On ECG Compressed Sensing using Specific Overcomplete Dictionaries

被引：27

作者：

Fira, Monica ^{[1
]}

Goras, Liviu ^{[1
,2
]}

Barabasa, Constantin ^{[2
]}

Cleju, Nicolae ^{[2
]}

机构：

[1] Romanian Acad, Inst Comp Sci, Iasi 700054, Romania

[2] Gheorghe Asachi Tech Univ Iasi, Iasi 700506, Romania

来源：

ADVANCES IN ELECTRICAL AND COMPUTER ENGINEERING | 2010年 / 10卷 / 04期

关键词：

Compressed sensing; Biomedical signal processing; Electrocardiography; Pursuit algorithms; Signal processing algorithms; WAVELET COMPRESSION; SIGNAL COMPRESSION; CLASSIFICATION; ALGORITHM; VECTOR;

D O I：

10.4316/AECE.2010.04004

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The paper presents a number of results regarding the construction of specific overcomplete dictionaries for ECG compressed sensing (CS). The dictionaries were built using normal and patological cardiac patterns extracted from 24 recordings of the MIT-BIH Arrhythmia Database. It has been shown that the compression results obtained using the CS concept based on specific dictionaries are better that those using the wavelet overcomplete dictionaries. Starting from the concept of sparse signal with respect to a given overcomplete dictionary the paper present several results regarding the possibility of simple pattern classification as well.

引用

页码：23 / 28

页数：6

共 36 条

[1] A novel compression algorithm for electrocardiogram signals based on the linear prediction of the wavelet coefficients [J].