• DocumentCode
    720681
  • Title

    A new method to detect nystagmus for vertigo diagnosis system by eye movement velocity

  • Author

    Charoenpong, Theekapun ; Pattrapisetwong, Preeyanan ; Mahasitthiwat, Visan

  • Author_Institution
    Fac. of Med., Srinakharinwirot Univ., Thailand
  • fYear
    2015
  • fDate
    18-22 May 2015
  • Firstpage
    174
  • Lastpage
    177
  • Abstract
    As vertigo is common disease, it causes by problem with Nystagmus. It is difficult to diagnosis by observation. In this paper, we propose a method to detect nystagmus for vertigo diagnosis system using eye movement velocity. This method consists of three main steps: pupil extraction, velocity of eye movement computation, and nystagmus detection. An infrared camera is used to record eye movement in image sequence format. For first step, pupil is primary extracted by an adaptive threshold, blackest blob, and ellipse fitting technique. For second step, we measures pupil position from its center. Velocity of eye movement is then computed. For third step, involuntary eye movement is detected by comparing velocity of eye movement in each frame with a criterion. To evaluate performance of the proposed method, eye movement is recorded from six subjects. Accuracy rate of involuntary eye movement detection is 87.21%. The results show that the performance of this method is satisfactory. This is first method able to detect nystagmus from video-oculography.
  • Keywords
    biomedical optical imaging; cameras; diseases; eye; image sequences; medical image processing; adaptive threshold; disease; eye movement computation; eye movement velocity; image sequence; infrared camera; involuntary eye movement; nystagmus detection; pupil extraction; vertigo diagnosis system; video-oculography; Accuracy; Algorithm design and analysis; Cameras; Diseases; Fitting; Image processing; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Vision Applications (MVA), 2015 14th IAPR International Conference on
  • Conference_Location
    Tokyo
  • Type

    conf

  • DOI
    10.1109/MVA.2015.7153161
  • Filename
    7153161