Performance Evaluation of Compressive Sensing Technique for ECG Signal in WBAN

Karthik.N.B, Rajashekar.K

Abstract: Wireless Body Area Network (WBAN) is a class of Wireless Sensor Network (WSN). WBAN consists Biomedical Wireless Sensors (BWs) ; these BWs sense the vital signals from human bodyandtransmitthrough Gateway (GW) to access point (APs) at hospital for therapeutic and diagnostic purposes. Electrocardiogram (ECG) signals are commonly used for healthcare centers of WBAN; it generatesbioelectric currentwaveformsof heart rhythmand specifies underlying heart diseases. WBAN suffer some problems arelimited storage capacity; processing; power; time; transmission and sampling rate. Compressed sensing (CS) with Block Sparse Bayesian Learning (BSBL) techniques used to improvements of these parameters. Furthermore; performance evaluation of ECG monitoring shows that cost saving and improving the quality. The simulation result performsthe good quality of Signal-to-Noise Ratio (SNR) increaseswhile Percentage in Root-mean-square Difference (PRD) decreases.

Keywords: ECG Signal, Compressed Sensing, Dynamic Thresholding Approach, Block Sparse Bayesian learning

How to Cite?: Karthik.N.B, Rajashekar.K, "Performance Evaluation of Compressive Sensing Technique for ECG Signal in WBAN", Volume 3 Issue 6, June 2014, International Journal of Science and Research (IJSR), Pages: 2585-2588, https://www.ijsr.net/getabstract.php?paperid=2014872, DOI: https://dx.doi.org/10.21275/2014872