Video-oculography

From Wikipedia, the free encyclopedia
Video-oculography examination in progress

Video-oculography (VOG) is a non-invasive, video-based method of measuring horizontal, vertical and torsional position components of the movements of both eyes (eye tracking) using a head-mounted mask that is equipped with small cameras. VOG is usually employed for medical purposes.

Technology[]

The measurement of the horizontal and vertical components is well established technology which uses pupil tracking and/or corneal reflection tracking and has been widely applied, for example for tracking eye movements in reading. In contrast, the measurement of the torsional component (cyclorotation) is usually considered a computationally more difficult task. Approaches to solving this problem include, among others, polar cross correlation methods and iris pattern matching/tracking.[1][2]

In animal studies, VOG has been used in combination with fluorescent marker arrays affixed to the eye, and it has been proposed that such an array could be embedded into a scleral lens for humans.[3]

Use[]

VOG techniques have been put to use in a wide field of scientific research related to visual development and cognitive science as well as to pathologies of the eyes and of the visual system.[citation needed]

For example, miniaturized ocular-videography systems are used to analyze eye movements in freely moving rodents.[4]

VOG can be used in eye examinations for quantitative assessments of ocular motility, binocular vision, vergence, cyclovergence, stereoscopy and disorders related to eye positioning such as nystagmus and strabismus.

It has also been proposed for assessing linear and torsional eye movements in vestibular patients[5][6] and for early stroke recognition.[5][7]

References[]

  1. ^ Kai Schreiber; T. Haslwanter (April 2004). "Improving calibration of 3-D video oculography systems". IEEE Transactions on Biomedical Engineering. 51 (4): 676–679. doi:10.1109/TBME.2003.821025.
  2. ^ See also the brief review on p. 142 of: Americo A. Migliaccio; Hamish G. McDougall; Lloyd B. Minor; Charles C. Della Santina (2005). "Inexpensive system for real-time 3-dimensional video-oculography using a fluorescent marker array". Journal of Neuroscience Methods. 143 (2): 141–150. doi:10.1016/j.jneumeth.2004.09.024. PMC 2767269. PMID 15814146.
  3. ^ Americo A. Migliaccio; Hamish G. McDougall; Lloyd B. Minor; Charles C. Della Santina (2005). "Inexpensive system for real-time 3-dimensional video-oculography using a fluorescent marker array". Journal of Neuroscience Methods. 143 (2): 141–150. doi:10.1016/j.jneumeth.2004.09.024. PMC 2767269. PMID 15814146.
  4. ^ Damian J. Wallace; David S. Greenberg; Juergen Sawinski; Stefanie Rulla; Giuseppe Notaro; Jason N. D. Kerr (6 June 2013). "Rats maintain an overhead binocular field at the expense of constant fusion". Nature. 498 (498): 65–69. doi:10.1038/nature12153.
  5. ^ a b Newman-Toker D.E.; Saber Tehrani A.S.; Mantokoudis G.; Pula J.H.; Guede C.I.; Kerber K.A.; Blitz A.; Ying S.H.; Hsieh Y.H.; Rothman R.E.; Hanley D.F.; Zee D.S.; Kattah J.C. (April 2013). "Quantitative video-oculography to help diagnose stroke in acute vertigo and dizziness: toward an ECG for the eyes". Stroke. 44 (4): 1158–1161. doi:10.1161/STROKEAHA.111.000033. PMC 8448203. PMID 23463752.
  6. ^ Richard E. Gans (May 2001). "Video-oculography: A new diagnostic technology for vestibular patients". The Hearing Journal. 54 (5): 40. doi:10.1097/01.HJ.0000294840.79013.39.
  7. ^ Hopkins Stroke Detector Uses Video-Oculography for Faster Diagnosis, medgadget.com, 7 March 2013 (downloaded 11 July 2013)
Retrieved from ""