Real-Time Automatic ECG Diagnosis Method Dedicated to Pervasive Cardiac Care

DOI: 10.4236/wsn.2009.14034   PDF   HTML     7,182 Downloads   12,488 Views   Citations


Recent developments of the wireless sensor network will revolutionize the way of remote monitoring in dif-ferent domains such as smart home and smart care, particularly remote cardiac care. Thus, it is challenging to propose an energy efficient technique for automatic ECG diagnosis (AED) to be embedded into the wireless sensor. Due to the high resource requirements, classical AED methods are unsuitable for pervasive cardiac care (PCC) applications. This paper proposes an embedded real-time AED algorithm dedicated to PCC sys-tems. This AED algorithm consists of a QRS detector and a rhythm classifier. The QRS detector adopts the linear time-domain statistical and syntactic analysis method and the geometric feature extraction modeling technique. The rhythm classifier employs the self-learning expert system and the confidence interval method. Currently, this AED algorithm has been implemented and evaluated on the PCC system for 30 patients in the Gabriel Monpied hospital (CHRU of Clermont-Ferrand, France) and the MIT-BIH cardiac arrhythmias da-tabase. The overall results show that this energy efficient algorithm provides the same performance as the classical ones.

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H. ZHOU, K. HOU and D. ZUO, "Real-Time Automatic ECG Diagnosis Method Dedicated to Pervasive Cardiac Care," Wireless Sensor Network, Vol. 1 No. 4, 2009, pp. 276-283. doi: 10.4236/wsn.2009.14034.

Conflicts of Interest

The authors declare no conflicts of interest.


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