No Access

MULTIVARIATE TIME-VARYING AUTOREGRESSIVE MODELING OF FETAL SYMPATHO-VAGAL BALANCE THROUGH GESTATION

D. Gutiérrez

Center for Research and Advanced Studies (Cinvestav), Monterrey's Unit, Apodaca NL 66600, Mexico

Corresponding author: D. Gutiérrez, Ph.D., Cinvestav, Monterrey's Unit, Apodaca, NL 66600, Mexico.

https://doi.org/10.4015/S1016237213500142Cited by:1 (Source: Crossref)

Abstract

A processing framework is proposed to model relative changes in fetal sympatho-vagal balance at equally spaced gestational periods. The proposed method is based on a multivariable time-varying autoregression (TVAR) of the beat-to-beat time differences obtained from non-invasive fetal electrocardiographic (ECG) or magnetocardiographic (MCG) measurements. In order to quantify the sympatho-vagal balance at each measured gestational period, the ratio between the standard deviation of normal-to-normal (SDNN) beat intervals and the sum of absolute differences (SAD) is computed. While the SDNN quantifies the overall variability of the sympathetic and vagal systems, the SAD enhances short-term variability components related to vagal control, then the ratio of these two compares with high specificity the overall variability against the short-term vagal component in the time domain. The SDNN/SAD ratio is used to form a new data set by removing short-term variability events, then leaving only those corresponding to longer-term sympatho-vagal balance. The new data set is then analyzed as a dynamical system by fitting it to a suitable multivariate TVAR, and relative changes in the sympatho-vagal balance through the analyzed gestational periods are assumed to be related to the dynamics of the time-varying coefficients of the TVAR. In order to demonstrate the applicability of the proposed method, simulated and real fetal E/MCG data are analyzed. The results show that the modeling approach is able to infer the expected trend seen through sympatho-vagal development.

Keywords:

References

A. Malliani et al. , Circulation 98 , 2640 ( 1998 ) . Crossref, Web of Science, Google Scholar
C. B. Martin , Clin. Perinatol. 9 , 339 ( 1982 ) . Crossref, Web of Science, Google Scholar
J. F. Strasburger and R. T. Wakai , Nat. Rev. Cardiol. 7 , 277 ( 2010 ) . Crossref, Web of Science, Google Scholar
J. G. Nijhuis et al. , Early. Human. Develop. 6 , 177 ( 1982 ) . Crossref, Web of Science, Google Scholar
M. Peters et al. , J. Perinatal. Med. 29 , 408 ( 2001 ) . Crossref, Web of Science, Google Scholar
J. D. Wilson et al. , IEEE. Trans. Biomed. Engrg. 55 , 2190 ( 2008 ) . Crossref, Web of Science, Google Scholar
Z. Rauf et al. , PLoS. ONE. 6 , e28129 ( 2011 ) . Crossref, Web of Science, Google Scholar
P. Van Leeuwen et al. , Prenat. Diagn. 23 , 909 ( 2003 ) . Crossref, Web of Science, Google Scholar
U. Schneider et al. , J. Perina. Med. 36 , 433 ( 2008 ) . Crossref, Web of Science, Google Scholar
B. Grimm et al. , Pacing. Clin. Electrophysiol. 26 , 2121 ( 2003 ) . Crossref, Web of Science, Google Scholar
D. Hoyer et al. , Early. Human. Develop. 85 , 379 ( 2009 ) . Crossref, Web of Science, Google Scholar
R. B. Govindan et al. , Amer. J. Obstet. Gynecol. 196 , 572.e1 ( 2007 ) . Crossref, Web of Science, Google Scholar
M. David et al. , J. Appl. Physiol. 102 , 1057 ( 2007 ) . Crossref, Web of Science, Google Scholar
R. Wakai , Exp. Neurol. 190 , S65 ( 2004 ) . Crossref, Web of Science, Google Scholar
G. R. Sandercock , P. D. Bromley and D. A. Brodie , Int. J. Cardiol. 103 , 238 ( 2005 ) . Crossref, Web of Science, Google Scholar
E. B. Schroeder et al. , Int. J. Cardiol. 37 , 163 ( 2004 ) . Google Scholar
T. S. Rao , J. Roy. Stat. Soc. B 32 , 312 ( 1970 ) . Google Scholar
A. D. Krystal , R. Prado and M. West , Clin. Neurophysiol. 110 , 2197 ( 1999 ) . Crossref, Web of Science, Google Scholar
Y. E. Zhuravlev et al. , Early. Human. Develop. 66 , 1 ( 2002 ) . Crossref, Web of Science, Google Scholar
S. E. Robinsonet al., A biomagnetic instrument for human reproductive assessment, Proc. 12th Int. Conf. Biomagn. (2000) pp. 919–922. Google Scholar
T. Schneider and A. Neumaier , ACM. Trans. Math. Softw. 27 , 58 ( 2001 ) . Crossref, Web of Science, Google Scholar
A. Boardman et al. , Physiol. Meas. 23 , 325 ( 2002 ) . Crossref, Web of Science, Google Scholar
S. Lange et al. , Early. Human. Develop. 85 , 131 ( 2009 ) . Crossref, Web of Science, Google Scholar
J. de Haan et al. , British. J. Obstet. Gynecol. 82 , 353 ( 1975 ) . Crossref, Web of Science, Google Scholar
T. F. of the European Society of Cardiology and T. N. A. S. of Pacing Electrophysiology, Heart rate variability: Standards of measurement, physiological interpretation, and clinical use, Circulation 93:1043, 1996 . Google Scholar
K. K. Kim et al. , Comput. Meth. Programs. Biomed. , DOI: 10.1016/j.cmpb.2010.11.011 . Google Scholar
A. Neumaier and T. Schneider , ACM. Trans. Math. Softw. 27 , 27 ( 2001 ) . Crossref, Web of Science, Google Scholar
H. Lütkepohl , Introduction to Multiple Time Series Analysis ( Springer-Verlag , New York , 1993 ) . Crossref, Google Scholar
D. Gutiérrezet al., Characterizing fetal sympatho-vagal balance through multivariate time-varying autoregressive modeling of magnetocardiographic data, Adv. Biomagn. BIOMAG2010, IFMBE Proc.28 (2010) p. 270. Google Scholar
G. Schwarz , Ann. Stat. 6 , 461 ( 1978 ) . Crossref, Web of Science, Google Scholar
H. Hytti , R. Takalo and H. Ihalainen , J. Clin. Monit. Comput. 20 , 101 ( 2006 ) . Crossref, Google Scholar
T. Ohta et al. , Fetal. Diagn. Ther. 14 , 92 ( 1999 ) . Crossref, Web of Science, Google Scholar
H. Von Storch et al. , J. Climate. 8 , 377 ( 1995 ) . Crossref, Web of Science, Google Scholar