Peer-Reviewed Journal Details
Mandatory Fields
Craven, D,McGinley, B,Kilmartin, L,Glavin, M,Jones, E
2015
March
Ieee Journal Of Biomedical And Health Informatics
Compressed Sensing for Bioelectric Signals: A Review
Published
WOS: 49 ()
Optional Fields
Bioelectric signal compression body area networks (BAN) compressed sensing (CS) electrocardiogram (ECG) electroencephalography (EEG) INFORMATION ANALOG ECG RECONSTRUCTION RECOVERY DESIGN
19
529
540
This paper provides a comprehensive review of compressed sensing or compressive sampling (CS) in bioelectric signal compression applications. The aim is to provide a detailed analysis of the current trends in CS, focusing on the advantages and disadvantages in compressing different biosignals and its suitability for deployment in embedded hardware. Performance metrics such as percent root-mean-squared difference (PRD), signal-to-noise ratio (SNR), and power consumption are used to objectively quantify the capabilities of CS. Furthermore, CS is compared to state-of-the-art compression algorithms in compressing electrocardiogram (ECG) and electroencephalography (EEG) as examples of typical biosignals. The main technical challenges associated with CS are discussed along with the predicted future trends.
10.1109/JBHI.2014.2327194
Grant Details
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