DocumentCode :
2715968
Title :
System considerations for the compressive sampling of EEG and ECoG bio-signals
Author :
Gangopadhyay, Daibashish ; Allstot, Emily G. ; Dixon, Anna M R ; Allstot, David J.
Author_Institution :
Dept. of Electr. Eng., Univ. of Washington, Seattle, WA, USA
fYear :
2011
fDate :
10-12 Nov. 2011
Firstpage :
129
Lastpage :
132
Abstract :
Analog domain Compressed Sensing (CS) has enabled dramatic levels of sub-Nyquist sampling of sparse signals in applications such as electrocardiogram (ECG) and electromyogram (EMG) bio-signals. This work describes extensions of CS to electroencephalogram (EEG) and electrocorticogram (ECoG) brain signals. Specifically, the time-, frequency- and wavelet-domain sparsity of these signals is investigated. For EEG/ECoG signals it is shown that the time-and frequency-domain capture essential spike features even at high threshold levels and are useful for coarse EEG/ECoG processing. Wavelet domain can be used for fine processing with signal de-noising properties without using thresholding. CS signal-reconstruction performance for time-, frequency- and wavelet domain (Daubechies, Symlets, Coiflets and Meyer wavelets) are presented along with system design considerations.
Keywords :
electroencephalography; medical signal processing; neurophysiology; signal denoising; wavelet transforms; Coiflet waveletss; Daubechies wavelets; ECoG biosignal compressive sampling; EEG biosignal compressive sampling; Meyer wavelets; Symlets wavelets; analog domain compressed sensing; compressive sensing signal reconstruction; electrocorticogram brain signals; electroencephalogram brain signals; frequency domain capture; frequency domain sparsity; signal denoising; sparse signals; subNyquist sampling; time domain capture; time domain sparsity; wavelet domain sparsity; Compressed sensing; Electroencephalography; Frequency domain analysis; Sensors; Sparse matrices; Wavelet domain; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Circuits and Systems Conference (BioCAS), 2011 IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4577-1469-6
Type :
conf
DOI :
10.1109/BioCAS.2011.6107744
Filename :
6107744
Link To Document :
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