Cardiovascular variables such as heart rate, arterial blood pressure, stroke volume and the shape of electrocardiographic complexes all fluctuate on a beat to beat basis. These fluctuations have traditionally been ignored or, at best, treated as noise to be averaged out. The variability in cardiovascular signals reflects the homeodynamic interplay between perturbations to cardiovascular function and the dynamic response of the cardiovascular regulatory systems. Modern signal processing techniques provide a means of analyzing beat to beat fluctuations in cardiovascular signals, so as to permit a quantitative, noninvasive or minimally invasive method of assessing closed loop hemodynamic regulation and cardiac electrical stability. This method promises to provide a new approach to the clinical diagnosis and management of alterations in cardiovascular regulation and stability.

We applied system identification to the analysis of fluctuations in heart rate (HR), arterial blood pressure (ABP), and instantaneous lung volume (ILV) to characterize quantitatively the physiological mechanisms responsible for the couplings between these variables. We characterized two autonomically mediated coupling mechanisms [the heart rate baroreflex (HR baroreflex) and respiratory sinus arrhythmia (ILV-HR)] and two mechanically mediated coupling mechanisms [the blood pressure wavelet generated with each cardiac contraction (circulatory mechanics) and the direct mechanical effects of respiration on blood pressure (ILV-->ABP)]. We evaluated the method in humans studied in the supine and standing postures under control conditions and under conditions of beta-sympathetic and parasympathetic pharmacological blockades. Combined beta-sympathetic and parasympathetic blockade abolished the autonomically mediated couplings while preserving the mechanically mediated coupling. Selective autonomic blockade and postural changes also altered the couplings in a manner consistent with known physiological mechanisms. System identification is an "inverse-modeling" technique that provides a means for creating a closed-loop model of cardiovascular regulation for an individual subject without altering the underlying physiological control mechanisms.

Beat-to-beat heart rate variability was studied by power spectral analysis in 17 orthotopic cardiac transplant patients. Heart rate power spectra were calculated from eighty-four 256-second recordings and compared with those taken from six normal subjects. The power spectra from the control subjects resolved into discrete peaks at 0.04-0.12 Hz and 0.2-0.3 Hz, whereas those of heart transplant recipients resembled broad-band noise without peaks. Log total power in the 0.02-1.0 Hz range was greater in the control subjects (0.982±0.084 within 48 hours of an endomyocardial biopsy. When the power spectra of those patients whose endomyocardial biopsies showed evidence of myocardial rejection were compared with those from patients who were found to be free of rejection, a significant dilference was found in log total power (-0.602±0.090 [0.525] vs. -0.909±0.136 [0.577], p <0.02). We conclude that denervation of the heart significantly reduces heart rate variability and abolishes the discrete spectral peaks seen in untransplanted control subjects and that the development of allograft rejection may significantly increase heart rate variability. (Circulation 1989;79: 76-82) Spontaneous beat-to-beat fluctuations in heart rate reflect ongoing modulation of sinus node activity through several cardiovascular control mechanisms.1 In addition to the respiratory sinus arrhythmia (0.2-0.3 Hz), the heart rate typically oscillates at specific lower frequencies, most commonly at 0.04-0.12 Hz.2,3-4 Heart rate fluctuations can be quantified by the technique of power spectrum analysis, which calculates the frequency content of time-varying signals.The purpose of this study was to characterize heart rate variability patterns in the orthotopic cardiac transplant recipient, a clinical model of the denervated heart. Using power spectrum analysis,

The influence of some extreme body postures on vital capacity (VC) was examined in young adult humans. Two postures required full support of body weight by the arms: arms up, hanging from a bar, and arms down with hands gripping parallel bars. Three involved muscles that flex and extend the trunk: a partial sit-up position while supine and nearly maximal spinal extension and flexion while standing. Changes at the inspiratory and expiratory volume extremes were recognized by having the subjects do two VC efforts: the first standing and the second in the posture in question while continuing to breathe on the spirometer. Control observations in which the second of a VC pair was performed in an unstressed posture allowed correction for the influence of rebreathing. The changes in corrected VC were small, the greatest being an average reduction of approximately 8% in the partial sit-up position. During full support of body weight by the arms, the VC was slightly increased due to a significant increase in the inspiratory extreme and no change in the expiratory extreme. Spinal extension produced small increases in lung volume at both extremes with no significant change in VC, whereas spinal flexion did not influence the upper extreme but did increase lung volume at the lower extreme. The changes are discussed in terms of trunk muscle action.