DocumentCode :
2102926
Title :
Signal agnostic compressive sensing for Body Area Networks: Comparison of signal reconstructions
Author :
Casson, A.J. ; Rodriguez-Villegas, Esther
Author_Institution :
Dept. of Electr. & Electron. Eng., Imperial Coll. London, London, UK
fYear :
2012
fDate :
Aug. 28 2012-Sept. 1 2012
Firstpage :
4497
Lastpage :
4500
Abstract :
Compressive sensing is a lossy compression technique that is potentially very suitable for use in power constrained sensor nodes and Body Area Networks as the compression process has a low computational complexity. This paper investigates the reconstruction performance of compressive sensing when applied to EEG, ECG, EOG and EMG signals; establishing the performance of a signal agnostic compressive sensing strategy that could be used in a Body Area Network monitoring all of these. The results demonstrate that the EEG, ECG and EOG can all be reconstructed satisfactorily, although large inter- and intra- subject variations are present. EMG signals are not well reconstructed. Compressive sensing may therefore also find use as a novel method for the identification of EMG artefacts in other electro-physiological signals.
Keywords :
body area networks; data compression; electro-oculography; electrocardiography; electroencephalography; electromyography; medical signal detection; medical signal processing; signal reconstruction; BAN monitoring; ECG signals; EEG signals; EMG artefacts; EMG signals; EOG signals; body area networks; electrophysiological signals; lossy compression technique; power constrained sensor nodes; reconstruction performance; signal agnostic compressive sensing; signal reconstruction; Body area networks; Compressed sensing; Data compression; Electrocardiography; Electroencephalography; Electromyography; Electrooculography; Algorithms; Artifacts; Computer Communication Networks; Data Compression; Diagnosis, Computer-Assisted; Electrodiagnosis; Humans; Monitoring, Ambulatory; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location :
San Diego, CA
ISSN :
1557-170X
Print_ISBN :
978-1-4244-4119-8
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/EMBC.2012.6346966
Filename :
6346966
Link To Document :
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