Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Ultra-Reliable and Low-Latency Wireless Hierarchical Federated Learning: Performance Analysis.

Entropy (Basel, Switzerland)·2024
Same author

Secrecy Capacity Region of the AWGN MAC with External Eavesdropper and Feedback.

Entropy (Basel, Switzerland)·2023
Same author

Utility-Privacy Trade-Off in Distributed Machine Learning Systems.

Entropy (Basel, Switzerland)·2022
Same author

New Result on the Feedback Capacity of the Action-Dependent Dirty Paper Wiretap Channel.

Entropy (Basel, Switzerland)·2021
Same author

A Capacity-Achieving Feedback Scheme of the Gaussian Multiple-Access Channel with Degraded Message Sets.

Entropy (Basel, Switzerland)·2021
Same author

Feedback Schemes for the Action-Dependent Wiretap Channel with Noncausal State at the Transmitter.

Entropy (Basel, Switzerland)·2020
Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026
Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026
Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026
Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026
Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026
Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Oct 2, 2025

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
08:15

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

Published on: March 28, 2025

803

Object Selection as a Biometric.

Joyce Tlhoolebe1,2, Bin Dai1,3

  • 1School of Information Science and Technology, Southwest Jiaotong University, Chengdu 610031, China.

Entropy (Basel, Switzerland)
|February 25, 2022
PubMed
Summary
This summary is machine-generated.

Eye movement biometrics offer a novel authentication method, addressing limitations of traditional techniques. This study demonstrates unique identification through eye movement patterns, showing promising results for enhanced security systems.

Keywords:
biometric authenticationbiometricseye trackingmachine learningpattern recognitionsaccades

More Related Videos

Author Spotlight: An Accurate and Quantitative Approach to Study Visual Feature Selectivity of the Optokinetic Reflex in Mice
09:28

Author Spotlight: An Accurate and Quantitative Approach to Study Visual Feature Selectivity of the Optokinetic Reflex in Mice

Published on: June 23, 2023

3.1K
A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences
08:33

A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences

Published on: September 4, 2019

7.1K

Related Experiment Videos

Last Updated: Oct 2, 2025

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
08:15

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

Published on: March 28, 2025

803
Author Spotlight: An Accurate and Quantitative Approach to Study Visual Feature Selectivity of the Optokinetic Reflex in Mice
09:28

Author Spotlight: An Accurate and Quantitative Approach to Study Visual Feature Selectivity of the Optokinetic Reflex in Mice

Published on: June 23, 2023

3.1K
A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences
08:33

A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences

Published on: September 4, 2019

7.1K

Area of Science:

  • Biometrics
  • Human-Computer Interaction
  • Computer Science

Background:

  • Traditional authentication methods like passwords and tokens present security vulnerabilities.
  • Biometric authentication utilizes unique physical or behavioral characteristics for identification.
  • Eye movement analysis emerges as a novel biometric modality.

Purpose of the Study:

  • To propose and evaluate a biometric authentication system based on eye movement patterns.
  • To develop a method for creating unique user templates from eye movement data.
  • To assess the performance of eye movement biometrics in terms of accuracy and reliability.

Main Methods:

  • Collected eye movement data from twenty participants during object selection tasks using eye-tracking equipment.
  • Developed a model to generate unique binary signatures (templates) from observed eye movement data.
  • Implemented error correction and template security using matrix multiplication.
  • Utilized Hamming distance for enhanced verification.

Main Results:

  • Individuals could be uniquely identified using their eye movement features.
  • The proposed model demonstrated promising performance metrics.
  • The use of Hamming distance significantly improved the model's performance.
  • Achieved 37% False Rejection Rate (FRR) and 27% False Acceptance Rate (FAR) over 400 trials.

Conclusions:

  • Eye movement biometrics represent a viable and unique method for user identification.
  • The proposed system shows potential for future development in secure authentication.
  • Further improvements are expected to enhance the accuracy and reduce error rates.