System considerations for the compressive sampling of EEG and ECoG bio-signals

• Published in: 2011 IEEE Biomedical Circuits and Systems Conference (BioCAS) pp. 129 - 132
• Main Authors: Gangopadhyay, D., Allstot, E. G., Dixon, A. M. R., Allstot, D. J.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-11-2011
• Subjects: Compressed sensing; Electroencephalography; Frequency domain analysis; Sensors; Sparse matrices; Wavelet domain; Wavelet transforms
• ISBN: 9781457714696; 1457714698
• ISSN: 2163-4025; 2766-4465
• DOI: 10.1109/BioCAS.2011.6107744

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.