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

Edward Jones; Liam Kilmartin; M. Glavin

doi:10.1049/el.2014.4188

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

Electrical & Electronic Engineering

University of Galway

Research output: Contribution to a Journal (Peer & Non Peer) › Article › peer-review

16 Citations (Scopus)

Abstract

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.

Original language	English (Ireland)
Pages (from-to)	323-325
Number of pages	2
Journal	Electronics Letters
Volume	51
Issue number	4
DOIs	https://doi.org/10.1049/el.2014.4188
Publication status	Published - 1 Feb 2015

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Authors
Craven, D,McGinley, B,Kilmartin, L,Glavin, M,Jones, E

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10.1049/el.2014.4188

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

Abstract

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