• DocumentCode
    2931206
  • Title

    SigMate: A MATLAB-based neuronal signal processing tool

  • Author

    Mahmud, Mufti ; Bertoldo, Alessandra ; Girardi, Stefano ; Maschietto, Marta ; Vassanelli, Stefano

  • Author_Institution
    Dept. of Human Anatomy & Physiol., Univ. of Padova, Padova, Italy
  • fYear
    2010
  • fDate
    Aug. 31 2010-Sept. 4 2010
  • Firstpage
    1352
  • Lastpage
    1355
  • Abstract
    Advances in neuronal probe technology to record brain activity have posed a significant challenge in performing necessary processing and analysis of the recorded data. To be able to infer meaningful conclusions from the recorded signals through these probes, sophisticated signal processing and analysis tools are required. This paper presents a MATLAB-based novel tool, `SigMate´, capable of performing various processing and analysis incorporating the available standard tools and our in-house custom tools. The present features include, data display (2D and 3D), baseline correction, stimulus artifact removal, noise characterization, file operations (file splitter, file concatenator, and file column rearranger), latency estimation, determination of cortical layer activation order, spike detection, spike sorting, and are gradually growing. This tool has been tested extensively for the recordings using the standard micropipettes as well as implantable neural probes based on EOSFETs (Electrolyte-Oxide-Semiconductor Field Effect Transistors) and will be made available to the community shortly.
  • Keywords
    bioelectric phenomena; brain; estimation theory; field effect transistors; mathematics computing; medical signal detection; medical signal processing; neurophysiology; noise; prosthetics; EOSFET; MATLAB; SigMate; baseline correction; brain activity; cortical layer activation order; data display; electrolyte oxide semiconductor field effect transistors; file column rearranger; file concatenator; file splitter; implantable neural probes; in-house custom tools; latency estimation; micropipettes; neuronal probe technology; neuronal signal processing; noise characterization; spike detection; spike sorting; stimulus artifact removal; Estimation; Graphical user interfaces; Noise; Software packages; Sorting; Three dimensional displays; Neuronal signal analysis; Neuronal signal processing; local field potentials; neuronal activity; signal analysis software; Action Potentials; Algorithms; Animals; Neurons; Programming Languages; Rats; Signal Processing, Computer-Assisted; Software;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
  • Conference_Location
    Buenos Aires
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-4123-5
  • Type

    conf

  • DOI
    10.1109/IEMBS.2010.5626747
  • Filename
    5626747