An Algorithm for Correcting Fetal Heart Rate Baseline_Journal of Biomedical Engineering

Authors：

LIXiaodong ,  LUYaosheng

Department of Electronic Engineering, College of Information Science and Technology, Jinan University, Guangzhou 510632, China;

Corresponding author：

LUYaosheng, Email: tluys@jnu.edu.cn

Keywords：

fetal heart rate; baseline correction; smoothing

DOI：

10.7507/1001-5515.20150196

Video：

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Abstract Full text Figures/Tables Video References Cited by

Fetal heart rate (FHR) baseline estimation is of significance for the computerized analysis of fetal heart rate and the assessment of fetal state. In our work, a fetal heart rate baseline correction algorithm was presented to make the existing baseline more accurate and fit to the tracings. Firstly, the deviation of the existing FHR baseline was found and corrected. And then a new baseline was obtained finally after treatment with some smoothing methods. To assess the performance of FHR baseline correction algorithm, a new FHR baseline estimation algorithm that combined baseline estimation algorithm and the baseline correction algorithm was compared with two existing FHR baseline estimation algorithms. The results showed that the new FHR baseline estimation algorithm did well in both accuracy and efficiency. And the results also proved the effectiveness of the FHR baseline correction algorithm.

Citation： LIXiaodong, LUYaosheng. An Algorithm for Correcting Fetal Heart Rate Baseline. Journal of Biomedical Engineering, 2015, 32(5): 1106-1112. doi: 10.7507/1001-5515.20150196 Copy

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6.	MANTEL R, VAN GEIJN H P, CARON F J M, et al. Computer analysis of antepartum fetal heart rate:1. Baseline determination[J]. International Journal of Bio-medical Computing, 1990, 25(4):261-272.
7.	AYRES-DE-CAMPOS D, BERNARDES J, GARRIDO A, et al. SisPorto 2.0:a program for automated analysis of cardiotocograms[J]. Journal of Maternal-Fetal and Neonatal Medicine, 2000, 9(5):311-318.
8.	JIMENEZ L, GONZALEZ R, GAITAN M, et al. Computerized algorithm for baseline estimation of fetal heart rate[C]//Computers in Cardiology. Memphis:2002:477-480.
9.	KRUPA B N, ALI M A M, ZAHEDI E. Computerized fetal heart rate baseline estimation based on number and continuity of occurrences[C]//4th Kuala Lumpur International Conference on Biomedical Engineering 2008. Kuala Lumpur:2008, 21:162-165.
10.	NIDHAL S, ALI M A M, NAJAH H. A novel cardiotocography fetal heart rate baseline estimation algorithm[J]. Scientific Research and Essays, 2010, 5(24):4002-4010.
11.	ANDERSSON S. Acceleration and deceleration detection and baseline estimation[D]. G? teborg:Chalmers University of Technology, 2011.
12.	GELMETTI A, MARAZZI A, GERMAGNOLI F, et al. Neural network filtering of antepartum fetal hearth rate for the baseline determination[C]//Proceedings of the International Conference on Artificial Neural Networks, ICANN'94. Sorrento, 1994:1319-1322.
13.	LU Y S, WEI S Y, LIU X L. Nonlinear FHR baseline estimation using empirical mode decomposition and Kohonen neural network[C]//2012 IEEE Biomedical Circuits and Systems Conference. Taipei:2012:368-371.
14.	GEORGOULAS G, CHRYSOSTOMOS D, GROUMPOS P. Predicting the risk of metabolic acidosis for newborns based on fetal heart rate signal classification using support vector machines[J]. IEEE Transactions on Biomedical Engineering, 2006, 53(5):875-884.
15.	NIDHAL S, ALI M A M, ZAIDAN A A, et al. Computerized algorithm for fetal heart rate baseline and baseline variability estimation based on distance between signal average and α value[J]. International Journal of Pharmacology, 2011, 7(2):228-237.
16.	LU Y, LI X, WEI S, et al. Fetal heart rate baseline estimation with analysis of fetal movement signal[J]. Bio-medical Materials and Engineering, 2014, 24(6):3763-3769.
17.	GORRY P A. General least-squares smoothing and differentiation by the convolution (Savitzky-Golay) method[J]. Analytical Chemistry, 1990, 62(6):570-573.
18.	BJÖRCK A. Numerical methods for least squares problems[M]. Philadelphia:Society for Industrial and Applied Mathematics, 1996:42-50.
19.	National Certification Corporation. NICHD Definitions and Classifications:Application to Electronic Fetal Monitoring Interpretation[J]. NCC Monograph, 2010, 3(1):1-20.

