抄録
The implantable cardioverter-defibrillator (ICD) is an effective therapeutic device for rescuing patients with cardiac diseases from death caused by life-threatening arrhythmias. For development of the ICD, it is important to accurately distinguish among normal sinus rhythm, ventricular tachycardia (VT), ventricular fibrillation, and supraventricular tachycardia (SVT) . Thus, in this study, we have proposed a multiple regression model based on 14 indices extracted from two-dimensional statistics of intracardiac electrocardiograms to detect four kinds of cardiac rhythms as accurately and quickly as possible. The experimental results showed that the proposed method had a sensitivity of 0.97 for detecting SVT and a specificity of 0.99 for detecting VT, which were improved respectively from 0.83 and 0.85 obtained from the previous method, and that early detection within about 1.6 seconds was attained.
