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Abstrakty
A correctly estimated component of fetal heart rate signal (FHR) – so called baseline – is a precondition for proper recognition of acceleration and deceleration patterns. A number of various algorithms for estimating the FHR baseline was proposed so far. However, there is no reference standard enabling their objective evaluation, and thus no methodology of comparing the different algorithms still exists. In this paper we propose a method for evaluation of automatically determined baseline in reference to a set of experts, based on ten separate groups of signals comprising typical variability patterns observed in the fetal heart rate. As it was proposed earlier [1], the given algorithm is evaluated based on the characteristic patterns detected using the obtained baseline, instead of direct analysis of the baseline shape. For the purpose of quantitative assessment of the estimated baseline a new synthetic inconsistency coefficient was applied. The proposed methodology enabled to evaluate eleven well-known algorithms. We believe that the method will be a valuable tool for assessment of the existing algorithms, as well as for developing the new ones.
Wydawca
Czasopismo
Rocznik
Tom
Strony
562--573
Opis fizyczny
Bibliogr. 40 poz., rys., tab., wykr.
Twórcy
autor
- Institute of Medical Technology and Equipment ITAM, Roosevelta 118, 41-800 Zabrze, Poland
autor
- Institute of Medical Technology and Equipment ITAM, Roosevelta 118, 41-800 Zabrze, Poland
autor
- Institute of Medical Technology and Equipment ITAM, Roosevelta 118, 41-800 Zabrze, Poland
autor
- Institute of Medical Technology and Equipment ITAM, Roosevelta 118, 41-800 Zabrze, Poland
autor
- Institute of Medical Technology and Equipment ITAM, Roosevelta 118, 41-800 Zabrze, Poland
autor
- Institute of Medical Technology and Equipment ITAM, Roosevelta 118, 41-800 Zabrze, Poland
Bibliografia
- [1] Jezewski J, Horoba K, Matonia A. Baseline and acceleration episodes – clinically significant nonstationarities in FHR signal: Part II. Indirect comparison. In: Kurzynski M, editor. Computer recognition systems, vol. 30. Springer Verlag; 2005. p. 535–42.
- [2] Kupka T, Jezewski J, Matonia A, Horoba K, Wrobel J. Timing events in Doppler ultrasound signal of fetal heart activity. Proc. 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society; 2004. pp. 337–40.
- [3] Wrobel J, Jezewski J, Horoba K, Pawlak A, Czabanski R, Jezewski M, et al. Medical cyber-physical system for home telecare of high-risk pregnancy – design challenges and requirements. J Med Imag Health Inf 2015;5(6):1295–301.
- [4] Jezewski J, Roj D, Wrobel J, Horoba K. A novel technique for fetal heart rate estimation from Doppler ultrasound signal. Biomed Eng Online 2011;10:1–17. Article no. 92.
- [5] Nidhal S, Mohd-Ali M, Zaidan A, Zaidan B, Najah H. Computerized algorithm for fetal heart rate baseline and baseline variability estimation based on distance between signal average and alpha value. Int J Pharmacol 2011;7: 228–37.
- [6] Das S, Roy K, Saha CK. A novel approach for extraction and analysis of variability of baseline. 2011 International Conference on Recent Trends in Information Systems. 2011. pp. 336–9.
- [7] Breborowicz G, Moczko J. Mathematical analysis of cardiotocographic recording of fetal heart activity. Ginekol Pol 1980;51(9):795–800 [in Polish].
- [8] Jimenez L, Gonzalez R, Gaitan M, Carrasco S, Vargas C. Computerized algorithm for baseline estimation of fetal heart rate. Comput Cardiol Memphis 2002;29:477–80.
- [9] Wrobel J, Roj D, Jezewski J, Horoba K, Kupka T, Jezewski M. Evaluation of the robustness of fetal heart rate variability measures to low signal quality. J Med Imag Health Inf 2015;5 (6):1311–8.
- [10] Rooth G. Guidelines for the use of fetal monitoring. Int J Gynaecol Obstet 1987;25:159–67.
- [11] Lu Y, Li X, Wei S, Liu X. Fetal heart rate baseline estimation with analysis of fetal movement signal. Bio-Med Mater Eng 2014;24:3763–9.
- [12] Jezewski M, Czabanski R, Wrobel J, Horoba K. Analysis of extracted cardiotocographic signal features to improve automated prediction of fetal outcome. Biocybern Biomed Eng 2010;30:39–47.
- [13] Czabanski R, Jezewski J, Horoba K, Jezewski M. Fetal state assessment using fuzzy analysis of the fetal heart rate signals – agreement with the neonatal outcome. Biocybern Biomed Eng 2013;33(3):145–55.
- [14] Chourasia VS, Tiwari AK. A review and comparative analysis of recent advancements in fetal monitoring techniques. Crit Rev Biomed Eng 2008;36(5–6):335–73.
- [15] Jezewski M, Wrobel J, Labaj P, Leski J, Henzel N, Horoba K, Jezewski J. Some practical remarks on neural networks approach to fetal cardiotocograms classification. Proc. 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society; 2007. pp. 5170–3.
- [16] Pander T. New polynomial approach to myriad filter computation. Signal Process 2010;90:1991–2001.
