DocumentCode :
2152232
Title :
From compressive to adaptive sampling of neural and ECG recordings
Author :
Alvarado, Alexander Singh ; Príncipe, José C.
Author_Institution :
Electr. & Comput. Eng. Dept., Univ. of Florida, Gainesville, FL, USA
fYear :
2011
fDate :
22-27 May 2011
Firstpage :
633
Lastpage :
636
Abstract :
The miniaturization required for interfacing with the brain demands new methods of transforming neuron responses (spikes) into digital representations. The sparse nature of neural recordings is evident when represented in a shift invariant basis. Although a compressive sensing (CS) framework may seem suitable in reducing the data rates, we show that the time varying sparsity in the signals makes it difficult to apply. Furthermore, we present an adaptive sampling scheme which takes advantage of the local characteristics of the neural spike trains and electrocardiograms (ECG). In contrast to the global constraints imposed in CS our solution is sensitive to the local time structure of the input. The simplicity in the design of the integrate-and-fire (IF) make it a viable solution in current brain machine interfaces (BMI) and ambulatory cardiac monitoring.
Keywords :
brain-computer interfaces; electrocardiography; medical signal processing; signal representation; signal sampling; time-varying systems; ECG recording; adaptive sampling; ambulatory cardiac monitoring; brain machine interface; compressive sensing; digital representation; electrocardiogram; integrate-and-fire design; neural recording; neural spike trains; neuron response; signal sparsity; time varying sparsity; Accuracy; Compressed sensing; Electrocardiography; Modulation; Neurons; Quantization; Sparse matrices; Adaptive sampling; ECG; brain-machine interface; integrate-and-fire model; non-uniform sampling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
Conference_Location :
Prague
ISSN :
1520-6149
Print_ISBN :
978-1-4577-0538-0
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2011.5946483
Filename :
5946483
Link To Document :
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