Title :
Feature Extraction for ECG Time-Series Mining Based on Chaos Theory
Author :
Jovic, Alan ; Bogunovic, Nikola
Author_Institution :
Rudjer Boskovic Inst., Zagreb
Abstract :
Chaos theory applied to ECG feature extraction is presented in this article. Several chaos methods, including phase space and attractors, correlation dimension, spatial filling index, central tendency measure and approximate entropy are explained in detail. A new feature extraction environment called ECG chaos extractor has been created in order to apply these chaos methods. System model and program functions are presented. Some of the obtained results are listed. Future work in this field of research is discussed.
Keywords :
chaos; correlation methods; data mining; electrocardiography; entropy; feature extraction; medical signal processing; time series; ECG chaos extractor; ECG time-series mining; approximate entropy; attractors; central tendency measure; correlation dimension; feature extraction; phase space; spatial filling index; Biological system modeling; Chaos; Electrocardiography; Extraterrestrial measurements; Feature extraction; Heart; Laboratories; Principal component analysis; Psychology; Statistical analysis; ECG analysis; chaos theory; feature extraction;
Conference_Titel :
Information Technology Interfaces, 2007. ITI 2007. 29th International Conference on
Conference_Location :
Cavtat
Print_ISBN :
953-7138-10-0
Electronic_ISBN :
1330-1012
DOI :
10.1109/ITI.2007.4283745
