Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)

Analysis of the Atrial Signals Based on a Novel Complex Network

Authors
Baodan Bai, Boyu Si
Corresponding Author
Baodan Bai
Available Online June 2017.
DOI
https://doi.org/10.2991/caai-17.2017.114How to use a DOI?
Keywords
atrial fibrillation; complex networt; atrial vulnerability; phase synchronization
Abstract
Atrial fibrillation (AF) is one of the most common arrhythmia in clinical, which is the major cause of embolic events and stroke, resulting in an important morbidity and mortality. The mechanisms leading to AF are still under extensive research. In this study, we present a novel complex network approach to analysis the dynamics of the heart during the whole AF process (before the AF to end of the AF). Three canine models of acute AF were designed and the common parameters of the novel complex network were used to investigate the method. The results show that the novel complex network parameter can not only detect the AF, but also can estimate the vulnerability of atrial fibrillation effectively.
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Proceedings
2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
Part of series
Advances in Intelligent Systems Research
Publication Date
June 2017
ISBN
978-94-6252-360-9
ISSN
1951-6851
DOI
https://doi.org/10.2991/caai-17.2017.114How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Baodan Bai
AU  - Boyu Si
PY  - 2017/06
DA  - 2017/06
TI  - Analysis of the Atrial Signals Based on a Novel Complex Network
BT  - 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
PB  - Atlantis Press
SP  - 508
EP  - 511
SN  - 1951-6851
UR  - https://doi.org/10.2991/caai-17.2017.114
DO  - https://doi.org/10.2991/caai-17.2017.114
ID  - Bai2017/06
ER  -