- [17] Ayres-de-Campos D, Bernardes J, Marsal K, Nickelsen C, Makarainen L, Banfield P, et al. Can the reproducibility of fetal heart rate baseline estimation be improved? Eur J Obstet Gynecol Reprod Biol 2004;112:49–54.
- [18] Chudacek V, Spilka J, Bursa M, Janku P, Hruban L, Huptych M, et al. Open access intrapartum CTG database. BMC Pregn Childbirth 2014;14(16). 12 pp., http://www.biomedcentral.com/1471-2393/14/16.
- [19] Jezewski J, Wrobel J, Kupka T. Baseline and acceleration episodes – clinically significant nonstationarities in FHR Signal: Part I. Coefficients of inconsistency. In: Kurzynski M, editor. Computer recognition systems, vol. 30. Springer Verlag; 2005. p. 527–34.
- [20] Costa M, Ayres-de-Campos D, Machadao A, Santos C, Bernardes J. Comparison of computer system evaluation of intrapartum cardiotocographic events and a consensus of clinicians. J Perinat Med 2010;38:191–5.
- [21] Hruban L, Spilka J, Chudacek V, Janku P. Agreement on CTG intrapartum recordings between expert-obstetricians. J Eval Clin Pract 2015;9.
- [22] Marques-de-Sa J, Reis L, Lau J, Bernardes J. Estimation and classification of fetal heart rate baselines using artificial neural networks. Comput Cardiol Bethesda 1994;21: 541–4.
- [23] Lu Y, Wei S. Nonlinear baseline estimation of FHR signal using empirical mode decomposition. IEEE 11th International Conference on Signal Processing (ICSP); 2012. pp. 1645–9.
- [24] Moslem B, Mohydeen A, Bazzi O. Monitoring the fetal heart rate variability during labor. Proc. 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society; 2015. pp. 5846–50.
- [25] Jezewski J, Horoba K, Wrobel J, Gacek A. Inconsistency in evaluation of clinical patterns in fetal heart rate waveforms. J Med Inf Technol 2002;4:27–35.
- [26] Chudacek V, Spilka J, Lhotska L, Janku P, Koucky M, Huptych M, et al. Assessment of features for automatic CTG analysis based on expert annotation. 33rd Annual International Conference of the IEEE EMBS Boston; 2011. pp. 6051–4.
- [27] Dalton KJ, Dawson AJ. Baseline: a computer method of calculating baseline in fetal heart rate recordings. Int J Biomed Comput 1984;15:311–7.
- [28] Dawes GS, Moulden M, Redman CWG. System 8000: computerized antenatal FHR analysis. J Perinat Med 1991;19:47–51.
- [29] Dawes G, Houghton C. Baseline in human fetal heart rate records. Br J Obstet Gynaecol 1982;89:270–5.
- [30] Van Alphen M, Wagenvoort AM, Van Geijn HP. Quantitative intrapartum CTG analysis. In: Cosmi EV, Di Renzo GC, editors. Current progress in perinatal medicine. Parthenon Publishing Group; 1994. p. 805–11.
- [31] Mantel R, Ververs I, Colenbrander GJ, Van Geijn HP. Automated antepartum baseline FHR determination and detection of accelerations and decelerations. In: van Geijn HP, Copray FJA, editors. A critical appraisal of fetal surveillance. Elsevier Science B.V.; 1994. p. 333–48.
- [32] Jezewski J, Wrobel J. Global baseline determination in fetal heart rate records with the identification of local prominent rates. Proc. 1st Int. Conf. on Medical Physics and Biomedical Engineering, vol. 2; 1994. pp. 365–9.
- [33] Bernardes J, Ayres-De-Campos D, Moura C, Marques De-Sa J. Computer recognition of fetal heart rate patterns by the Porto system. Proc. 2nd World Congress of Perinatal Medicine; 1993. pp. 559–64.
- [34] Bernardes J, Costa-Pereira A, van-Geijn H, Pereira-Leite L. A more objective fetal heart rate baseline estimation. Br J Obstet Gynaecol 1996;103:714–5.
- [35] Arduini D, Rizzo G, Giannini F, Garzetti G, Romanini C. Computerized analysis of fetal heart rate: II. Comparison with the interpretation of experts. J Matern Fetal Invest 1993;3:165–8.
- [36] Arduini D, Rizzo G, Piana G, Bonalumi A, Brambilla P, Romanini C. Computerized analysis of fetal heart rate: I. Description of the system (2CTG). J Matern Fetal Invest 1993;3:159–63.
- [37] Searle JR, Devoe LD, Phillips MC. Computerized analysis of resting fetal heart rate tracings. Obstet Gynecol 1988;71:407–11.
- [38] Aeyels B, Van Der Perre G, Pello L, Van Assche A, Spitz B. On-line processing of perinatal fetal heart rate and intra-uterine pressure. Proc. of the 14th IEEE/EMBS Conf.; 1992. pp. 2728–9.
- [39] Wrobel J, Horoba K, Pander T, Jezewski J, Czabanski R. Improving the fetal heart rate signal interpretation by application of myriad filtering. Biocybern Biomed Eng 2013;33:211–21.
- [40] Mongelli M, Dawkins R, Chung T, Sahota D, Spencer JA, Chang AM. Computerised estimation of the baseline fetal heart rate in labour: the low frequency line. Br J Obstet Gynaecol 1997;104:1128–33.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-dfa58b2a-45ef-460d-81ea-5bcba85f43c6