• DocumentCode
    2428089
  • Title

    A low power biomedical signal processor ASIC based on hardware software codesign

  • Author

    Nie, Z.D. ; Wang, L. ; Chen, W.G. ; Zhang, T. ; Zhang, Y.T.

  • Author_Institution
    Inst. of Biomed. & Health Eng. (IBHE), Shenzhen Inst. of Adv. Technol. (SIAT), Shenzhen, China
  • fYear
    2009
  • fDate
    3-6 Sept. 2009
  • Firstpage
    2559
  • Lastpage
    2562
  • Abstract
    A low power biomedical digital signal processor ASIC based on hardware and software codesign methodology was presented in this paper. The codesign methodology was used to achieve higher system performance and design flexibility. The hardware implementation included a low power 32bit RISC CPU ARM7TDMI, a low power AHB-compatible bus, and a scalable digital co-processor that was optimized for low power Fast Fourier Transform (FFT) calculations. The co-processor could be scaled for 8-point, 16-point and 32-point FFTs, taking approximate 50, 100 and 150 clock circles, respectively. The complete design was intensively simulated using ARM DSM model and was emulated by ARM Versatile platform, before conducted to silicon. The multi-million-gate ASIC was fabricated using SMIC 0.18 mum mixed-signal CMOS 1P6M technology. The die area measures 5,000 mum times 2,350 mum. The power consumption was approximately 3.6 mW at 1.8 V power supply and 1 MHz clock rate. The power consumption for FFT calculations was less than 1.5 % comparing with the conventional embedded software-based solution.
  • Keywords
    application specific integrated circuits; coprocessors; embedded systems; fast Fourier transforms; hardware-software codesign; medical signal processing; ARM DSM model; ARM Versatile platform; ASIC processor; Fast Fourier Transform; biomedical signal processor; design flexibility; embedded software based solution; hardware software codesign; power supply; scalable digital coprocessor; Algorithms; Biomedical Engineering; Computer Simulation; Computers; Equipment Design; Fourier Analysis; Humans; Neural Networks (Computer); Pattern Recognition, Automated; Programming Languages; Signal Processing, Computer-Assisted; Software;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
  • Conference_Location
    Minneapolis, MN
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-3296-7
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2009.5335295
  • Filename
    5335295