Energy efficiency is still the obstacle for long-term real-time wireless ECG monitoring. In this paper, a digital compressed sensing-\n(CS-) based single-spot Bluetooth ECG node is proposed to deal with the challenge in wireless ECG application. A periodic\nsleep/wake-up scheme and a CS-based compression algorithm are implemented in a node, which consists of ultra-low-power\nanalog front-end, microcontroller, Bluetooth 4.0 communication module, and so forth. The efficiency improvement and the\nnode�s specifics are evidenced by the experiments using the ECG signals sampled by the proposed node under daily activities of\nlay, sit, stand, walk, and run. Under using sparse binary matrix (SBM), block sparse Bayesian learning (BSBL) method, and\ndiscrete cosine transform (DCT) basis, all ECG signals were essentially undistorted recovered with root-mean-square differences\n(PRDs) which are less than 6%. The proposed sleep/wake-up scheme and data compression can reduce the airtime over energyhungry\nwireless links, the energy consumption of proposed node is 6.53 mJ, and the energy consumption of radio decreases\n77.37%. Moreover, the energy consumption increase caused by CS code execution is negligible, which is 1.3% of the total\nenergy consumption
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