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ECG-based beat-to-beat assessment of AV node conduction properties during AF

Karlsson, Mattias LU ; Plappert, Felix LU orcid ; Platonov, Pyotr G. LU ; Östenson, Sten ; Wallman, Mikael and Sandberg, Frida LU (2025) In Frontiers in Physiology 16.
Abstract

Introduction: The refractory period and conduction delay of the atrioventricular (AV) node play a crucial role in regulating the heart rate during atrial fibrillation (AF). Beat-to-beat variations in these properties are known to be induced by the autonomic nervous system (ANS) but have previously not been assessable during AF. Assessing these could provide novel information for improved diagnosis, prognosis, and treatment on an individual basis. Methods: To estimate AV nodal conduction properties with beat-to-beat resolution, we propose a methodology comprising a network model of the AV node, a particle filter, and a smoothing algorithm. The methodology was evaluated using simulated data and using synchronized electrogram (EGM) and ECG... (More)

Introduction: The refractory period and conduction delay of the atrioventricular (AV) node play a crucial role in regulating the heart rate during atrial fibrillation (AF). Beat-to-beat variations in these properties are known to be induced by the autonomic nervous system (ANS) but have previously not been assessable during AF. Assessing these could provide novel information for improved diagnosis, prognosis, and treatment on an individual basis. Methods: To estimate AV nodal conduction properties with beat-to-beat resolution, we propose a methodology comprising a network model of the AV node, a particle filter, and a smoothing algorithm. The methodology was evaluated using simulated data and using synchronized electrogram (EGM) and ECG recordings from five patients in the intracardiac atrial fibrillation database. The methodology’s ability to quantify ANS-induced changes in AV node conduction properties was evaluated by analyzing ECG data from 21 patients in AF undergoing a tilt test protocol. Results: The estimated refractory period and conduction delay matched the simulated ground truth based on ECG recordings with a mean absolute error ((Formula presented.) std) of 169 (Formula presented.) 14 ms for the refractory period in the fast pathway; 131 (Formula presented.) 13 ms for the conduction delay in the fast pathway; 67 (Formula presented.) 10 ms for the refractory period in the slow pathway; and 178 (Formula presented.) 28 ms for the conduction delay in the slow pathway. These errors decreased when using simulated ground truth based on EGM recordings. Moreover, a decrease in conduction delay and refractory period in response to head-up tilt was seen during the tilt test protocol, as expected under sympathetic activation. Discussion: These results suggest that beat-to-beat estimation of AV nodal conduction properties during AF from ECG is feasible, with different levels of uncertainty, and that the estimated properties agree with expected AV nodal modulation.

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author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
atrial fibrillation, atrioventricular node model, autonomic nervous system, mathematical modeling, particle filter, smoothing algorithm
in
Frontiers in Physiology
volume
16
article number
1624403
publisher
Frontiers Media S. A.
external identifiers
  • scopus:105013391844
  • pmid:40821943
ISSN
1664-042X
DOI
10.3389/fphys.2025.1624403
project
Diagnostic Biomarkers in Atrial Fibrillation - Autonomic Nervous System Response as a Sign of Disease Progression
Ph.D. project: Non-invasive analysis of ANS activity in atrial fibrillation
language
English
LU publication?
yes
additional info
Publisher Copyright: Copyright © 2025 Karlsson, Plappert, Platonov, Östenson, Wallman and Sandberg.
id
c92ad954-26e6-4cf4-aef2-ead7f763ea5b
date added to LUP
2025-09-01 08:05:07
date last changed
2025-09-02 03:00:06
@article{c92ad954-26e6-4cf4-aef2-ead7f763ea5b,
  abstract     = {{<p>Introduction: The refractory period and conduction delay of the atrioventricular (AV) node play a crucial role in regulating the heart rate during atrial fibrillation (AF). Beat-to-beat variations in these properties are known to be induced by the autonomic nervous system (ANS) but have previously not been assessable during AF. Assessing these could provide novel information for improved diagnosis, prognosis, and treatment on an individual basis. Methods: To estimate AV nodal conduction properties with beat-to-beat resolution, we propose a methodology comprising a network model of the AV node, a particle filter, and a smoothing algorithm. The methodology was evaluated using simulated data and using synchronized electrogram (EGM) and ECG recordings from five patients in the intracardiac atrial fibrillation database. The methodology’s ability to quantify ANS-induced changes in AV node conduction properties was evaluated by analyzing ECG data from 21 patients in AF undergoing a tilt test protocol. Results: The estimated refractory period and conduction delay matched the simulated ground truth based on ECG recordings with a mean absolute error ((Formula presented.) std) of 169 (Formula presented.) 14 ms for the refractory period in the fast pathway; 131 (Formula presented.) 13 ms for the conduction delay in the fast pathway; 67 (Formula presented.) 10 ms for the refractory period in the slow pathway; and 178 (Formula presented.) 28 ms for the conduction delay in the slow pathway. These errors decreased when using simulated ground truth based on EGM recordings. Moreover, a decrease in conduction delay and refractory period in response to head-up tilt was seen during the tilt test protocol, as expected under sympathetic activation. Discussion: These results suggest that beat-to-beat estimation of AV nodal conduction properties during AF from ECG is feasible, with different levels of uncertainty, and that the estimated properties agree with expected AV nodal modulation.</p>}},
  author       = {{Karlsson, Mattias and Plappert, Felix and Platonov, Pyotr G. and Östenson, Sten and Wallman, Mikael and Sandberg, Frida}},
  issn         = {{1664-042X}},
  keywords     = {{atrial fibrillation; atrioventricular node model; autonomic nervous system; mathematical modeling; particle filter; smoothing algorithm}},
  language     = {{eng}},
  publisher    = {{Frontiers Media S. A.}},
  series       = {{Frontiers in Physiology}},
  title        = {{ECG-based beat-to-beat assessment of AV node conduction properties during AF}},
  url          = {{http://dx.doi.org/10.3389/fphys.2025.1624403}},
  doi          = {{10.3389/fphys.2025.1624403}},
  volume       = {{16}},
  year         = {{2025}},
}