A novel, batch modular learning approach for ECG beat classification

Author

Mani, Vijay P. ; Hu, Yu Hen ; Palreddy, Surekha

Author_Institution

Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA

Volume

2

fYear

1998

fDate

12-15 May 1998

Firstpage

1093

Abstract

We investigate a modular architecture for ECG beat classification. The feature space is divided into distinct regions and individual classifiers are developed for each region. We compare different combination strategies, and feature space partition strategies. We also describe a novel, batch modular learning method that can be used to incrementally improve the performance of the modular network

Keywords

electrocardiography; feature extraction; learning (artificial intelligence); medical signal processing; parallel architectures; pattern classification; vector quantisation; ECG beat classification; LVQ; batch modular learning; batch modular learning method; classifiers; clustering based approach; feature space partition; fuzzy combination strategies; learning vector quantization; modular architecture; modular network performance; premature ventricular contraction; random based approach; Artificial neural networks; Computer architecture; Drives; Electrocardiography; Heart rate variability; Machine learning; Morphology; Parallel processing; Rhythm; Terminology;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on

Conference_Location

Seattle, WA

ISSN

1520-6149

Print_ISBN

0-7803-4428-6

Type

conf

DOI

10.1109/ICASSP.1998.675459

Filename

675459