• 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