A Mathematical Model of The Atrioventricular Node during Atrial Fibrillation
Author
Summary, in English
The atrioventricular (AV) node plays a crucial role during
atrial fibrillation (AF). The aim of this study is to
present an AV node model which can be fitted to short-term
ECG recordings in order to infer certain AV node characteristics.
The proposed model is characterized by: i) the
arrival rate of atrial impulses; ii) two different refractory
periods, corresponding to dual AV nodal paths; iii) the
probability of an atrial impulse choosing either of these
pathways; iv) a parameter modeling prolongation of the
refractory period due to different physiological reasons.
The model was tested on atrial fibrillatory ECGs recorded
from 33 patients; the average normalized absolute error
between the normalized RR histogram and the estimated
model probability density function was 0.0023 ± 0.0016,
(20-ms bin size, 0–2 s interval). These preliminary results
are encouraging as AV nodal properties can be noninvasively
assessed by a set of statistical parameters with a
simple electrophysiological interpretation.
atrial fibrillation (AF). The aim of this study is to
present an AV node model which can be fitted to short-term
ECG recordings in order to infer certain AV node characteristics.
The proposed model is characterized by: i) the
arrival rate of atrial impulses; ii) two different refractory
periods, corresponding to dual AV nodal paths; iii) the
probability of an atrial impulse choosing either of these
pathways; iv) a parameter modeling prolongation of the
refractory period due to different physiological reasons.
The model was tested on atrial fibrillatory ECGs recorded
from 33 patients; the average normalized absolute error
between the normalized RR histogram and the estimated
model probability density function was 0.0023 ± 0.0016,
(20-ms bin size, 0–2 s interval). These preliminary results
are encouraging as AV nodal properties can be noninvasively
assessed by a set of statistical parameters with a
simple electrophysiological interpretation.
Publishing year
2010
Language
English
Pages
117-120
Publication/Series
[Host publication title missing]
Volume
37
Document type
Conference paper
Topic
- Electrical Engineering, Electronic Engineering, Information Engineering
Conference name
Computing in Cardiology 2010
Conference date
2010-09-26
Conference place
Ireland
Status
Published
Research group
- Signal Processing
ISBN/ISSN/Other
- ISSN: 0276-6574