High - Resolution QRS detection algorithm for wireless ECG systems based on compressed sensing theory

Abstract

Wireless electrocardiogram (ECG) systems are responsible to collect and transmit the vital signals of cardiac patients wirelessly to medical centers for diagnostic and therapeutic purposes. ECG is a noninvasive technique widely used in health care systems for diagnosis of heart diseases. However, the use of conventional ECG system is restricted by patient's mobility and the system's transmission capacity, and physical size. Aforementioned highlights the need and advantage of wireless ECG systems with low sampling-rate and low power consumption. With this in mind, Compressed Sensing (CS) procedure as a new sampling approach and the collaboration of wireless ECG framework is used to provide a robust high-resolution QRS detection algorithm in the hospitals and medical centers with high probability and enough accuracy. Advanced wireless ECG systems based on our approach will be able to deliver healthcare not only to patients in hospitals and medical centers; but also at their homes and workplaces thus offering cost saving, and improving the quality of life. Our simulation results for two records of ECG signals show an increment of 10% for sensitivity as well as 12% for the prediction level and good detection accuracy. The proposed algorithm also achieves significantly better detection rate in comparison with Empirical Mode Decomposition (EMD) method.