Fetal electrocardiogram extraction based on independent component analysis and quantum particle swarm optimizer algorithm.
- Author:
Yanqin DU
1
;
Hua HUANG
Author Information
1. Department of Medical Information Engineering, School of Electrical Engineering and Information, Sichuan University, Chengdu 610065, China.
- Publication Type:Journal Article
- MeSH:
Algorithms;
Electrocardiography;
methods;
Fetal Heart;
physiology;
Humans;
Principal Component Analysis;
Quantum Theory;
Signal Processing, Computer-Assisted
- From:
Journal of Biomedical Engineering
2011;28(5):941-945
- CountryChina
- Language:Chinese
-
Abstract:
Fetal electrocardiogram (FECG) is an objective index of the activities of fetal cardiac electrophysiology. The acquired FECG is interfered by maternal electrocardiogram (MECG). How to extract the fetus ECG quickly and effectively has become an important research topic. During the non-invasive FECG extraction algorithms, independent component analysis(ICA) algorithm is considered as the best method, but the existing algorithms of obtaining the decomposition of the convergence properties of the matrix do not work effectively. Quantum particle swarm optimization (QPSO) is an intelligent optimization algorithm converging in the global. In order to extract the FECG signal effectively and quickly, we propose a method combining ICA and QPSO. The results show that this approach can extract the useful signal more clearly and accurately than other non-invasive methods.
