Title :
Impact of compressed sensing on clinically relevant metrics for ambulatory ECG monitoring
Author :
Craven, D. ; McGinley, B. ; Kilmartin, L. ; Glavin, M. ; Jones, E.
Author_Institution :
Coll. of Eng. & Inf., Nat. Univ. of Ireland Galway, Galway, Ireland
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.
Keywords :
biomedical electronics; cardiovascular system; compressed sensing; electrocardiography; feature extraction; medical diagnostic computing; medical signal processing; patient monitoring; signal reconstruction; DL application; ECG monitoring CS impact; ECG monitoring compressed sensing impact; ECG signals; HRV-based clinical metrics; QRS feature extraction-based clinical metrics; ambulatory ECG monitoring; ambulatory electrocardiogram monitoring; automatic dictionary creation; clinically relevant ECG monitoring metrics; clinically relevant electrocardiogram monitoring metrics; compression ratio; dictionary creation methods; dictionary learning; electrocardiogram monitoring CS impact; electrocardiogram signals; heart rate variability-based clinical metrics; lossy compression; over-complete dictionaries; patient agnostic dictionary creation method analysis; patient specific dictionary creation method analysis; reconstructed ECG signal analysis; reconstructed electrocardiogram signal analysis;
Journal_Title :
Electronics Letters
DOI :
10.1049/el.2014.4188
