The application of empirical mode decomposition for the enhancement of cardiotocograph signals

Physiological Measurement

Volumn 30, Issue 8, 2009, Pages 729-743

  Krupa, B N ^a   Mohd Ali, M A ^a   Zahedi, E ^b  

^a UNIVERSITI KEBANGSAAN MALAYSIA   (Malaysia)

^b SHARIF UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Cardiotocograph; Empirical mode decomposition; Fetal heart rate; Non stationary; Nonlinear; Signal enhancement; Uterine activity

Indexed keywords

BIOMEDICAL SIGNAL PROCESSING; BUTTERWORTH FILTERS; FETAL MONITORING; LOW PASS FILTERS; NEONATAL MONITORING;

CARDIOTOCOGRAPH; CLINICAL PRACTICES; EMPIRICAL MODE DECOMPOSITION; FETAL SURVEILLANCE; FOETAL HEART RATES; HIGH-FREQUENCY NOISE; NONLINEAR; NONSTATIONARY; SIGNAL ENHANCEMENT; UTERINE ACTIVITIES;

HEART;

ARTICLE; CARDIOTOCOGRAPHY; FETUS HEART RATE; FETUS MONITORING; INTRAPARTUM CARE; PRIORITY JOURNAL; SIGNAL PROCESSING; UTERUS CONTRACTION; FETUS; HUMAN; METHODOLOGY; MOTION; OBSTETRICS; PHYSIOLOGY; REPRODUCIBILITY; STATISTICAL MODEL;

CARDIOTOCOGRAPHY; FETUS; HEART RATE, FETAL; HUMANS; LINEAR MODELS; MOTION; OBSTETRICS; REPRODUCIBILITY OF RESULTS; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 70349782789     PISSN: 09673334     EISSN: 13616579     Source Type: Journal    
DOI: 10.1088/0967-3334/30/8/001     Document Type: Article

References (33)

