DocumentCode :
862414
Title :
A Fully Integrated Mixed-Signal Neural Processor for Implantable Multichannel Cortical Recording
Author :
Sodagar, A.M. ; Wise, K.D. ; Najafi, K.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI
Volume :
54
Issue :
6
fYear :
2007
fDate :
6/1/2007 12:00:00 AM
Firstpage :
1075
Lastpage :
1088
Abstract :
A 64-channel neural processor has been developed for use in an implantable neural recording microsystem. In the Scan Mode, the processor is capable of detecting neural spikes by programmable positive, negative, or window thresholding. Spikes are tagged with their associated channel addresses and formed into 18-bit data words that are sent serially to the external host. In the Monitor Mode, two channels can be selected and viewed at high resolution for studies where the entire signal is of interest. The processor runs from a 3-V supply and a 2-MHz clock, with a channel scan rate of 64 kS/s and an output bit rate of 2 Mbps
Keywords :
CMOS integrated circuits; bioelectric phenomena; brain; medical signal detection; mixed analogue-digital integrated circuits; neurophysiology; prosthetics; fully integrated mixed-signal neural processor; implantable multichannel cortical recording; implantable neural recording microsystem; neural processor; neural spike detection; programmable negative thresholding; programmable positive thresholding; window thresholding; Bit rate; Circuits; Clocks; Digital signal processing; Implants; Monitoring; Nervous system; Signal processing algorithms; Signal resolution; Telemetry; Biomedical electronics; mixed-signal CMOS circuits; neural recording; spike detection; Animals; Cerebral Cortex; Electrodes, Implanted; Electroencephalography; Equipment Design; Equipment Failure Analysis; Evoked Potentials; Haplorhini; Prostheses and Implants; Signal Processing, Computer-Assisted; Systems Integration; Telemetry;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2007.894986
Filename :
4203028
Link To Document :
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