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.
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