Hybrid Particle Swarm Optimization-Fuzzy Inference System for Premature Atrial Contraction Detection

DOI

10.2991/icopia-14.2015.30How to use a DOI?

Keywords

Particle swarm optimization, fuzzy inference system, premature atrial contraction, electrocardiogram

Abstract

This article presents a new technique to detect a premature atrial contraction (PAC). The technique employs a hybrid of particle swarm optimization (PSO) and fuzzy inference system (FIS), and is called PSO-FIS. In the detection electrocardiographic features are used for the inputs of PSO-FIS. In PSO-FIS, a PSO is used to find the optimal parameters of the FIS. A Gaussian function is employed for the fuzzification part of the FIS. The inputs of the FIS are the interval between two consecutive electrocardiographic R waves and the accumulation of the amplitudes around the P waves. Using clinical data, the technique performs well for PAC detection with 81.93%, 82.27% and 82.26% respectively.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Nuryani Nuryani
AU  - Iwan Yahya
AU  - Anik Lestari
PY  - 2014/09
DA  - 2014/09
TI  - Hybrid Particle Swarm Optimization-Fuzzy Inference System for Premature Atrial Contraction Detection
BT  - Proceedings of the 2014 International Conference on Physics and its Applications
PB  - Atlantis Press
SP  - 153
EP  - 156
SN  - 2352-541X
UR  - https://doi.org/10.2991/icopia-14.2015.30
DO  - 10.2991/icopia-14.2015.30
ID  - Nuryani2014/09
ER  -