Respiration response curve analysis of heart rate variability

Zhang, P.Z.; Tapp, Walter N.; Reisman, S.; Natelson, Benjamin H.

doi:10.1109/10.563302

Cited by 31 publications

(24 citation statements)

References 10 publications

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“…Another interesting signal to be considered in a hyperbaric study is the respiratory one, which can be extracted from ECG or PPG [13] - [19]. In this regard, it has been shown that changes in the respiratory pattern alter the spectral content of HRV [20] and, consequently, the interpretation of sympathetic or vagal activations [21] - [23].…”

Section: Introductionmentioning

confidence: 99%

Autonomic Nervous System Measurement in Hyperbaric Environments Using ECG and PPG Signals

Hernando

Peláez-Coca

Lozano

et al. 2019

IEEE J. Biomed. Health Inform.

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The main aim of this work was to characterise the Autonomic Nervous System (ANS) response in hyperbaric environments using electrocardiogram (ECG) and pulse-photoplethysmogram (PPG) signals. To that end, 26 subjects were introduced into a hyperbaric chamber and five stages with different atmospheric pressures (1 atm; descent to 3 and 5 atm; ascent to 3 and 1 atm) were recorded. Respiratory information was extracted from the ECG and PPG signals and a combined respiratory rate was studied. This information was also used to analyse Heart Rate Variability (HRV) and Pulse Rate Variability (PRV). The database was cleaned by eliminating those cases where the respiratory rate dropped into the low frequency band (LF: 0.04-0.15 Hz) and those in which there was a discrepancy between the respiratory rates estimated using the ECG and PPG signals. Classical temporal and frequency indices were calculated in such cases. The ECG results showed a time-related dependency, with the heart rate and sympathetic markers (normalised power in LF and LF/HF ratio) decreasing as more time was spent inside the hyperbaric environment. A dependency between the atmospheric pressure and the parasympathetic response, as reflected in the high frequency band power (HF: 0.15-0.40 Hz), was also found, with power increasing with atmospheric pressure. The combined respiratory rate also reached a maximum in the deepest stage, thus highlighting a significant difference between this stage and the first one. The PPG data gave similar findings and also allowed the oxygen saturation to be computed, therefore we propose the use of this signal for future studies in hyperbaric environments.

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Section: Introductionmentioning

confidence: 99%

Autonomic Nervous System Measurement in Hyperbaric Environments Using ECG and PPG Signals

Hernando

Peláez-Coca

Lozano

et al. 2019

IEEE J. Biomed. Health Inform.

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“…However, these methods cannot describe a precise phase relation between respiration and multiple cardiovascular variables, because respiration is not a linear or harmonic oscillator. One solution to this problem is to use paced respiration (12,24,31), but this investigates the respiratory influence only in a specific condition, and the pacing itself may result in unnatural hyperventilation or an alteration in the autonomic balance (19). Therefore, an analysis that represents respiration as a nonlinear oscillator, thus focusing on the respiratory phase, is required.…”

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confidence: 99%

Postural-induced phase shift of respiratory sinus arrhythmia and blood pressure variations: insight from respiratory-phase domain analysis

