Title :
Live demonstration: A closed loop Compressive Sensing neural recording system
Author :
Jie Zhang ; Tao Xiong ; Mitra, S. ; Yuanming Suo ; Tran, T.D. ; Firat Yazicioglu, R. ; Etienne-Cummings, R.
Author_Institution :
Johns Hopkins Univ., Baltimore, MD, USA
Abstract :
A complete neural recording ASIC based on Compressive Sensing (CS) is demonstrated. Implemented using efficient digital circuit, this CS technique is able to achieve 10 times data compression while consuming only 0.83uW (@0.53VDD) additional digital power per electrode. Since CS performance is strongly signal dependent, the ASIC has been tested with standard public database. The characteristic spikes and inter-spike data can be recovered while guarantee >95% spike classification success rate. The complete signal processing circuit consumes <;16uW/electrode.
Keywords :
application specific integrated circuits; biomedical electronics; closed loop systems; compressed sensing; data compression; digital circuits; medical signal processing; neurophysiology; CS technique; closed loop compressive sensing neural recording system; complete neural recording ASIC; data compression; digital circuit; live demonstration; power 0.83 muW; signal processing circuit; standard public database; Application specific integrated circuits; Compressed sensing; Dictionaries; Electrodes; Shape; Signal processing algorithms; Standards;
Conference_Titel :
Biomedical Circuits and Systems Conference (BioCAS), 2014 IEEE
Conference_Location :
Lausanne
DOI :
10.1109/BioCAS.2014.6981673
