Title :
Information-enhanced sparse binary matrix in compressed sensing for ECG
Author :
Kan Luo ; Zhigang Wang ; Jianqing Li ; Yanakieva, R. ; Cuschieri, Alfred
Author_Institution :
Sch. of Instrum. Sci. & Eng., Southeast Univ., Nanjing, China
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.
Keywords :
compressed sensing; electrocardiography; entropy; medical signal processing; sparse matrices; ECG signal; IESBM; compressed sensing; high-quality recovery; information entropy; information-enhanced sparse binary matrix; signal compression;
Journal_Title :
Electronics Letters
DOI :
10.1049/el.2014.1749