The Eye is the Window to Working Memory: How to Improve Multitasking Decisions Using Eye Data

Abstract

Interruption management systems have as a goal to defer interruptions to a moment of low workload for the user, minimizing the costs of interruptions, and reducing risks. In this research we have explored whether eye-data can serve as a basis for such a decision. Exploring multiple datasets and paradigms we found that such a system is feasible, assuming alterations in workload are not too rapid. The most successful classifier is based on the boosted tree algorithm, leading to a classification accuracy of 74 percent.

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Document Details

Document Type
Technical Report
Publication Date
Jan 21, 2019
Accession Number
AD1087804

Entities

People

  • Hagit Shaposhnik
  • Jelmer P Borst
  • Niels A. Taatgen

Tags

Communities of Interest

  • Air Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Abstracts
  • Accuracy
  • Air Force
  • Air Force Research Laboratories
  • Air Traffic
  • Aircrafts
  • Airplanes
  • Availability
  • Classification
  • Cognitive Science
  • Contracts
  • Eye
  • Instructions
  • Machine Learning
  • Supervised Machine Learning
  • Traffic
  • Workload

Fields of Study

  • Computer science

Readers

  • Circadian Sleep-Wake Regulation and Chronobiology
  • Database Systems and Applications
  • Life Cycle Cost Analysis