• DocumentCode
    184454
  • Title

    An efficient VLSI implementation of SVD processor of on-line recursive ICA for real-time EEG system

  • Author

    Wai-Chi Fang ; Jui-Chung Chang ; Kuan-Ju Huang ; Chih-Wei Feng ; Chia-Ching Chou

  • Author_Institution
    Dept. of Electr. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
  • fYear
    2014
  • fDate
    22-24 Oct. 2014
  • Firstpage
    73
  • Lastpage
    76
  • Abstract
    This paper presents an efficient VLSI implementation of a singular value decomposition (SVD) processor of on-line recursive independent component analysis (ORICA) for use in a real-time electroencephalography (EEG) system. ICA is a well-known method for blind source separation (BBS), which helps to obtain clear EEG signals without artifacts. In general, computations of ORICA are complicated and the critical computational latency is associated with the SVD process. Accordingly, the performance of the SVD processor should be prioritized. Going beyond previous research [1], this work presents a novel design of coordinate rotation digital computer (CORDIC) engine which is optimized and speeded up to avoid structural hazards. Finally, the processor is fabricated using TSMC 40nm CMOS technology in a 16-channel EEG system. The computation time of the SVD processor is reduced by 24.7% and the average correlation coefficient between original source signals and extracted ORICA signals is 0.95452.
  • Keywords
    VLSI; digital arithmetic; electroencephalography; independent component analysis; medical signal processing; singular value decomposition; CMOS technology; CORDIC engine; ORICA computation; SVD processor; VLSI implementation; blind source separation; coordinate rotation digital computer; electroencephalography; independent component analysis; online recursive ICA; real time EEG system; singular value decomposition processor; Accuracy; Conferences; Electroencephalography; Engines; Hardware; Real-time systems; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Circuits and Systems Conference (BioCAS), 2014 IEEE
  • Conference_Location
    Lausanne
  • Type

    conf

  • DOI
    10.1109/BioCAS.2014.6981648
  • Filename
    6981648