological signals. Commun Stat Theory Methods 36:1005–1019

    Article  Google Scholar 

  39. Salamalekis E, Thomopoulos P, Giannaris D, Salloum I, Vasios G, Prentza A, Koutsouris D (2002) Computerised intrapartum diagnosis of fetal hypoxia based on fetal heart rate monitoring and fetal pulse oximetry recordings utilising wavelet analysis and neural networks. Br J Obstet Gynecol 109:1137–1142

    Article  CAS  Google Scholar 

  40. Signorini MG, Magenes G, Cerutti S, Arduini D (2003) Linear and nonlinear parameters for the analysis of fetal heart rate signal from cardiotocographic recordings. IEEE Trans Biomed Eng 50(3):365–374

    Article  PubMed  Google Scholar 

  41. STAN Service Manual, Neoventa, Sweden 2005

  42. Suzuki T, Okamura K, Kimura Y, Watanabe T, Yaegashi N, Murotsuki J, Uehara S, Yajima A (2000) Power spectral analysis of R–R interval variability before and during the sinusoidal heart rate pattern in fetal lambs. Am J Obstet Gynecol 182:1227–1232

    Article  PubMed  CAS  Google Scholar 

  43. Task force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology (1996) Task force heart rate variability: standards of measurement, physiological interpretation and clinical use. Circulation 93(5):1043–1065

    Article  Google Scholar 

  44. Wilcox MA, Wang W, Sahota DS, Dawkins RR, Chung TK, Chang AM (1997) The effect of different sampling intervals on the measurement of intrapartum fetal heart rate variability. Obstet Gynecol 89:577–580

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

Hernâni Gonçalves is funded by post-doctoral grant from the Fundação para a Ciência e a Tecnologia, Portugal (FCT: SFRH/BPD/69671/2010). The authors would also like to acknowledge project POSI/CPS/40153/2001, also funded by FCT. Finally, we would like to thank Prof. Karl Rosen for his invaluable information regarding the STAN® 21 monitor characteristics.

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Authors and Affiliations

  1. Center for Research in Health Technologies and Information Systems (CINTESIS), Faculty of Medicine, University of Porto, Al. Prof. Hernâni Monteiro, 4200-319, Porto, Portugal

    Hernâni Gonçalves, Diogo Ayres-de-Campos, Cristina Costa-Santos & João Bernardes

  2. Department of Obstetrics and Gynecology, Faculty of Medicine, University of Porto, Al. Prof. Hernâni Monteiro, 4200-319, Porto, Portugal

    Antónia Costa, Diogo Ayres-de-Campos & João Bernardes

  3. Department of Obstetrics and Gynecology, Hospital São João, Al. Prof. Hernâni Monteiro, 4200-319, Porto, Portugal

    Antónia Costa, Diogo Ayres-de-Campos & João Bernardes

  4. Instituto de Engenharia Biomédica (INEB), Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Antónia Costa, Diogo Ayres-de-Campos & João Bernardes

  5. Departamento de Matemática, Faculdade de Ciências, Universidade do Porto, Rua do Campo Alegre s/n, 4169-007, Porto, Portugal

    Ana Paula Rocha

  6. Centro de Matemática da Universidade do Porto, Rua do Campo Alegre, s/n, 4169-007, Porto, Portugal

    Ana Paula Rocha

Authors
  1. Hernâni Gonçalves
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  2. Antónia Costa
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  3. Diogo Ayres-de-Campos
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  4. Cristina Costa-Santos
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  5. Ana Paula Rocha
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  6. João Bernardes
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Correspondence to Hernâni Gonçalves.

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Gonçalves, H., Costa, A., Ayres-de-Campos, D. et al. Comparison of real beat-to-beat signals with commercially available 4 Hz sampling on the evaluation of foetal heart rate variability. Med Biol Eng Comput 51, 665–676 (2013). https://doi.org/10.1007/s11517-013-1036-7

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  • DOI: https://doi.org/10.1007/s11517-013-1036-7

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