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Related Experiment Video

Updated: May 25, 2026

Video-oculography in Mice
09:43

Video-oculography in Mice

Published on: July 19, 2012

Robust video-oculography for non-invasive autonomic nerve quantification.

Masaru Kiyama1, Hitoshi Iyatomi, Koichi Ogawa

  • 1Faculty of Engineering, Hosei University, 3-7-2 Kajino-cho Koganei, 184-8522 Tokyo, Japan.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|January 19, 2012
PubMed
Summary

This study introduces a new, accurate method for measuring pupil size transitions using video-oculography. This technique improves disease severity quantification and early detection for conditions like Alzheimer's disease.

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Area of Science:

  • Biomedical Engineering
  • Ophthalmology
  • Neuroscience

Background:

  • Autonomic nervous system activity correlates with depression and Alzheimer's disease.
  • Quantifying autonomic nerves aids in disease severity assessment and early detection.
  • Video-oculography offers non-invasive pupil response measurement but faces challenges like eyelid overlap and blinking.

Purpose of the Study:

  • To develop a robust and accurate method for measuring pupil size transitions.
  • To overcome limitations of current video-oculography techniques in pupil area measurement.

Main Methods:

  • Developed a novel method incorporating an active contour model for interpolation.
  • Utilized ellipse estimation with reliable contour point selection.
  • Applied the method to analyze 8,518 image frames from 30 movies.

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Related Experiment Videos

Last Updated: May 25, 2026

Video-oculography in Mice
09:43

Video-oculography in Mice

Published on: July 19, 2012

Quantification of Visual Feature Selectivity of the Optokinetic Reflex in Mice
09:28

Quantification of Visual Feature Selectivity of the Optokinetic Reflex in Mice

Published on: June 23, 2023

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Multispectral Optoacoustic Tomography for Functional Imaging in Vascular Research

Published on: June 8, 2022

Main Results:

  • Achieved high accuracy in pupil area extraction.
  • Demonstrated precision of 98.3% and recall of 98.9% on average.
  • The method proved robust against common artifacts like eyelid overlap and blinking.

Conclusions:

  • The developed method offers a significant improvement for accurate pupil size transition measurement.
  • This advancement can enhance the utility of video-oculography in clinical practice for neurological and psychiatric conditions.
  • Improved pupil measurement accuracy supports better disease monitoring and early diagnosis.