• DocumentCode
    1706973
  • Title

    A 0.45V 100-channel neural-recording IC with sub-µW/channel consumption in 0.18µm CMOS

  • Author

    Dong Han ; Yuanjin Zheng ; Rajkumar, R. ; Dawe, G. ; Minkyu Je

  • Author_Institution
    Nanyang Technol. Univ., Singapore, Singapore
  • fYear
    2013
  • Firstpage
    290
  • Lastpage
    291
  • Abstract
    Conventional neural-recording systems face limitations in simultaneously achieving a good NEF and low power consumption [1-4]. This is because the input amplifier current consumption is dictated by an input-referred noise requirement that determines the system sensitivity, while the supply voltage is determined by a DR requirement at the analog recording chain output that limits the maximum achievable resolution of the A-to-D conversion. In this paper, a power-efficient neural-recording architecture using a DR-folding technique is presented to enable low-voltage operation without compromising the DR performance. The proposed architecture can operate with only half of the typically required supply voltage, which results in about 50% power reduction.
  • Keywords
    CMOS analogue integrated circuits; amplifiers; analogue-digital conversion; integrated circuit noise; low-power electronics; 100-channel neural-recording IC; A-to-D conversion; CMOS; DR performance; DR requirement; DR-folding technique; NEF; analog recording chain output; channel consumption; face limitation; input amplifier current consumption; input-referred noise requirement; low power consumption; low-voltage operation; neural-recording system; power reduction; power-efficient neural-recording architecture; size 0.18 mum; supply voltage; system sensitivity; voltage 0.45 V; CMOS integrated circuits; Educational institutions; Noise; Noise measurement; Power demand; Solid state circuits;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Solid-State Circuits Conference Digest of Technical Papers (ISSCC), 2013 IEEE International
  • Conference_Location
    San Francisco, CA
  • ISSN
    0193-6530
  • Print_ISBN
    978-1-4673-4515-6
  • Type

    conf

  • DOI
    10.1109/ISSCC.2013.6487739
  • Filename
    6487739