1. Ayres-de-Campo D, Bernardes J, Costa-Pereira A and Pereira-Leite L 1999 Inconsistencies in expert's classification of cardiotocograms and subsequent clinical decision Br. J. Obstet. Gynaecol. 106 1307-10
2. Ayres-de-Campos D, Bernardes J, Garrido A, de Sa J P M and Pereira-Leite L 2000 SisPorto 2.0: a program for automated analysis of cardiotocograms J. Matern. Fetal Med. 9 311-8
3. Balocchi R, Menicucci D, Santarcangelo E, Sebastiani L, Gemignani A, Ghelarducci B and Varanini M 2004 Deriving the respiratory sinus arrhythmia from the heartbeat time series using empirical mode decomposition Chaos Solitons Fractals 20 171-7
4. Bernardes J, Costa-Pereira A, Ayres-de-Campos D, Van Geijn H P and Pereira-Leite L 1997 Evaluation of interobserver agreement of cardiotocograms Int. J. Gynecol. Obset. 57 33-7
5. Bernardes J, Moura C, de Sa J P M and Pereira-Leite L 1991 The Porto system for automated cardiotocographic signal analysis J. Perinat. Med. 19 61-5
6. Blanco-Velasco M, Weng B and Barner K E 2008 ECG signal denoising and baseline wander correction based on the empirical mode decomposition Comput. Biol. Med. 38 1-13
7. Cattani C, Doubrovina O, Rogosin S, Voskresensky S L and Zelianko E 2006 On the creation of a new diagnostic model for fetal well-being on the base of wavelet analysis of cardiotocograms J. Med. Syst. 30 489-94
8. Coughlin K and Tung K K 2004 Eleven-year solar cycle signal throughout the lower atmosphere J. Geophys. Res.-Atmos. 109 D21105
9. Delechelle E, Lemoine J and Niang O 2005 Empirical mode decomposition: an analytical approach for sifting process IEEE Signal Process. Lett. 12 764-7
10. Echevarría J C, Crowe J A, Woolfson M S and Hayes-Gill B R 2001 Application of empirical mode decomposition to heart rate variability analysis Med. Biol. Eng. Comput. 39 471-9
11. Flandrin P, Goncalves P and Rilling G 2004a Detrending and denoising with empirical mode decomposition Proc. of XII EUSIPCO (Viena, Austria, 2004) pp 1581-4
12. Flandrin P, Rilling G and Goncalves P 2004b Empirical mode decomposition as a filter bank IEEE Signal Process. Lett. 11 112-4
13. Fontenla-Romero O, Alonso-Betanzos A and Guijarro-Berdinas B 2001 Adaptive pattern recognition in the analysis of cardiotocographic records IEEE Trans. Neural Netw. 12 1188-95
14. Georgoulas G, Stylios C D and Groumpos P P 2005 Classification of fetal heart rate using scale dependent features and support vector machines Proc. 16th IFAC World Cong. (Prague)
15. Georgoulas G, Stylios C D and Groumpos P P 2006 Predicting the risk of metabolic acidosis for newborns based on fetal heart rate signal classification using support vector machines IEEE Trans. Biomed. Eng. 53 875-84
16. Huang N and Attoh-Okine N O 2005 The Hilbert-Huang Transform in Engineering (Boca Raton, FL: CRC Press)
17. Huang N E, Shen Z, Long S R, Wu M C, Shih H H, Zheng Q, Yen N-C, Tung C C and Liu H H 1998a The empirical mode decomposition and Hilbert spectrum for nonlinear and nonstationary time series analysis Proc. R. Soc. A 454 903-95
18. Huang W, Shen Z, Huang N E and Fung Y C 1998b Engineering analysis of biological variables: an example of blood pressure over 1 day Proc. Natl. Acad. Sci. USA 95 4816-21
19. Liang H, Lin Q-H and Chen J D Z 2005 Application of the empirical mode decomposition to the analysis of esophageal manometric data in gastroesophageal reflux disease IEEE Trans. Biomed. Eng. 52 1692-701
20. Liang H, Lin Z and McCallum R W 2000 Artifact reduction in electrogastrogram based on the empirical model decomposition method Med. Biol. Eng. Comput. 38 35-41
21. MacDonald D, Grant A, Sheridan-Pereira M, Boylan P and Chalmers I 1985 The Dublin randomized controlled trial of intrapartum fetal heart rate monitoring Am. J. Obstet. Gynecol. 152 524-39
22. Mantel R, Van Geijn H P, Caron F J M, Swartjes J M, Van Woerden E E and Jongsma H W 1990a Computer analysis of antepartum fetal heart rate: 1. Baseline determination Int. J. Biomed. Comput. 25 261-72
23. Mantel R, Van Geijn H P, Caron F J M, Swartjes J M, Van Woerden E E and Jongsma H W 1990b Computer analysis of antepartum fetal heart rate: 2. Detection of accelerations and decelerations Int. J. Biomed. Comput. 25 273-86 (Pubitemid 20169378)
24. Ortiz M R, Bojorges E R, Aguilar S D, Echeverria J C, Gonzalez-Camarena R, Carrasco S, Gaitan M J and Martinez A 2005 Analysis of high frequency fetal heart rate variability using empirical mode decomposition Comput. Cardiol. 32 675-78
25. Rooth G, Huch A and Huch R 1987 Guidelines for the use of fetal monitoring Int. J. Gynaecol. Obstet. 25 159-67
26. Rouvre D, Kouame D, Tranquart F and Pourcelot L 2005 Empirical mode decomposition (EMD) for multi-gate, multi-transducer ultrasound Doppler fetal heart monitoring Signal Processing and Information Technology, Proc. 5th IEEE Int. Symp. pp 208-12
27. Salamalekis E, Hintipas E, Salloum I, Vasios G, Loghis C, Vitoratos N, Chrelias Ch and Creatsas G 2006 Computerized analysis of fetal heart rate variability using the matching pursuit technique as an indicator of fetal hypoxia during labor J. Matern. Fetal. Neonatal. Med. 19 165-9
28. Salisbury J I and Sun Y 2004 Assessment of chaotic parameters in nonstationary electrocardiograms by use of empirical mode decomposition Ann. Biomed. Eng. 32 1348-54
29. Signorini M G, Magenes G, Cerutti S and Arduini D 2003 Linear and nonlinear parameters for the analysis of fetal heart rate signal from cardiotocographic recordings IEEE Trans. Biomed. Eng. 50 365-74
30. Ulbricht C, Dorffner G and Lee A 1998 Neural networks for recognizing patterns in cardiotocograms Artif. Intell. Med. 12 271-84
31. Weng B, Blanco-Velasco M and Barner K E 2006a ECG denoising based on the empirical mode decomposition Proc. IEEE EMBS'06 pp 1-4
32. Weng B, Blanco-Velasco M and Barner K E 2006b Baseline wander correction in ECG by the empirical mode decomposition Proc. IEEE 32nd Ann. Northeast Bioengineering Conf. (Easton, PA) pp 135-6 (Pubitemid 44761591)
33. Wu Z and Huang N E 2004 A study of the characteristics of white noise using the empirical mode decomposition method Proc. R. Soc. A 460 1597-611