• DocumentCode
    1598155
  • Title

    Artificial neural network-based estimation of the eyeball position using the magnetic contact lens sensing technique

  • Author

    Lee, Seung Yup ; Kim, Keun Young ; Kim, Hee Chan

  • Author_Institution
    Seoul Nat. Univ.
  • fYear
    2005
  • fDate
    6/27/1905 12:00:00 AM
  • Firstpage
    7766
  • Lastpage
    7768
  • Abstract
    We have created an artificial neural network based approach for measuring eye movement using a magnetic contact lens sensing technique. The sensor array is based on using four magnetoresistive sensors. A two-layer feed-forward artificial neural network was used and an artificial eyeball model was made for the test. The neural network is trained with sample data obtained from nine spots. After training, we compared the position calculated from the developed system with the real one. The result shows that there is a good linear relationship between them. This indicates the developed system is capable of recording the position of the eyeball with a high degree of accuracy
  • Keywords
    biomagnetism; biomechanics; contact lenses; eye; feedforward neural nets; magnetic sensors; magnetoresistive devices; medical signal processing; eye movement; eyeball position estimation; magnetic contact lens sensing technique; magnetoresistive sensors; sensor array; two-layer feedforward artificial neural network; Artificial neural networks; Biomedical engineering; Biomedical measurements; Biosensors; Lenses; Magnetic field measurement; Magnetic sensors; Magnetoresistance; Sensor arrays; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
  • Conference_Location
    Shanghai
  • Print_ISBN
    0-7803-8741-4
  • Type

    conf

  • DOI
    10.1109/IEMBS.2005.1616313
  • Filename
    1616313