Hybrid Particle Swarm Optimization-Fuzzy Inference System for Premature Atrial Contraction Detection
- 10.2991/icopia-14.2015.30How to use a DOI?
- Particle swarm optimization, fuzzy inference system, premature atrial contraction, electrocardiogram
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.
- © 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/).
Cite this article
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 -