Embedded real-time QRS detection algorithm for pervasive cardiac care system

The emergence and development of pervasive computing technology leads to the revolution of remote cardiac care and also brings forth challenges to the automatic ECG diagnosis (AED) techniques. Due to the high resource requirements, traditional AED methods are unsuitable for pervasive cardiac care (PCC) applications. This paper proposes an embedded real-time QRS detection algorithm dedicated to PCC systems. By analyzing QRS complex under PCC environments, this algorithm establishes the correction mechanism of motion artifacts, presents the QRS complex detection algorithm based on the linear time-domain statistical analysis and syntactic analysis. Currently, this algorithm has been implemented and evaluated on the PCC system for more than 30 patients in the CHU hospital of Clermont-Ferrand (France) and the MIT-BIH cardiac arrhythmias database. The overall results, average 99.5% sensitivity and 99.7% specificity, show its high performance.