Respiratory Modulation in Permanent Atrial Fibrillation
(2020) 2020 Computing in Cardiology, CinC 2020 In Computing in Cardiology 2020-September.- Abstract
Several studies have shown that the autonomic nervous system (ANS) can induce changes during atrial fibrillation (AF). There is currently a lack of methods for quantifying ANS induced variations during AF. The purpose of this study is to quantify respiratory induced modulation in the f-wave frequency trend. Following qrst-cancellation, the local f-wave frequency is estimated by fitting a harmonic f-wave model signal and a quality index (SQI) is computed based on the model fit. The resulting frequency trend is filtered using a narrow bandpass filter with a center frequency corresponding to the local respiration rate. The magnitude of the respiratory induced f-wave frequency modulation is estimated by the envelope of the filtered... (More)
Several studies have shown that the autonomic nervous system (ANS) can induce changes during atrial fibrillation (AF). There is currently a lack of methods for quantifying ANS induced variations during AF. The purpose of this study is to quantify respiratory induced modulation in the f-wave frequency trend. Following qrst-cancellation, the local f-wave frequency is estimated by fitting a harmonic f-wave model signal and a quality index (SQI) is computed based on the model fit. The resulting frequency trend is filtered using a narrow bandpass filter with a center frequency corresponding to the local respiration rate. The magnitude of the respiratory induced f-wave frequency modulation is estimated by the envelope of the filtered frequency trend. The performance of the method is validated using simulations and the method is applied to analyze ECG data from eight patients with permanent AF recorded during 0.125 Hz frequency controlled respiration before and after the full vagal blockade, respectively. Results from simulated data show the magnitude of the respiratory induced f-wave frequency modulation can be estimated with an error of less than = 0.005Hz if the SQI is above 0.45. The signal quality was sufficient for analysis in 7 out of 8 patients. In 4 patients the magnitude decreased and in 3 patients there was no change.
(Less)
- author
- Abdollahpur, Mostafa LU ; Holmqvist, Fredrik LU ; Platonov, Pyotr G. LU and Sandberg, Frida LU
- organization
- publishing date
- 2020
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2020 Computing in Cardiology, CinC 2020
- series title
- Computing in Cardiology
- volume
- 2020-September
- article number
- 9344442
- publisher
- IEEE Computer Society
- conference name
- 2020 Computing in Cardiology, CinC 2020
- conference location
- Rimini, Italy
- conference dates
- 2020-09-13 - 2020-09-16
- external identifiers
-
- scopus:85100915995
- ISSN
- 2325-8861
- 2325-887X
- ISBN
- 9781728173825
- DOI
- 10.22489/CinC.2020.182
- project
- Ph.D. project: Risk stratification and prediction of intervention outcome in AF using novel ECG-based markers of atrial remodelling
- Diagnostic Biomarkers in Atrial Fibrillation - Autonomic Nervous System Response as a Sign of Disease Progression
- language
- English
- LU publication?
- yes
- id
- b9840500-4a21-4c0f-b3cf-5732d397728f
- date added to LUP
- 2021-03-05 10:52:40
- date last changed
- 2024-05-02 04:16:54
@inproceedings{b9840500-4a21-4c0f-b3cf-5732d397728f,
abstract = {{<p>Several studies have shown that the autonomic nervous system (ANS) can induce changes during atrial fibrillation (AF). There is currently a lack of methods for quantifying ANS induced variations during AF. The purpose of this study is to quantify respiratory induced modulation in the f-wave frequency trend. Following qrst-cancellation, the local f-wave frequency is estimated by fitting a harmonic f-wave model signal and a quality index (SQI) is computed based on the model fit. The resulting frequency trend is filtered using a narrow bandpass filter with a center frequency corresponding to the local respiration rate. The magnitude of the respiratory induced f-wave frequency modulation is estimated by the envelope of the filtered frequency trend. The performance of the method is validated using simulations and the method is applied to analyze ECG data from eight patients with permanent AF recorded during 0.125 Hz frequency controlled respiration before and after the full vagal blockade, respectively. Results from simulated data show the magnitude of the respiratory induced f-wave frequency modulation can be estimated with an error of less than = 0.005Hz if the SQI is above 0.45. The signal quality was sufficient for analysis in 7 out of 8 patients. In 4 patients the magnitude decreased and in 3 patients there was no change.</p>}},
author = {{Abdollahpur, Mostafa and Holmqvist, Fredrik and Platonov, Pyotr G. and Sandberg, Frida}},
booktitle = {{2020 Computing in Cardiology, CinC 2020}},
isbn = {{9781728173825}},
issn = {{2325-8861}},
language = {{eng}},
publisher = {{IEEE Computer Society}},
series = {{Computing in Cardiology}},
title = {{Respiratory Modulation in Permanent Atrial Fibrillation}},
url = {{https://lup.lub.lu.se/search/files/95172838/Respiratory_Modulation_in_Permanent_Atrial_Fibrillation.pdf}},
doi = {{10.22489/CinC.2020.182}},
volume = {{2020-September}},
year = {{2020}},
}