• DocumentCode
    2549129
  • Title

    A low power merge cell processor for real-time spike sorting in implantable neural prostheses

  • Author

    Linderman, Michael D. ; Meng, Teresa H.

  • Author_Institution
    Stanford Univ., CA
  • fYear
    2006
  • fDate
    21-24 May 2006
  • Lastpage
    4109
  • Abstract
    Extremely low power consumption is the critical constraint for designing implantable neural decoders that interface directly with the nervous system. Typically a system with such strict constraints is implemented as an ASIC; however, the rapid progress in the field mandates a more flexible solution. In this paper we introduce a new general architecture, the Merge Framework, and its low power implementation for real-time spike sorting in cortical control applications, that offers a flexible and powerful programming model with near ASIC power efficiency
  • Keywords
    low-power electronics; program processors; prosthetics; sorting; ASIC power efficiency; cortical control applications; flexible programming model; implantable neural decoders; implantable neural prostheses; low power consumption; low power merge cell processor; nervous system; powerful programming model; real-time spike sorting; Application specific integrated circuits; Bandwidth; Informatics; Merging; Pattern recognition; Personal communication networks; Power system modeling; Prosthetics; Sorting; Timing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 2006. ISCAS 2006. Proceedings. 2006 IEEE International Symposium on
  • Conference_Location
    Island of Kos
  • Print_ISBN
    0-7803-9389-9
  • Type

    conf

  • DOI
    10.1109/ISCAS.2006.1693532
  • Filename
    1693532