Title :
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
fDate :
29 Oct-1 Nov 1998
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;
Conference_Titel :
Engineering in Medicine and Biology Society, 1998. Proceedings of the 20th Annual International Conference of the IEEE
Conference_Location :
Hong Kong
Print_ISBN :
0-7803-5164-9
DOI :
10.1109/IEMBS.1998.745839
