Additive effect of simultaneously varying respiratory frequency and tidal volume on respiratory sinus arrhythmia

2014 ◽  
Vol 186 ◽  
pp. 69-76 ◽  
Author(s):  
Alejandra Guillén-Mandujano ◽  
Salvador Carrasco-Sosa
1989 ◽  
Vol 67 (4) ◽  
pp. 1447-1455 ◽  
Author(s):  
L. Bernardi ◽  
F. Keller ◽  
M. Sanders ◽  
P. S. Reddy ◽  
B. Griffith ◽  
...  

We performed this study to test whether the denervated human heart has the ability to manifest respiratory sinus arrhythmia (RSA). With the use of a highly sensitive spectral analysis technique (cross correlation) to define beat-to-beat coupling between respiratory frequency and heart rate period (R-R) and hence RSA, we compared the effects of patterned breathing at defined respiratory frequency and tidal volumes (VT), Valsalva and Mueller maneuvers, single deep breaths, and unpatterned spontaneous breathing on RSA in 12 normal volunteers and 8 cardiac allograft transplant recipients. In normal subjects R-R changes closely followed changes in respiratory frequency (P less than 0.001) but were little affected by changes in VT. On the R-R spectrum, an oscillation peak synchronous with respiration was found in heart transplant patients. However, the average magnitude of the respiration-related oscillations was 1.7–7.9% that seen in normal subjects and was proportionally more influenced by changes in VT. Changes in R-R induced by Valsalva and Mueller maneuvers were 3.8 and 4.9% of those seen in normal subjects, respectively, whereas changes in R-R induced by single deep breaths were 14.3% of those seen in normal subjects. The magnitude of RSA was not related to time since the heart transplantation, neither was it related to patient age or sex. Thus the heart has the intrinsic ability to vary heart rate in synchrony with ventilation, consistent with the hypothesis that changes, or rate of changes, in myocardial wall stretch might alter intrinsic heart rate independent of autonomic tone.


2019 ◽  
Vol 10 ◽  
Author(s):  
Fabien Cauture ◽  
Blair Sterba-Boatwright ◽  
Julie Rocho-Levine ◽  
Craig Harms ◽  
Stefan Miedler ◽  
...  

2007 ◽  
Vol 292 (5) ◽  
pp. H2397-H2407 ◽  
Author(s):  
Y. C. Tzeng ◽  
P. D. Larsen ◽  
D. C. Galletly

Normally, at rest, the amplitude of respiratory sinus arrhythmia (RSA) appears to correlate with cardiac vagal tone. However, recent studies showed that, under stress, RSA dissociates from vagal tone, indicating that separate mechanisms might regulate phasic and tonic vagal activity. This dissociation has been linked to the hypothesis that RSA improves pulmonary gas exchange through preferential distribution of heartbeats in inspiration. We examined the effects of hypercapnia and mild hypoxemia on RSA-vagal dissociation in relation to heartbeat distribution throughout the respiratory cycle in 12 volunteers. We found that hypercapnia, but not hypoxemia, was associated with significant increases in heart rate (HR), tidal volume, and RSA amplitude. The RSA amplitude increase remained statistically significant after adjustment for respiratory rate, tidal volume, and HR. Moreover, the RSA amplitude increase was associated with a paradoxical rise in HR and decrease in low-frequency-to-high-frequency mean amplitude ratio derived from spectral analysis, which is consistent with RSA-vagal dissociation. Although hypercapnia was associated with a significant increase in the percentage of heartbeats during inspiration, this association was largely secondary to increases in the inspiratory period-to-respiratory period ratio, rather than RSA amplitude. Additional model analyses of RSA were consistent with the experimental data. Heartbeat distribution did not change during hypoxemia. These results support the concept of RSA-vagal dissociation during hypercapnia; however, the putative role of RSA in optimizing pulmonary perfusion matching requires further experimental validation.


1981 ◽  
Vol 241 (4) ◽  
pp. H620-H629 ◽  
Author(s):  
J. A. Hirsch ◽  
B. Bishop

The relationship of respiratory sinus arrhythmia amplitude (RSA) to tidal volume and breathing frequency was quantified during voluntarily controlled tidal volume and breathing frequency and spontaneous quiet breathing. Seventeen seated subjects breathed via mouthpiece and nose-clip, maintaining constant tidal volumes at each of several breathing frequencies. Inspiratory breath hold was zero frequency. Log RSA was plotted vs. log frequency for each tidal volume. The large stable RSA for frequencies less than 6 cycles/min was called low-frequency intercept (LFI, 20 +/- 5 beats/min). Low-frequency intercept was inversely proportional to a subject's age only to 35 yr. At higher breathing frequencies above a characteristic corner frequency (fC, 7.2 +/- 1.5 cycles/min) RSA decreased with constant slope (roll-off; 21 +/- 3.4 dB/decade). The RSA-volume relationship was linear permitting normalization of RSA-frequency curves for tidal volume to yield one curve. Spontaneous breathing data points fell on this curve. Voluntarily coupling of heart rate to breathing frequency in integer ratios reduced breath-by-breath variability of RSA without changing mean RSA. In conclusion, low-frequency intercept, corner frequency, and roll-off characterize an individual's RSA-frequency relationship during both voluntarily controlled and spontaneous breathing.


2013 ◽  
Vol 53 (6) ◽  
pp. 854-861
Author(s):  
Christoph Hoog Antink ◽  
Steffen Leonhardt

Respiratory Sinus Arrhythmia, the variation in the heart rate synchronized with the breathing cycle, forms an interconnection between cardiac-related and respiratory-related signals. It can be used by itself for diagnostic purposes, or by exploiting the redundancies it creates, for example by extracting respiratory rate from an electrocardiogram (ECG). To perform quantitative analysis and patient specific modeling, however, simultaneous information about ventilation as well as cardiac activity needs to be recorded and analyzed. The recent advent of medically approved Electrical Impedance Tomography (EIT) devices capable of recording up to 50 frames per second facilitates the application of this technology. This paper presents the automated selection of a cardiac-related signal from EIT data and quantitative analysis of this signal. It is demonstrated that beat-to-beat intervals can be extracted with a median absolute error below 20 ms. A comparison between ECG and EIT data shows a variation in peak delay time that requires further analysis. Finally, the known coupling of heart rate variability and tidal volume can be shown and quantified using global impedance as a surrogate for tidal volume.


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