Impact of compressed sensing on clinically relevant metrics for ambulatory ECG monitoring

被引：16

作者：

Craven, D. ^{[1
]}

McGinley, B. ^{[1
]}

Kilmartin, L. ^{[1
]}

Glavin, M. ^{[1
]}

Jones, E. ^{[1
]}

机构：

[1] Natl Univ Ireland Galway, Coll Engn & Informat, Galway, Ireland

来源：

ELECTRONICS LETTERS | 2015年 / 51卷 / 04期

关键词：

Compressed sensing;

D O I：

10.1049/el.2014.4188

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Recent research has examined the combination of compressed sensing with over-complete dictionaries for the lossy compression of electrocardiogram (ECG) signals. The application of dictionary learning to automatically create the dictionary is described. A novel analysis of the reconstructed signals using a range of clinical metrics based around QRS feature extraction and heart rate variability is employed. Two methods for dictionary creation are proposed: patient specific and patient agnostic. A detailed comparison of each approach is described. Considering ambulatory ECG monitoring as an application, each methodology is analysed for a wide range of compression ratios.

引用

页码：323 / 324

页数：2

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