DocumentCode :
1380905
Title :
Embedded Neural Recording With TinyOS-Based Wireless-Enabled Processor Modules
Author :
Farshchi, Shahin ; Pesterev, Aleksey ; Nuyujukian, Paul ; Guenterberg, Eric ; Mody, Istvan ; Judy, Jack W.
Author_Institution :
Lux Capital Manage., New York, NY, USA
Volume :
18
Issue :
2
fYear :
2010
fDate :
4/1/2010 12:00:00 AM
Firstpage :
134
Lastpage :
141
Abstract :
To create a wireless neural recording system that can benefit from the continuous advancements being made in embedded microcontroller and communications technologies, an embedded-system-based architecture for wireless neural recording has been designed, fabricated, and tested. The system consists of commercial-off-the-shelf wireless-enabled processor modules (motes) for communicating the neural signals, and a back-end database server and client application for archiving and browsing the neural signals. A neural-signal-acquisition application has been developed to enable the mote to either acquire neural signals at a rate of 4000 12-bit samples per second, or detect and transmit spike heights and widths sampled at a rate of 16670 12-bit samples per second on a single channel. The motes acquire neural signals via a custom low-noise neural-signal amplifier with adjustable gain and high-pass corner frequency that has been designed, and fabricated in a 1.5-??m CMOS process. In addition to browsing acquired neural data, the client application enables the user to remotely toggle modes of operation (real-time or spike-only), as well as amplifier gain and high-pass corner frequency.
Keywords :
CMOS integrated circuits; amplifiers; biomedical electronics; biomedical measurement; medical signal detection; neurophysiology; CMOS process; TinyOS-based wireless-enabled processor modules; archiving; back-end database server; browsing; client application; commercial-off-the-shelf wireless-enabled processor modules; communications technology; embedded microcontroller; embedded neural recording; embedded-system-based architecture; high-pass corner frequency; low-noise neural-signal amplifier; neural signals; neural-signal-acquisition application; size 1.5 mum; wireless neural recording system; Biomedical electronics; embedded sensor; low-power circuit design; neural amplifier; unit detection; Amplifiers, Electronic; Animals; Brain; Computer Systems; Electric Impedance; Electrodes, Implanted; Electronics; Equipment Design; Hippocampus; Mice; Mice, Inbred C57BL; Microcomputers; Signal Processing, Computer-Assisted; Software;
fLanguage :
English
Journal_Title :
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1534-4320
Type :
jour
DOI :
10.1109/TNSRE.2009.2039606
Filename :
5378630
Link To Document :
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