1. LEVENE M I, CHERVENAK F A. Fetal and neonatal neurology and neurosurgery[M]. 4th ed. London:Churchill Livingstone, 2009:506.
2. ALFIREVIC Z, DEVANE D, GYTE G M. Continuous cardiotocography (CTG) as a form of electronic fetal monitoring (EFM) for fetal assessment during labour[J]. Cochrane Database Syst Rev, 2006, 3(3):CD006066.
3. WARREN R, ARULKUMARAN S. Best practice in labour and delivery[M]. Cambridge:Cambridge University Press, 2009:38-53.
4. MACONES G, HANKINS G, SPONG C, et al. The 2008 National Institute of Child Health and Human Development workshop report on electronic fetal monitoring:update on definitions, interpretation, and research guidelines[J]. Journal of Obstetric, Gynecologic, Neonatal Nursing, 2008, 37(5):510-515.
5. DAWES G S, HOUGHTON C R S, REDMAN C W G. Baseline in human fetal heart-rate records[J]. BJOG:An International Journal of Obstetrics & Gynaecology, 1982, 89(4):270-275.
6. MANTEL R, VAN GEIJN H P, CARON F J M, et al. Computer analysis of antepartum fetal heart rate:1. Baseline determination[J]. International Journal of Bio-medical Computing, 1990, 25(4):261-272.
7. AYRES-DE-CAMPOS D, BERNARDES J, GARRIDO A, et al. SisPorto 2.0:a program for automated analysis of cardiotocograms[J]. Journal of Maternal-Fetal and Neonatal Medicine, 2000, 9(5):311-318.
8. JIMENEZ L, GONZALEZ R, GAITAN M, et al. Computerized algorithm for baseline estimation of fetal heart rate[C]//Computers in Cardiology. Memphis:2002:477-480.
9. KRUPA B N, ALI M A M, ZAHEDI E. Computerized fetal heart rate baseline estimation based on number and continuity of occurrences[C]//4th Kuala Lumpur International Conference on Biomedical Engineering 2008. Kuala Lumpur:2008, 21:162-165.
10. NIDHAL S, ALI M A M, NAJAH H. A novel cardiotocography fetal heart rate baseline estimation algorithm[J]. Scientific Research and Essays, 2010, 5(24):4002-4010.
11. ANDERSSON S. Acceleration and deceleration detection and baseline estimation[D]. G? teborg:Chalmers University of Technology, 2011.
12. GELMETTI A, MARAZZI A, GERMAGNOLI F, et al. Neural network filtering of antepartum fetal hearth rate for the baseline determination[C]//Proceedings of the International Conference on Artificial Neural Networks, ICANN'94. Sorrento, 1994:1319-1322.
13. LU Y S, WEI S Y, LIU X L. Nonlinear FHR baseline estimation using empirical mode decomposition and Kohonen neural network[C]//2012 IEEE Biomedical Circuits and Systems Conference. Taipei:2012:368-371.
14. GEORGOULAS G, CHRYSOSTOMOS D, GROUMPOS P. Predicting the risk of metabolic acidosis for newborns based on fetal heart rate signal classification using support vector machines[J]. IEEE Transactions on Biomedical Engineering, 2006, 53(5):875-884.
15. NIDHAL S, ALI M A M, ZAIDAN A A, et al. Computerized algorithm for fetal heart rate baseline and baseline variability estimation based on distance between signal average and α value[J]. International Journal of Pharmacology, 2011, 7(2):228-237.
16. LU Y, LI X, WEI S, et al. Fetal heart rate baseline estimation with analysis of fetal movement signal[J]. Bio-medical Materials and Engineering, 2014, 24(6):3763-3769.
17. GORRY P A. General least-squares smoothing and differentiation by the convolution (Savitzky-Golay) method[J]. Analytical Chemistry, 1990, 62(6):570-573.
18. BJÖRCK A. Numerical methods for least squares problems[M]. Philadelphia:Society for Industrial and Applied Mathematics, 1996:42-50.
19. National Certification Corporation. NICHD Definitions and Classifications:Application to Electronic Fetal Monitoring Interpretation[J]. NCC Monograph, 2010, 3(1):1-20.

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