Information-enhanced sparse binary matrix in compressed sensing for ECG

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

    Research output: Contribution to journalArticlepeer-review

    8 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 languageEnglish
    Pages (from-to)1271-1273
    Number of pages3
    JournalElectronics Letters
    Volume50
    Issue number18
    DOIs
    Publication statusPublished - 2014

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