Xinshu Xiao et al 2005 Physiol. Meas. 26 R41 doi:10.1088/0967-3334/26/3/R01
Xinshu Xiao1, Thomas J Mullen2 and Ramakrishna Mukkamala3
Show affiliationsShort-term, beat-to-beat cardiovascular variability reflects the dynamic interplay between ongoing perturbations to the circulation and the compensatory response of neurally mediated regulatory mechanisms. This physiologic information may be deciphered from the subtle, beat-to-beat variations by using digital signal processing techniques. While single signal analysis techniques (e.g., power spectral analysis) may be employed to quantify the variability itself, the multi-signal approach of system identification permits the dynamic characterization of the neural regulatory mechanisms responsible for coupling the variability between signals. In this review, we provide an overview of applications of system identification to beat-to-beat variability for the quantitative characterization of cardiovascular regulatory mechanisms. After briefly summarizing the history of the field and basic principles, we take a didactic approach to describe the practice of system identification in the context of probing neural cardiovascular regulation. We then review studies in the literature over the past two decades that have applied system identification for characterizing the dynamical properties of the sinoatrial node, respiratory sinus arrhythmia, and the baroreflex control of sympathetic nerve activity, heart rate and total peripheral resistance. Based on this literature review, we conclude by advocating specific methods of practice and that future research should focus on nonlinear and time-varying behaviors, validation of identification methods, and less understood neural regulatory mechanisms. Ultimately, we hope that this review stimulates such future investigations by both new and experienced system identification researchers.
87.85.Xd Dynamical, regulatory, and integrative biology
Issue 3 (June 2005)
Received 25 August 2004, in final form 19 November 2004
Published 1 February 2005
Xinshu Xiao et al 2005 Physiol. Meas. 26 R41
Zhifa Pu et al 2006 Nanotechnology 17 799
Somnath Bharadwaj and Biswajit Pandey 2004 ApJ 615 1
Sebastian Guttenberg et al JHEP06(2004)030
P S Chung 1983 J. Phys. D: Appl. Phys. 16 1179
K McGee and S Shalev 1993 Phys. Med. Biol. 38 601
D Treschev 2002 Nonlinearity 15 2033
W Taweepreda et al 2009 J. Phys.: Conf. Ser. 190 012150
J Herrero-Martín et al 2009 J. Phys.: Conf. Ser. 190 012086
A. Moskalenko et al 1997 Europhys. Lett. 40 135