Respiratory Induced Modulation in f-Wave Characteristics During Atrial Fibrillation

Abdollahpur, Mostafa; Holmqvist, Fredrik; Platonov, Pyotr G.; Sandberg, Frida

doi:10.3389/fphys.2021.653492

Cited by 2 publications

(22 citation statements)

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“…In the present study, we propose a novel methodology, based on orthogonal subspace projection, for quantifying respiratory variations in the f-wave frequency trend. Results from analysis of simulated data show that the estimation accuracy of the proposed approach is comparable to that of our previously proposed bandpass filtering approach (Abdollahpur et al, 2021). However, the proposed approach is better suited for analysis of standard ECG recordings since it can handle time-varying respiration (Figure 3) and provides more accurate estimates of respiratory variations at low SNR (Figure 4).…”

Section: Respiratory F-wave Variationmentioning

confidence: 75%

“…Through these simulated signals, the accuracy of

as an estimate of Δ F is compared to our previously proposed band-pass filtering approach to quantify respiratory induced variations in the f-wave frequency trend ( Abdollahpur et al, 2021 ). In that method, respiratory variation is estimated by applying a narrow band-pass filter with a fixed bandwidth of 0.06 Hz and a center frequency corresponding to the F r .…”

Section: Methodsmentioning

confidence: 99%

“…Respiratory induced f-wave frequency variations has previously been shown to be affected by parasympathetic regulation. In our previous study, (Abdollahpur et al, 2021), 5-min ECGs recorded from eight patients during controlled respiration before and after full vagal blockade were analyzed; in 50% of the patients, respiratory variation was significantly reduced after the vagal blockade. Moreover, results from computational simulations of human Frontiers in Physiology frontiersin.org atrial tissues confirmed that the pattern of the parasympathetic neurotransmitter acetylcholine release could be an important factor involved in f-wave frequency variation (Celotto et al, 2020).…”

Section: Respiratory F-wave Variationmentioning

confidence: 99%

“…Östenson et al studied changes in the f-wave frequency in response to changes in ANS tone induced by tilt-test in 40 patients with persistent AF, results showed f-wave frequency decreased during head-down tilt (HDT) compared to baseline and increased during head-up tilt (HUT) ( Östenson et al, 2017 ). In a previous study, we investigated changes in f-wave frequency variations in response to controlled respiration ( Abdollahpur et al, 2021 ). In a study population of eight pacemaker patients with permanent AF recorded at baseline, during controlled respiration, and during controlled respiration after injection of atropine.…”

Section: Introductionmentioning

confidence: 99%

“…Briefly, a high-resolution f-wave frequency trend obtained using model-based approach was filtered using a narrow bandpass filter with center frequency corresponding to respiration rate and fixed bandwidth. The envelope of the filtered frequency trend served as an estimate of the magnitude of the respiratory variation; the results indicated that this magnitude was affected by parasympathetic regulation ( Abdollahpur et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

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A subspace projection approach to quantify respiratory variations in the f-wave frequency trend

Abdollahpur

Engström²,

Platonov

et al. 2022

Front. Physiol.

