A New Method to Derive Fetal Heart Rate from Maternal Abdominal Electrocardiogram: Monitoring Fetal Heart Rate During Cesarean Section

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2015 Feb 14

PMID 25680192

Citations 2

Authors

Huei-Ming Yeh

Yi-Chung Chang

Chen Lin

Chien-Hung Yeh

Chien-Nan Lee

Ming-Kwang Shyu

Ming-Hui Hung

Po-Ni Hsiao

Yung-Hung Wang

Yu-Hsin Tseng

Jenho Tsao

Ling-Ping Lai

Lian-Yu Lin

Men-Tzung Lo

Affiliations

Soon will be listed here.

Abstract

Background: Monitoring of fetal heart rate (FHR) is important during labor since it is a sensitive marker to obtain significant information about fetal condition. To take immediate response during cesarean section (CS), we noninvasively derive FHR from maternal abdominal ECG.

Methods: We recruited 17 pregnant women delivered by elective cesarean section, with abdominal ECG obtained before and during the entire CS. First, a QRS-template is created by averaging all the maternal ECG heart beats. Then, Hilbert transform was applied to QRS-template to generate the other basis which is orthogonal to the QRS-template. Second, maternal QRS, P and T waves were adaptively subtracted from the composited ECG. Third, Gabor transformation was applied to obtain time-frequency spectrogram of FHR. Heart rate variability (HRV) parameters including standard deviation of normal-to-normal intervals (SDNN), 0V, 1V, 2V derived from symbolic dynamics of HRV and SD1, SD2 derived from Poincareé plot. Three emphasized stages includes: (1) before anesthesia, (2) 5 minutes after anesthesia and (3) 5 minutes before CS delivery.

Results: FHRs were successfully derived from all maternal abdominal ECGs. FHR increased 5 minutes after anesthesia and 5 minutes before delivery. As for HRV parameters, SDNN increased both 5 minutes after anesthesia and 5 minutes before delivery (21.30±9.05 vs. 13.01±6.89, P < 0.001 and 22.88±12.01 vs. 13.01±6.89, P < 0.05). SD1 did not change during anesthesia, while SD2 increased significantly 5 minutes after anesthesia (27.92±12.28 vs. 16.18±10.01, P < 0.001) and both SD2 and 0V percentage increased significantly 5 minutes before delivery (30.54±15.88 vs. 16.18±10.01, P < 0.05; 0.39±0.14 vs. 0.30±0.13, P < 0.05).

Conclusions: We developed a novel method to automatically derive FHR from maternal abdominal ECGs and proved that it is feasible during CS.

Citing Articles

A systematic review on the utility of non-invasive electrophysiological assessment in evaluating for intra uterine growth restriction.

Smith V, Nair A, Warty R, Sursas J, da Silva Costa F, Wallace E BMC Pregnancy Childbirth. 2019; 19(1):230.

PMID: 31277600 PMC: 6610904. DOI: 10.1186/s12884-019-2357-9.

Spectral Analysis of Heart Rate Variability: Time Window Matters.

Li K, Rudiger H, Ziemssen T Front Neurol. 2019; 10:545.

PMID: 31191437 PMC: 6548839. DOI: 10.3389/fneur.2019.00545.

References

Cheng F, Venetsanopoulos A . An adaptive morphological filter for image processing. IEEE Trans Image Process. 1992; 1(4):533-9. DOI: 10.1109/83.199924. View

Kamen P . Heart rate variability. Aust Fam Physician. 1996; 25(7):1087-9, 1091-5. View

Hutson J . Diagnosis and management of intrapartum reflex fetal heart rate changes. Clin Perinatol. 1982; 9(2):325-37. View

Karvounis E, Tsipouras M, Fotiadis D . Detection of fetal heart rate through 3-D phase space analysis from multivariate abdominal recordings. IEEE Trans Biomed Eng. 2009; 56(5):1394-406. DOI: 10.1109/TBME.2009.2014691. View

Clifford G, Sameni R, Ward J, Robinson J, Wolfberg A . Clinically accurate fetal ECG parameters acquired from maternal abdominal sensors. Am J Obstet Gynecol. 2011; 205(1):47.e1-5. PMC: 3145045. DOI: 10.1016/j.ajog.2011.02.066. View

