Characterization of Atrial Fibrillation Episodes Using a Point Process Model
(2020) 11th Conference of the European Study Group on Cardiovascular Oscillations, ESGCO 2020 In 2020 11th Conference of the European Study Group on Cardiovascular Oscillations: Computation and Modelling in Physiology: New Challenges and Opportunities, ESGCO 2020- Abstract
The purpose of the present study is to introduce a point process model for characterizing the pattern of atrial fibrillation (AF) episodes. A variant of the bivariate Hawkes process is proposed, accounting for clustered episodes. The model parameters are inferred by the maximum likelihood method. The goodness-of-fit analysis show that model fits the data in most of the recordings (27 out of 32). The information provided by this approach is complementary to AF burden.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/7587467a-da17-4628-8d98-e81241780ba6
- author
- Martin-Yebra, Alba ; Henriksson, Mikael LU ; Rasmussen, Jakob G. and Sornmo, Leif LU
- organization
- publishing date
- 2020-07
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2020 11th Conference of the European Study Group on Cardiovascular Oscillations : Computation and Modelling in Physiology: New Challenges and Opportunities, ESGCO 2020 - Computation and Modelling in Physiology: New Challenges and Opportunities, ESGCO 2020
- series title
- 2020 11th Conference of the European Study Group on Cardiovascular Oscillations: Computation and Modelling in Physiology: New Challenges and Opportunities, ESGCO 2020
- article number
- 9158173
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 11th Conference of the European Study Group on Cardiovascular Oscillations, ESGCO 2020
- conference location
- Virtual, Online, Italy
- conference dates
- 2020-07-15
- external identifiers
-
- scopus:85091056533
- ISBN
- 9781728157511
- DOI
- 10.1109/ESGCO49734.2020.9158173
- language
- English
- LU publication?
- yes
- id
- 7587467a-da17-4628-8d98-e81241780ba6
- date added to LUP
- 2021-01-12 13:19:27
- date last changed
- 2022-04-19 03:38:30
@inproceedings{7587467a-da17-4628-8d98-e81241780ba6, abstract = {{<p>The purpose of the present study is to introduce a point process model for characterizing the pattern of atrial fibrillation (AF) episodes. A variant of the bivariate Hawkes process is proposed, accounting for clustered episodes. The model parameters are inferred by the maximum likelihood method. The goodness-of-fit analysis show that model fits the data in most of the recordings (27 out of 32). The information provided by this approach is complementary to AF burden. </p>}}, author = {{Martin-Yebra, Alba and Henriksson, Mikael and Rasmussen, Jakob G. and Sornmo, Leif}}, booktitle = {{2020 11th Conference of the European Study Group on Cardiovascular Oscillations : Computation and Modelling in Physiology: New Challenges and Opportunities, ESGCO 2020}}, isbn = {{9781728157511}}, language = {{eng}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, series = {{2020 11th Conference of the European Study Group on Cardiovascular Oscillations: Computation and Modelling in Physiology: New Challenges and Opportunities, ESGCO 2020}}, title = {{Characterization of Atrial Fibrillation Episodes Using a Point Process Model}}, url = {{http://dx.doi.org/10.1109/ESGCO49734.2020.9158173}}, doi = {{10.1109/ESGCO49734.2020.9158173}}, year = {{2020}}, }