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Background: The autonomic nervous system (ANS) is known as a potent modulator of the initiation and perpetuation of atrial fibrillation (AF), hence information about ANS activity during AF may improve treatment strategy. Respiratory induced ANS variation in the f-waves of the ECG may provide such information.Objective: This paper proposes a novel approach for improved estimation of such respiratory induced variations and investigates the impact of deep breathing on the f-wave frequency in AF patients.Methods: A harmonic model is fitted to the f-wave signal to estimate a high-resolution f-wave frequency trend, and an orthogonal subspace projection approach is employed to quantify variations in the frequency trend that are linearly related to respiration using an ECG-derived respiration signal. The performance of the proposed approach is evaluated and compared to that of a previously proposed bandpass filtering approach using simulated f-wave signals. Further, the proposed approach is applied to analyze ECG data recorded for 5 min during baseline and 1 min deep breathing from 28 AF patients from the Swedish cardiopulmonary bioimage study (SCAPIS).Results: The simulation results show that the estimates of respiratory variations obtained using the proposed approach are more accurate than estimates obtained using the previous approach. Results from the analysis of SCAPIS data show no significant differences between baseline and deep breathing in heart rate (75.5 ± 22.9 vs. 74 ± 22.3) bpm, atrial fibrillation rate (6.93 ± 1.18 vs. 6.94 ± 0.66) Hz and respiratory f-wave frequency variations (0.130 ± 0.042 vs. 0.130 ± 0.034) Hz. However, individual variations are large with changes in heart rate and atrial fibrillatory rate in response to deep breathing ranging from −9% to +5% and −8% to +6%, respectively and there is a weak correlation between changes in heart rate and changes in atrial fibrillatory rate (r = 0.38, p < 0.03).Conclusion: Respiratory induced f-wave frequency variations were observed at baseline and during deep breathing. No significant changes in the magnitude of these variations in response to deep breathing was observed in the present study population.

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Section: Respiratory F-wave Variationmentioning

confidence: 75%

“…Through these simulated signals, the accuracy of

Section: Methodsmentioning

confidence: 99%

Section: Respiratory F-wave Variationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A subspace projection approach to quantify respiratory variations in the f-wave frequency trend

Abdollahpur

Engström²,

Platonov

et al. 2022

Front. Physiol.

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The frequency of atrial fibrillatory waves is modulated by the spatiotemporal pattern of acetylcholine release: a 3D computational study

Celotto,

Sánchez,

Abdollahpur

et al. 2024

Front. Physiol.

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In atrial fibrillation (AF), the ECG P-wave, which represents atrial depolarization, is replaced with chaotic and irregular fibrillation waves (f waves). The f-wave frequency, Ff, shows significant variations over time. Cardiorespiratory interactions regulated by the autonomic nervous system have been suggested to play a role in such variations. We conducted a simulation study to test whether the spatiotemporal release pattern of the parasympathetic neurotransmitter acetylcholine (ACh) modulates the frequency of atrial reentrant circuits. Understanding parasympathetic involvement in AF may guide more effective treatment approaches and could help to design autonomic markers alternative to heart rate variability (HRV), which is not available in AF patients. 2D tissue and 3D whole-atria models of human atrial electrophysiology in persistent AF were built. Different ACh release percentages (8% and 30%) and spatial ACh release patterns, including spatially random release and release from ganglionated plexi (GPs) and associated nerves, were considered. The temporal pattern of ACh release, ACh(t), was simulated following a sinusoidal waveform of frequency 0.125 Hz to represent the respiratory frequency. Different mean concentrations (ACh̄) and peak-to-peak ranges of ACh (ΔACh) were tested. We found that temporal variations in Ff, Ff(t), followed the simulated temporal ACh(t) pattern in all cases. The temporal mean of Ff(t), F̄f, depended on the fibrillatory pattern (number and location of rotors), the percentage of ACh release nodes and ACh̄. The magnitude of Ff(t) modulation, ΔFf, depended on the percentage of ACh release nodes and ΔACh. The spatial pattern of ACh release did not have an impact on F̄f and only a mild impact on ΔFf. The f-wave frequency, being indicative of vagal activity, has the potential to drive autonomic-based therapeutic actions and could replace HRV markers not quantifiable from AF patients.

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Respiratory Induced Modulation in f-Wave Characteristics During Atrial Fibrillation

Cited by 2 publications

References 40 publications

A subspace projection approach to quantify respiratory variations in the f-wave frequency trend

A subspace projection approach to quantify respiratory variations in the f-wave frequency trend

The frequency of atrial fibrillatory waves is modulated by the spatiotemporal pattern of acetylcholine release: a 3D computational study

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