A high reliability detection algorithm for wireless ECG systems based on compressed sensing theory

Wireless Body Area Networks (WBANs) consist of small intelligent biomedical wireless sensors attached on or implanted in the body to collect vital biomedical data from the human body providing Continuous Health Monitoring Systems (CHMS). The WBANs promise to be a key element in wireless electrocardiogram (ECG) systems for next-generation. ECG signals are widely used in health care systems as a noninvasive technique for diagnosis of heart conditions. However, the use of conventional ECG system is restricted by patient´s mobility, 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 from Shannon Energy Transformation (SET) and Peak Finding Schemes (PFS) is used to provide a robust low-complexity detection algorithm in gateways and access points 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 show an increment of 0.1 % for sensitivity as well as 1.5% for the prediction level and detection accuracy.