Complexity measure revisited: a new algorithm for classifying cardiac arrhythmias

Author

Ayesta, U. ; Serrano, L. ; Romero, I.

Author_Institution

Dept. of Electr. & Electron. Eng., Public Univ. of Navarra, Pamplona, Spain

Volume

2

fYear

2001

fDate

2001

Firstpage

1589

Abstract

This paper deals to the suitability of complexity measure of ECG signals for the classification of cardiac arrhythmia´s. Applying this algorithm to data from the MIT-BIH database a very poor performance, especially for SR signals, and an overall error rate of 20% is obtained. In this study a novel measure, named SPDR, sample percentage in the dynamic range, to be used in combination with the complexity measure algorithm, is proposed. Using this novel proposal the result of the classification is improved decreasing the overall error rate until to 9%. The algorithm has been implemented in a computer using LabView and C++ software.

Keywords

computational complexity; electrocardiography; filtering theory; medical signal processing; sequential estimation; signal classification; time-domain analysis; ECG signals; MIT-BIH database; biomedical signal processing; cardiac arrhythmias classification; complexity measure; malignant ventricular arrhythmias; normal sinus rhythm; sample percentage in dynamic range; simple learning machine; time analysis algorithms; Biomedical measurements; Databases; Dynamic range; Electrocardiography; Error analysis; Frequency; Proposals; Rhythm; Signal processing algorithms; Strontium;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE

ISSN

1094-687X

Print_ISBN

0-7803-7211-5

Type

conf

DOI

10.1109/IEMBS.2001.1020515

Filename

1020515