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Related Experiment Video

Updated: Nov 2, 2025

Recording Horizontal Saccade Performances Accurately in Neurological Patients Using Electro-oculogram

Recording Horizontal Saccade Performances Accurately in Neurological Patients Using Electro-oculogram

Published on: March 13, 2018

Evaluation of eyestrain with vertical electrooculogram.

Shuai Li¹, Dongmei Hao¹, Bing Liu²

¹Faculty of Environment and Life, Beijing University of Technology, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China.

Computer Methods and Programs in Biomedicine

|June 8, 2021

Summary

Analyzing vertical electrooculogram (VEOG) signals effectively evaluates digital eyestrain. Increased high-frequency VEOG power and blink features indicate worsening eyestrain from prolonged screen use.

Keywords:

Evaluation Eyestrain Feature Vertical electrooculogram (VEOG)

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Area of Science:

Ophthalmology
Neuroscience
Human-Computer Interaction

Background:

Digital eyestrain is a growing concern due to increased computer and smartphone use.
Accurate evaluation of eyestrain is crucial for prevention and relief strategies.

Purpose of the Study:

To evaluate digital eyestrain by analyzing vertical electrooculogram (VEOG) signals.
To identify specific VEOG signal features correlated with eyestrain severity.

Main Methods:

21 participants watched videos for 120 minutes, with VEOG signals recorded using three electrodes.
VEOG data was segmented into 30-minute phases, extracting VEOG signal power probability (VEOGSPP) and blink features.
Blink features analyzed included blink number, group blinks, blink amplitude, and blink duration parameters.

Main Results:

Significant increases in high-frequency VEOGSPP (0.8-6.3Hz), blink number (BN), group blinks number (GBN), and group blinks ratio (GBR) were observed with eyestrain.
Significant decreases in low-frequency VEOGSPP (0.1-0.4Hz), mean blink amplitude (Mean_BA), mean opening duration (Mean_OD), and mean late 50% opening duration (Mean_ODL50) correlated with eyestrain.
Statistical significance was determined at P<0.05.

Conclusions:

VEOG signal analysis provides a reliable method for evaluating eyestrain induced by prolonged screen exposure.
Specific changes in VEOGSPP and blink characteristics serve as indicators of digital eyestrain.