Information-enhanced sparse binary matrix in compressed sensing for ECG

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Abstract

An information-enhanced sparse binary matrix (IESBM) is proposed to improve the quality of the recovered ECG signal from compressed sensing. With the detection of the area of interest and the enhanced measurement model, the IESBM increases the information entropy of the compressed signal and preserves more information during compression; thus, it guarantees a high-quality recovery. The experimental results indicate that the proposed matrix is suitable for compressed sensing of the ECG signal with small distortions in both overall and the concerned diagnostic segments. © The Institution of Engineering and Technology 2014.

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Luo, K., Wang, Z., Li, J., Yanakieva, R., & Cuschieri, A. (2014). Information-enhanced sparse binary matrix in compressed sensing for ECG. Electronics Letters, 50(18), 1271–1273. https://doi.org/10.1049/el.2014.1749

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