Transient interactions between blood pressure, respiration and heart rate in man

Kitney, R.I.; Fulton, Timothy J.; McDonald, Alison; Linkenst, D.A.

doi:10.1016/0141-5425(85)90022-6

Cited by 94 publications

(51 citation statements)

References 24 publications

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“…This hypothesis is motivated by the observation that blood pressure and blood flow velocity can be entrained by respiration or other external perturbation [18,19], and exhibit spontaneous oscillations over a wide frequency ranges [0.05-0. 4 Hz] even during resting conditions [14,15,[20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Altered phase interactions between spontaneous blood pressure and flow fluctuations in type 2 diabetes mellitus: Nonlinear assessment of cerebral autoregulation

Peng

Huang

et al. 2008

Physica A: Statistical Mechanics and its Applications

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Cerebral autoregulation (CA) is an important mechanism that involves dilation and constriction in arterioles to maintain relatively s cerebral blood flow in response to changes of systemic blood pressure. Traditional assessments of CA focus on the changes of cerebral blood flow velocity in response to large blood pressure fluctuations induced by interventions. This approach is not feasible for patients with impaired autoregulation or cardiovascular regulation. Here we propose a newly developed technique-the multimodal pressure-flow (MMPF) analysis, which assesses CA by quantifying nonlinear phase interactions between spontaneous oscillations in blood pressure and flow velocity during resting conditions. We show that CA in healthy subjects can be characterized by specific phase shifts between spontaneous blood pressure and flow velocity oscillations, and the phase shifts are significantly reduced in diabetic subjects. Smaller phase shifts between oscillations in the two variables indicate more passive dependence of blood flow velocity on blood pressure, thus suggesting impaired cerebral autoregulation. Moreover, the reduction of the phase shifts in diabetes is observed not only in previously-recognized effective region of CA (<0.1Hz), but also over the higher frequency range from ~0.1 to 0.4Hz. These findings indicate that Type 2 diabetes alters cerebral blood flow regulation over a wide frequency range and that this alteration can be reliably assessed from spontaneous oscillations in blood pressure and blood flow velocity during resting conditions. We also show that the MMPF method has better performance than traditional approaches based on Fourier transform, and is more sui for the quantification of nonlinear phase interactions between nonstationary biological signals such as blood pressure and blood flow.

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Section: Introductionmentioning

confidence: 99%

Altered phase interactions between spontaneous blood pressure and flow fluctuations in type 2 diabetes mellitus: Nonlinear assessment of cerebral autoregulation

Peng

Huang

et al. 2008

Physica A: Statistical Mechanics and its Applications

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“…y means of spectral analysis, short-term (time scale of seconds to minutes) variability in blood pressure (BP) and heart rate (HR) tracings can be divided into oscillatory components arising from various sources: one is linked to respiration (at approximately 0.25 Hz), 1 another is assumed to be caused by baroreceptor activity (at approximately 0.1 Hz), 2 and the third is believed to originate in the system responsible for regulating body temperature (in the range of 0.08 to 0.04 Hz). 3 The slowest component also has been held to be due to local adjustments of resistance in individual vascular beds matching blood flow to local metabolic demand.…”

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confidence: 99%

Short-term variability of blood pressure and heart rate in borderline and mildly hypertensive subjects.

et al. 1994

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Electrocardiogram and intra-arterial blood pressure were recorded in % men (aged 35 to 45 years) by the Oxford method over a 30-hour period. The study involved 33 normotensive, 29 borderline hypertensive, and 34 mildly hypertensive individuals, as assessed by the cuff method. Five-minute periods during sleep and with subjects in supine, sitting, and standing positions were extracted from the recordings for frequency domain analysis. Power spectrum density estimates of systolic blood pressure, diastolic blood pressure, and heart rate were calculated by an autoregressive method over the bandwidths of 0.02 to 0.075 (low-frequency), 0.075 to 0.15 (midfrequency), and 0.15 to 035 Hz (high-frequency), attributable to thermoregulatory, baroreceptor, and respiratory activity. No significant intergroup differences were observed at nighttime, but in different body positions the borderline hypertensive subjects frequently had either greater low-frequency variability or smaller midfrequency variability than the other groups. In this respect, the power spectra for systolic and diastolic blood pressures provided better statistical differentiation between the groups than those for heart rate. Furthermore, the borderline hypertensive subjects exhibited attenuated night-day changes in the low-frequency band for all time series. The results suggest that in borderline hypertension the baroreceptor oscillations are shifted to lower frequencies, presumably reflecting altered function of the sympathetic nervous system. In conclusion, spectral analysis of blood pressure variability for controlled test situations made it possible to detect differences in the cardiovascular regulatory systems between normotensive, borderline hypertensive, and mildly hypertensive individuals. (Hypertension. 1994^3:18-24.) Key Words • blood pressure • hypertension, borderline • heart rate • spectrum analysis B y means of spectral analysis, short-term (time scale of seconds to minutes) variability in blood pressure (BP) and heart rate (HR) tracings can be divided into oscillatory components arising from various sources: one is linked to respiration (at approximately 0.25 Hz), 1 another is assumed to be caused by baroreceptor activity (at approximately 0.1 Hz), 2 and the third is believed to originate in the system responsible for regulating body temperature (in the range of 0.08 to 0.04 Hz).3 The slowest component also has been held to be due to local adjustments of resistance in individual vascular beds matching blood flow to local metabolic demand. 4 It is not known exactly how these fluctuations enter into the cardiovascular control loops, but they are generally considered to be mediated principally by the autonomic nervous system. Respiratory coupled variability, especially in HR, is a marker of vagal activity, whereas the lower frequencies are jointly mediated by parasympathetic and sympathetic outflows.56 Accordingly, spectral analysis is a method that can provide important information about autonomic nervous control

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“…Jumping from a plane at 4000 m of height may cause changes in the respiration rate and depth (Fenz and Epstein 1967;Roth et al 1996). These in turn can affect HRV (Penttila et al 2001;Brown et al 1993;Kitney et al 1985), and subsequently increase the parasympathetic contribution (HF) by a shift from LF to HF, potentially masking the LF increase that should coincide with the rise of the sympathetic tone during the jump. Thus, correct interpretation of HRV measures by frequency domain has to account for possible changes in the respiration rate during the time course of data collection.…”

Section: Discussionmentioning

confidence: 99%

Heart rate variability and critical flicker fusion frequency changes during and after parachute jumping in experienced skydivers

et al. 2015

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Transient interactions between blood pressure, respiration and heart rate in man

Cited by 94 publications

References 24 publications

Altered phase interactions between spontaneous blood pressure and flow fluctuations in type 2 diabetes mellitus: Nonlinear assessment of cerebral autoregulation

Altered phase interactions between spontaneous blood pressure and flow fluctuations in type 2 diabetes mellitus: Nonlinear assessment of cerebral autoregulation

Short-term variability of blood pressure and heart rate in borderline and mildly hypertensive subjects.

Heart rate variability and critical flicker fusion frequency changes during and after parachute jumping in experienced skydivers

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