title: Probing heart rate and blood pressure control mechanisms during graded levels of lower body negative pressure (LBNP).
abstract: Following space flight or head down tilt bed rest, cardiovascular deconditioning is often observed as a failure to maintain arterial blood pressure with symptoms of presyncope or syncope. LBNP can be used as a stressor of the cardiovascular system to observe the regulatory process. We have recently developed a new method to study cardiovascular control. Coarse graining spectral analysis (CGSA), allows simultaneous extraction of the harmonic components to evaluate sympathetic and parasympathetic nervous activities, and of the underlying complexity of the physiological response as given by the slope (beta) or fractal dimension (DF). The recognition that system complexity plays a major role in maintenance of cardiovascular stability is a relatively new concept. It was the purpose of the present study to examine the underlying complexity of heart rate and systolic blood pressure (SBP) variablities as indicated by the DF and power spectral analysis. Eight healthy men completed a test protocol of 20 min supine rest followed sequentially by 10 min at -5, -15, -25, -40, and -50 mmHg LBNP, and 10 min supine recovery. At rest, DF of R-R interval was 3.57 (beta = 1.56 +/- 0.12). There was a progressive decline in DF with LBNP, until at -50 mmHg, DF decreased to 1.2 (beta = 2.66 +/- 0.09). The DF for SBP was 1.3 (beta = 2.1 +/- 0.18) at rest, and was not significantly changed during LBNP. In the mid- and high-frequency ranges of the spectra, there was a moderately high degree of coherence between the variability in R-R interval and SBP. These findings indicate that short term SBP has a relatively low and unchanged complexity compared to heart rate. The changes in DF of heart rate variability were marked with increasing levels of LBNP. The results of this, and our previous study, indicate that a decline of DF to a critical level (near 1.4) is associated with orthostatic hypotension. These data show the utility of simple, non-invasive methods of data collection in conjunction with sophisticated data analysis techniques to point to possible mechanisms of orthostatic hypotension.
authors.affiliation: Department of Kinesiology, University of Waterloo, Canada.
authors.forename: G C
authors.initials: GC
authors.lastname: Butler
authors.forename: Y
authors.initials: Y
authors.lastname: Yamamoto
authors.forename: H C
authors.initials: HC
authors.lastname: Xing
authors.forename: D R
authors.initials: DR
authors.lastname: Northey
authors.forename: R L
authors.initials: RL
authors.lastname: Hughson
mesh_terms: D000328:Adult; D000337:Aerospace Medicine; D001794:Blood Pressure / Q000502:physiology*; D017709:Fractals; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D007024:Hypotension, Orthostatic / Q000517:prevention & control*; D008150:Lower Body Negative Pressure; D008297:Male; D008991:Monitoring, Physiologic; D017711:Nonlinear Dynamics; D013057:Spectrum Analysis; D016683:Supine Position; D013575:Syncope / Q000517:prevention & control