• DocumentCode
    642703
  • Title

    Analysis of myoelectric signals using a Field Programmable SoC

  • Author

    Borbely, Bence J. ; Kineses, Zoltan ; Vorohazi, Zsolt ; Nagy, Zsolt ; Szolgay, Peter

  • Author_Institution
    Fac. of Inf. Technol., Pazmany Peter Catholic Univ., Budapest, Hungary
  • fYear
    2013
  • fDate
    8-12 Sept. 2013
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    A platform design for the analysis of human myoelectric signals (MES) is presented. Offline recorded multichannel signals of forearm muscles are processed with a Field Programmable SoC in order to classify different movement patterns to control human-assisting electromechanical systems with multiple degrees of freedom (e.g. a prosthetic hand). Benchmark results of an ANSI C implementation are shown to assess the raw performance of the built-in ARM cores of the SoC. Possible computational bottlenecks are located based on the results and custom hardware implementations are shown to fully utilize the flexibility and performance of the used hardware platform.
  • Keywords
    electromyography; field programmable gate arrays; microprocessor chips; pattern recognition; system-on-chip; ANSI C implementation; ARM cores; field programmable SoC; forearm muscles; human myoelectric signals; offline recorded multichannel signals; Field programmable gate arrays; Process control; System-on-chip; Time-domain analysis; Training; Vector processors; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuit Theory and Design (ECCTD), 2013 European Conference on
  • Conference_Location
    Dresden
  • Type

    conf

  • DOI
    10.1109/ECCTD.2013.6662255
  • Filename
    6662255