DocumentCode :
51038
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
Volume :
50
Issue :
18
fYear :
2014
fDate :
August 28 2014
Firstpage :
1271
Lastpage :
1273
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;
fLanguage :
English
Journal_Title :
Electronics Letters
Publisher :
iet
ISSN :
0013-5194
Type :
jour
DOI :
10.1049/el.2014.1749
Filename :
6888557
Link To Document :
بازگشت