Improving detection algorithm of life-threatening arrhythmias for implementation of implantable cardioverter-defibrillators

The implantable cardioverter-defibrillator (ICD) is an effective therapeutic device for rescuing patients with cardiac diseases from death caused by life-threatening arrhythmias. The authors previously proposed a detection algorithm of life-threatening arrhythmias with a multiple regression model. To enhance the classification accuracy, in the present study, we have introduced an autoregressive filter and a multiple detection process into the previous detection algorithm. The experimental results showed that the proposed method could attain a high accuracy such that all ventricular fibrillation rhythms could be exactly detected. In addition, detection errors of sinus rhythms or supraventricular tachyarrhythmias provoking the ICD malfunction were reduced.