Open Access

Complexity-Measure-Based Sequential Hypothesis Testing for Real-Time Detection of Lethal Cardiac Arrhythmias

EURASIP Journal on Advances in Signal Processing20062007:020957

Received: 15 June 2006

Accepted: 17 September 2006

Published: 21 December 2006


A novel approach that employs a complexity-based sequential hypothesis testing (SHT) technique for real-time detection of ventricular fibrillation (VF) and ventricular tachycardia (VT) is presented. A dataset consisting of a number of VF and VT electrocardiogram (ECG) recordings drawn from the MIT-BIH database was adopted for such an analysis. It was split into two smaller datasets for algorithm training and testing, respectively. Each ECG recording was measured in a 10-second interval. For each recording, a number of overlapping windowed ECG data segments were obtained by shifting a 5-second window by a step of 1 second. During the windowing process, the complexity measure (CM) value was calculated for each windowed segment and the task of pattern recognition was then sequentially performed by the SHT procedure. A preliminary test conducted using the database produced optimal overall predictive accuracy of . The algorithm was also implemented on a commercial embedded DSP controller, permitting a hardware realization of real-time ventricular arrhythmia detection.


Ventricular TachycardiaVentricular ArrhythmiaVentricular FibrillationAlgorithm TrainingData Segment


Authors’ Affiliations

Department of Electronic Engineering, Chang Gung University, Kwei-Shan, Tao-Yuan, Taiwan


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© Szi-Wen Chen. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.