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DSESP: Dual sparsity estimation subspace pursuit for the compressive sensing based close-loop ecg monitoring structure

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Abstract

Compressive Sensing based ECG collecting system is an effective way for long time heart disease monitoring because of its precision as well as energy efficiency. Traditional Compressive Sensing methods are open-loop and the coordinator cannot obtain the recovery quality, which will impact the diagnosis results based on the recovered data. In this paper, a novel close-loop structure is designed for wireless ECG monitoring, which can maintain the recovery quality and the energy efficiency at a high level. Moreover, an improved Subspace Pursuit recovery method is designed to optimize the recovery quality. Simulations are made to prove that the recovery method is more efficient than most state-of-art recovery algorithm. Finally, an experimental testbed is built for evaluate the whole monitoring system. The results show that the recovery error can be controlled within the medical request while the energy efficiency can be improved by 12%.

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Acknowledgments

This work was supported by National Key Research and Development Program of China (2016YFB090190), National Natural Science Foundation of China (61803261), Shanghai Natural Science Foundation of China (18ZR1421100).

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Correspondence to Wenbin Yu.

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This article is part of the Topical Collection: Special Issue on Big Data and Smart Computing in Network Systems

Guest Editors: Jiming Chen, Kaoru Ota, Lu Wang, and Jianping He

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Yu, W., Chen, C., Liu, Z. et al. DSESP: Dual sparsity estimation subspace pursuit for the compressive sensing based close-loop ecg monitoring structure. Peer-to-Peer Netw. Appl. 12, 1311–1322 (2019). https://doi.org/10.1007/s12083-019-00731-5

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  • DOI: https://doi.org/10.1007/s12083-019-00731-5

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