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：
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.
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页码：323 / 324
页数：2
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