Quantitative analysis of circadian variation in atrial fibrillation frequency
Author
Summary, in English
Circadian variation in atrial fibrillation (AF) frequency
is explored in this paper by employing recent advances in
signal processing. Once the AF frequency has been estimated
and tracked by a hidden Markov model approach,
the resulting trend is analyzed for the purpose of detecting
and characterizing the presence of circadian variation.
With cosinor analysis, the results show that the shortterm
variations in AF frequency exceeds the variation that
may be attributed to circadian. Using the autocorrelation
method, circadian variation was detected in 13 of 18
ambulatory ECG recordings (Holter) acquired from patients
with long standing persistent AF. Using the ensemble
correlation method, the highest AF frequency usually occurred
during the afternoon, whereas the lowest usually
occurred during late night. It is concluded that circadian
variation is present in most patients with long standing
persistent AF but the short-term variation in AF frequency
is considerable.
is explored in this paper by employing recent advances in
signal processing. Once the AF frequency has been estimated
and tracked by a hidden Markov model approach,
the resulting trend is analyzed for the purpose of detecting
and characterizing the presence of circadian variation.
With cosinor analysis, the results show that the shortterm
variations in AF frequency exceeds the variation that
may be attributed to circadian. Using the autocorrelation
method, circadian variation was detected in 13 of 18
ambulatory ECG recordings (Holter) acquired from patients
with long standing persistent AF. Using the ensemble
correlation method, the highest AF frequency usually occurred
during the afternoon, whereas the lowest usually
occurred during late night. It is concluded that circadian
variation is present in most patients with long standing
persistent AF but the short-term variation in AF frequency
is considerable.
Publishing year
2009
Language
English
Pages
129-132
Publication/Series
[Host publication title missing]
Volume
36
Document type
Conference paper
Publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
Topic
- Electrical Engineering, Electronic Engineering, Information Engineering
Conference name
36th Annual Computers in Cardiology Conference, 2009
Conference date
2009-09-13 - 2009-09-16
Conference place
Park City, UT, United States
Status
Published
Research group
- Signal Processing