Ibrahimy M, Ahmed F, Ali M, Zahedi E . Real-time signal processing for fetal heart rate monitoring. IEEE Trans Biomed Eng. 2003; 50(2):258-62. DOI: 10.1109/TBME.2002.807642. View

Abboud S, Barkai G, Mashiach S, Sadeh D . Quantification of the fetal electrocardiogram using averaging technique. Comput Biol Med. 1990; 20(3):147-55. DOI: 10.1016/0010-4825(90)90001-6. View

Karmakar C, Khandoker A, Voss A, Palaniswami M . Sensitivity of temporal heart rate variability in Poincaré plot to changes in parasympathetic nervous system activity. Biomed Eng Online. 2011; 10:17. PMC: 3061954. DOI: 10.1186/1475-925X-10-17. View

Abboud S, Alaluf A, Einav S, Sadeh D . Real-time abdominal fetal ECG recording using a hardware correlator. Comput Biol Med. 1992; 22(5):325-35. DOI: 10.1016/0010-4825(92)90021-e. View

10.

Tulppo M, Makikallio T, Takala T, Seppanen T, Huikuri H . Quantitative beat-to-beat analysis of heart rate dynamics during exercise. Am J Physiol. 1996; 271(1 Pt 2):H244-52. DOI: 10.1152/ajpheart.1996.271.1.H244. View

11.

Aljadeff G, Gozal D, Schechtman V, Burrell B, Harper R, Ward S . Heart rate variability in children with obstructive sleep apnea. Sleep. 1997; 20(2):151-7. DOI: 10.1093/sleep/20.2.151. View

12.

Bergveld P, Meijer W . A new technique for the suppression of the MECG. IEEE Trans Biomed Eng. 1981; 28(4):348-54. DOI: 10.1109/TBME.1981.324803. View

13.

Kamen P, Krum H, Tonkin A . Poincaré plot of heart rate variability allows quantitative display of parasympathetic nervous activity in humans. Clin Sci (Lond). 1996; 91(2):201-8. DOI: 10.1042/cs0910201. View

14.

Karmakar C, Gubbi J, Khandoker A, Palaniswami M . Analyzing temporal variability of standard descriptors of Poincaré plots. J Electrocardiol. 2010; 43(6):719-24. DOI: 10.1016/j.jelectrocard.2010.09.001. View

15.

Muralikrishnan K, Balasubramanian K, Ali S, Rao B . Poincare plot of heart rate variability: an approach towards explaining the cardiovascular autonomic function in obesity. Indian J Physiol Pharmacol. 2013; 57(1):31-7. View

16.

Abrao K, Francisco R, Miyadahira S, Cicarelli D, Zugaib M . Elevation of uterine basal tone and fetal heart rate abnormalities after labor analgesia: a randomized controlled trial. Obstet Gynecol. 2008; 113(1):41-47. DOI: 10.1097/AOG.0b013e31818f5eb6. View

17.

DOWNS H, MORRISON P . THE EFFECTS OF SPINAL ANESTHESIA ON THE FETAL HEART RATE. Calif Med. 1963; 99:374-7. PMC: 1515329. View

18.

Hayano J, Takahashi H, Toriyama T, Mukai S, Okada A, Sakata S . Prognostic value of heart rate variability during long-term follow-up in chronic haemodialysis patients with end-stage renal disease. Nephrol Dial Transplant. 1999; 14(6):1480-8. DOI: 10.1093/ndt/14.6.1480. View

19.

Wu S, Shen Y, Zhou Z, Lin L, Zeng Y, Gao X . Research of fetal ECG extraction using wavelet analysis and adaptive filtering. Comput Biol Med. 2013; 43(10):1622-7. DOI: 10.1016/j.compbiomed.2013.07.028. View

20.

Stein P, Domitrovich P, Hui N, Rautaharju P, Gottdiener J . Sometimes higher heart rate variability is not better heart rate variability: results of graphical and nonlinear analyses. J Cardiovasc Electrophysiol. 2005; 16(9):954-9. DOI: 10.1111/j.1540-8167.2005.40788.x. View