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

Abdollahpur, Mostafa LU ; Engström, Gunnar LU ; Platonov, Pyotr G LU and Sandberg, Frida LU (2022) In Frontiers in Physiology 13.
Abstract


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... (More)


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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author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
atrial fibrillation, autonomic nervous system, respiratory variation, f-wave frequency, ECG processing
in
Frontiers in Physiology
volume
13
article number
976925
pages
11 pages
publisher
Frontiers Media S. A.
external identifiers
  • scopus:85139186390
  • pmid:36200057
ISSN
1664-042X
DOI
10.3389/fphys.2022.976925
project
Diagnostic Biomarkers in Atrial Fibrillation - Autonomic Nervous System Response as a Sign of Disease Progression
Ph.D. project: Risk stratification and prediction of intervention outcome in AF using novel ECG-based markers of atrial remodelling
MultidisciplinarY training network for ATrial fibRillation monItoring, treAtment and progression
language
English
LU publication?
yes
id
d2e84dd6-0ade-4700-8df4-6aebfaf92a4c
date added to LUP
2022-10-11 16:26:34
date last changed
2024-04-18 14:51:53
@article{d2e84dd6-0ade-4700-8df4-6aebfaf92a4c,
  abstract     = {{<p><br>
 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. <br>
 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. <br>
 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).<br>
 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 (<br>
 r = 0.38, <br>
 p &lt; 0.03). <br>
 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.<br>
 </p>}},
  author       = {{Abdollahpur, Mostafa and Engström, Gunnar and Platonov, Pyotr G and Sandberg, Frida}},
  issn         = {{1664-042X}},
  keywords     = {{atrial fibrillation; autonomic nervous system; respiratory variation; f-wave frequency; ECG processing}},
  language     = {{eng}},
  publisher    = {{Frontiers Media S. A.}},
  series       = {{Frontiers in Physiology}},
  title        = {{A subspace projection approach to quantify respiratory variations in the f-wave frequency trend}},
  url          = {{http://dx.doi.org/10.3389/fphys.2022.976925}},
  doi          = {{10.3389/fphys.2022.976925}},
  volume       = {{13}},
  year         = {{2022}},
}