Information-enhanced sparse binary matrix in compressed sensing for ECG

Kan Luo; Zhigang Wang; Jianqing Li; R. Yanakieva; A. Cuschieri

doi:10.1049/el.2014.1749

Information-enhanced sparse binary matrix in compressed sensing for ECG

Kan Luo, Zhigang Wang, Jianqing Li, R. Yanakieva, A. Cuschieri

Research output: Contribution to journal › Article › peer-review

14 Citations (Scopus)

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.

Original language	English
Pages (from-to)	1271-1273
Number of pages	3
Journal	Electronics Letters
Volume	50
Issue number	18
DOIs	https://doi.org/10.1049/el.2014.1749
Publication status	Published - 2014

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10.1049/el.2014.1749

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title = "Information-enhanced sparse binary matrix in compressed sensing for ECG",

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.",

author = "Kan Luo and Zhigang Wang and Jianqing Li and R. Yanakieva and A. Cuschieri",

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AU - Yanakieva, R.

AU - Cuschieri, A.

PY - 2014

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AB - 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.

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Information-enhanced sparse binary matrix in compressed sensing for ECG

Abstract

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