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A subspace projection approach to quantify respiratory variations in the f-wave frequency trend
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 in...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9527347/ https://www.ncbi.nlm.nih.gov/pubmed/36200057 http://dx.doi.org/10.3389/fphys.2022.976925 |
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author | Abdollahpur, Mostafa Engström, Gunnar Platonov, Pyotr G. Sandberg, Frida |
author_facet | Abdollahpur, Mostafa Engström, Gunnar Platonov, Pyotr G. Sandberg, Frida |
author_sort | Abdollahpur, Mostafa |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9527347 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95273472022-10-04 A subspace projection approach to quantify respiratory variations in the f-wave frequency trend Abdollahpur, Mostafa Engström, Gunnar Platonov, Pyotr G. Sandberg, Frida Front Physiol Physiology 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. Frontiers Media S.A. 2022-09-19 /pmc/articles/PMC9527347/ /pubmed/36200057 http://dx.doi.org/10.3389/fphys.2022.976925 Text en Copyright © 2022 Abdollahpur, Engström, Platonov and Sandberg. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Physiology Abdollahpur, Mostafa Engström, Gunnar Platonov, Pyotr G. Sandberg, Frida A subspace projection approach to quantify respiratory variations in the f-wave frequency trend |
title | A subspace projection approach to quantify respiratory variations in the f-wave frequency trend |
title_full | A subspace projection approach to quantify respiratory variations in the f-wave frequency trend |
title_fullStr | A subspace projection approach to quantify respiratory variations in the f-wave frequency trend |
title_full_unstemmed | A subspace projection approach to quantify respiratory variations in the f-wave frequency trend |
title_short | A subspace projection approach to quantify respiratory variations in the f-wave frequency trend |
title_sort | subspace projection approach to quantify respiratory variations in the f-wave frequency trend |
topic | Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9527347/ https://www.ncbi.nlm.nih.gov/pubmed/36200057 http://dx.doi.org/10.3389/fphys.2022.976925 |
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