• DocumentCode
    2599687
  • Title

    Automatic modeling based on cultural programming for osseointegration diagnosis

  • Author

    Arpaia, P. ; Clemente, Fabrizio ; Manna, Carlo ; Montenero, G.

  • Author_Institution
    Dipt. di Ing., Univ. del Sarmio, Benevento, Italy
  • fYear
    2009
  • fDate
    5-7 May 2009
  • Firstpage
    1274
  • Lastpage
    1277
  • Abstract
    The problem of modeling equivalent circuits for interpreting Electrical Impedance Spectroscopy (EIS) data in monitoring osseointegration level of metallic implants in bone is faced by means of an evolutionary programming approach based on cultural algorithms. With respect to state-of-the-art gene expression programming, the information on search advance acquired by most promising individuals during the evolution is shared with the entire population of potential solutions and stored also for next generations. Experimental results of the application such cultural programming-based analytical modeling to in-vitro EIS measurements of bone in-growth around metallic implants during prosthesis osseointegration are presented.
  • Keywords
    artificial intelligence; biomedical measurement; bone; electric impedance measurement; equivalent circuits; evolutionary computation; genetics; medical computing; orthopaedics; prosthetics; EIS data; artificial intelligence; automatic modeling; bone implant; cultural programming; electrical impedance spectroscopy; evolutionary programming approach; metallic implant; osseointegration diagnosis; prosthesis; state-of-the-art gene expression programming; Analytical models; Automatic programming; Bones; Cultural differences; Electrochemical impedance spectroscopy; Equivalent circuits; Gene expression; Genetic programming; Implants; Monitoring; Artificial Intelligence; Circuit modeling; Data analysis Impedance measurements;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Instrumentation and Measurement Technology Conference, 2009. I2MTC '09. IEEE
  • Conference_Location
    Singapore
  • ISSN
    1091-5281
  • Print_ISBN
    978-1-4244-3352-0
  • Type

    conf

  • DOI
    10.1109/IMTC.2009.5168651
  • Filename
    5168651