Automatic discrimination of arrhythmia waveforms using fuzzy logic

Author

Sugiura, Toshifumi ; Hirata, Hisashi ; Harada, Yukio ; Kazui, Teruhisa

Author_Institution

Res. Inst. of Electron., Shizuoka Univ., Hamamatsu, Japan

fYear

1998

fDate

29 Oct-1 Nov 1998

Firstpage

108

Abstract

A method was proposed for discrimination of ventricular arrhythmias using fuzzy logic. The classifier uses four features of ECG waveforms; amplitude variation ratio, interval variation ratio, peak sharpness, QRS complex width, and assigns each waveform a number of 0-100. The performance of the algorithm was evaluated on the surface and intracardiac electrocardiograms of ventricular tachycardia (VT), ventricular fibrillation (VF) and normal sinus rhythm (NSR) in mongrel dogs. NSRs were evaluated 90-100 while VFs less than 10. VTs were assigned the numbers of 30-75. An automatic detection and defibrillation experiment was performed with this algorithm

Keywords

electrocardiography; feature extraction; fuzzy logic; medical signal processing; pattern classification; signal classification; waveform analysis; ECG waveforms; QRS complex width; algorithm performance; amplitude variation ratio; arrhythmia waveforms; automatic discrimination; feature extraction; fuzzy logic; interval variation ratio; intracardiac electrocardiograms; mongrel dogs; morphology classification; normal sinus rhythm; peak sharpness; surface electrocardiograms; ventricular arrhythmias; ventricular fibrillation; ventricular tachycardia; Automatic control; Biomedical monitoring; Defibrillation; Dogs; Electric shock; Electric variables control; Electrocardiography; Fuzzy logic; Performance evaluation; Surface morphology;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 1998. Proceedings of the 20th Annual International Conference of the IEEE

Conference_Location

Hong Kong

ISSN

1094-687X

Print_ISBN

0-7803-5164-9

Type

conf

DOI

10.1109/IEMBS.1998.745839

Filename

745839