Kotani

Takamasu²,

Jimbo³

et al. 2008

American Journal of Physiology-Heart and Circulatory Physiology

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The purpose of this study is to evaluate the multiple effects of respiration on cardiovascular variability in different postures, by analyzing respiratory sinus arrhythmia (RSA) and respiratory-related blood pressure (BP) variations for systolic BP (SBP), diastolic BP (DBP), and pulse pressure (PP) in the respiratory-phase domain. The measurements were conducted for 420 s on healthy humans in the sitting and standing positions, while the subjects were continuously monitored for heart rate and BP variability and instantaneous lung volume. The waveforms of RSA and respiratory-related BP variations were extracted as a function of the respiratory phase. In the standing position, the waveforms of the BP variations for SBP, DBP, and PP show their maxima at around the end of expiration ( rad) and the minima at around the end of inspiration (2 rad), while the waveform of RSA is delayed by ϳ0.35 rad compared with the BP waveforms. On the other hand, in the sitting position, the phase of the DBP waveform (1.69 rad) greatly and significantly (P Ͻ 0.01) differs from that in the standing position (1.20 rad). Also, the phase of PP is delayed and that of RSA is advanced in the sitting position (P Ͻ 0.01). In particular, the phase shift of the DBP waveform is sufficiently large to alter whole hemodynamic fluctuations, affecting the amplitudes of SBP and PP variations. We conclude that the postural change associated with an altered autonomic balance affects not only the amplitude of RSA, but also the phases of RSA and BP variations in a complicated manner, and the respiratory-phase domain analysis used in this study is useful for elucidating the dynamic mechanisms of RSA.heart rate variability; Hilbert transform; respiratory phase; blood pressure variability RESPIRATION HAS STRONG AND multiple effects on the cardiovascular system. The best known effect of respiration is respiratory sinus arrhythmia (RSA) (12, 13, 26), i.e., fluctuations in heart rate (HR), depending on the phases of inspiration and expiration. RSA mainly reflects the modulation of the central autonomic outflow caused by respiration-related factors, such as spontaneous oscillations of respiratory centers and pulmonary stretch receptor afferents (8), and hemodynamic factors through the baroreflex and the Bainbridge reflex (30), which interact with each other in a complicated manner (4).Blood pressure (BP) is also affected by multiple interactions of these factors. To describe quantitatively the effects of respiration on HR and BP, Saul et al. (21) constructed a model in which HR is determined by the sum of central vagal and sympathetic activity, low-pass filtered and time delayed due to peripheral neurotransmitter kinetics. Arterial BP, determining the baroreceptor activity, is influenced by HR with some (mechanical) time delays. Then they incorporated the respiratory effects on HR and BP in two ways. First, instantaneous lung volume (ILV) has a (respiration-related) inhibitory effect on the central nervous system, which is known to be the inhibitory effect of in...

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“…The result is the dynamic pattern of R-R interval change along the respiratory cycle. Several researchers have applied the method to investigating magnitude (5,23,25,27) and phase properties (5,14,17,25,26) of RSA.…”

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confidence: 99%

Phase-averaged characterization of respiratory sinus arrhythmia pattern

Gilad

Swenne²,

Davrath³

et al. 2005

American Journal of Physiology-Heart and Circulatory Physiology

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A method for the accurate time-domain characterization of respiratory sinus arrhythmia (RSA) pattern is presented and applied to two groups of healthy subjects to lay the baseline of RSA patterns and to underlay their features: response to standing, stability in successive recordings, and individuality of the shape of RSA pattern. RSA pattern is evaluated by selective averaging of heart rate (HR) changes from multiple respiratory cycles over the respiratory phase and represents the complete modulating function of HR by respiration. The RSA pattern is evaluated with free respiration and even in cases of severe arrhythmia. Estimation error is 6-8% in magnitude, phase resolution is 0.2 rad, and sensitivity margin for respiratory-related HR variability (HRV) components is 1%. RSA magnitude, phase lag, and expiration-to-inspiration time ratio are derived in addition to the entire pattern. In a group of 10 healthy young adults, a phase lag difference of 11.4 +/- 8.5% (mean +/- SD, P < 0.004) was observed between supine and standing postures, possibly ascribed to breathing mechanics. A second group of 15 healthy young adults at supine rest showed stability of the RSA pattern in successive recordings (several weeks apart) as well as individuality among subjects. This may suggest a nonscalar individual long-term index for cardiorespiratory coupling. The method is complementary to the existing statistical and spectral methods. It allows the complete characterization of the primary RSA components and may provide new insight into the effects of vagal activity and changes in clinical conditions.

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Respiration response curve analysis of heart rate variability

Cited by 31 publications

References 10 publications

Autonomic Nervous System Measurement in Hyperbaric Environments Using ECG and PPG Signals

Autonomic Nervous System Measurement in Hyperbaric Environments Using ECG and PPG Signals

Postural-induced phase shift of respiratory sinus arrhythmia and blood pressure variations: insight from respiratory-phase domain analysis

Phase-averaged characterization of respiratory sinus arrhythmia pattern

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