The Analysis of Respiratory Sinus Arrhythmia Using Spectral Analysis and Digital Filtering

Womack, Baxter F.

doi:10.1109/tbme.1971.4502881

Cited by 62 publications

(29 citation statements)

References 7 publications

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“…The LF/HF n index is also very different: 0.03 for RR FM and 7 × 10 −9 for RR p . An improved simulation includes the low-pass filtering effect reported by Womack (1971). We have computed the LF/HF n index for the outputs of several low-pass filters whose inputs were RR p and RR FM .…”

Section: Results From Simulated Tachogramsmentioning

confidence: 99%

Variations in breathing patterns increase low frequency contents in HRV spectra

2000

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Abstract. This paper shows that variations in breathing patterns broaden heart rate variability (HRV) spectral bands and increase the power amplitude of low-frequency bands. Because of these influences, spectral markers for HRV signals, such as the quotient between spectral power at different frequency bands, should be compared only under controlled breathing conditions or after considering the effect of variations in breathing patterns.

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Section: Results From Simulated Tachogramsmentioning

confidence: 99%

Variations in breathing patterns increase low frequency contents in HRV spectra

2000

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“…Equidistantly sampled time series of the instantaneous BI were constructed from the series of heart beat events by linear interpolation of the instantaneous interval length and subsequent digital lowpass filtering [16,21,34]. The sample rate was stepwise reduced to 1 s -1 after digital lowpass filtering (FIR filter), in order to prevent aliasing effects.…”

Section: Frequency Domain Analysismentioning

confidence: 99%

Interbeat interval variability in isolated working rat hearts at various dynamic conditions and temperatures

et al. 1999

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This study quantifies the effect of afterload and preload changes and of temperature on interbeat interval variability of the intact isolated heart. Ventricular pressure pulse records were obtained from isolated working rat hearts. The variability of interbeat intervals (BIs) was quantified by C90, the central 90% range of the BIs during 10 min periods; predominant frequencies were searched for by power spectral analysis. At 37 degrees C the BI lengths oscillated pseudo-randomly with BI variability C90< or =4 ms. Alternating signs of consecutive BI differences were predominant, and no peaks. were seen in the power spectra. Changes in end-diastolic and aortic pressure had little effect. From 37 degrees C down to 27 degrees C the variability increased about sevenfold, run phase length became randomly distributed, and individual, time-variant peaks occurred in the power spectra. BI variability vanished during atrial pacing. We conclude that: (1) effective mutual synchronization with minimal fluctuation happens within the sino-atrial node of intact rat hearts at body temperature, and synchronization is not affected even by extreme changes in pre- and afterload, (2) the sino-atrial node is the sole source of BI variability in the intact isolated rat heart, (3) low temperature hampers this functional organization which can be reestablished by sinus node accelerating agents (isoprenaline, theophylline), (4) decreasing frequency by N6-Cyclopentyladenosine at normothermia also increases BI variability but less pronouncedly than hypothermia does.

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“…For the present study we employed a linear interpolation to provide equally spaced data. Although higher order interpolation could also be used, it has been found not to improve results (Womack 1971). …”

Section: Power Spectrummentioning

confidence: 99%

Bifurcations and Intrinsic Chaotic and 1/f Dynamics in an Isolated Perfused Rat Heart

et al. 1989

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The application of the theory of chaotic dynamical systems has gradually evolved from computer simulations to assessment of erratic behavior of physical, chemical, and biological systems. Whereas physical and chemical systems lend themselves to fairly good experimental control, biologic systems, because of their inherent complexity, are limited in this respect. This has not, however, prevented a number of investigators from attempting to understand many biologic periodicities. This has been especially true regarding cardiac dynamics: the spontaneous beating of coupled and non-coupled cardiac pacemakers provides a convenient comparison to the dynamics of oscillating systems of the physical sciences. One potentially important hypothesis regarding cardiac dynamics put forth by Goldberger and colleagues, is that normal heart beat fluctuations are chaotic, and are characterized by a 1/f-like power spectrum. To evaluate these conjectures, we studied the heart beat intervals (R wave to R wave of the electrocardiogram) of isolated, perfused rat hearts and their response to a variety of external perturbations. The results indicate bifurcations between complex patterns, states with positive dynamical entropies, and low values of fractal dimensions frequently seen in physical, chemical and cellular systems, as well as power law scaling of the spectrum. Additionally, these dynamics can be modeled by a simple, discrete map, which has been used to describe the dynamics of the Belousov-Zhabotinsky reaction.

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The Analysis of Respiratory Sinus Arrhythmia Using Spectral Analysis and Digital Filtering

Cited by 62 publications

References 7 publications

Variations in breathing patterns increase low frequency contents in HRV spectra

Variations in breathing patterns increase low frequency contents in HRV spectra

Interbeat interval variability in isolated working rat hearts at various dynamic conditions and temperatures

Bifurcations and Intrinsic Chaotic and 1/f Dynamics in an Isolated Perfused Rat Heart

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