ABAIS: Affect and Belief Adaptive Interface System

Abstract

We describe an Affect and Belief Adaptive Interface System (ABAIS) designed to compensate for performance biases caused by users' affective states and active beliefs. The ABMS architecture implements an adaptive methodology consisting of four steps: sensing/inferring user affective state and performance relevant beliefs; identifying their potential impact on performance; selecting a compensatory strategy; and implementing this strategy in terms of specific GUI adaptations. ABAIS provides a generic adaptive framework for exploring a variety of user assessment methods (e.g., knowledge based, self reports, diagnostic tasks, physiological sensing), and GUI adaptation strategies (e.g., content and format based). The ABAIS performance bias prediction is based on empirical findings from emotion research, and knowledge of specific task requirements. The initial ABAIS prototype is demonstrated in the context of an Air Force combat task, uses a knowledge based approach to assess the pilot's anxiety level, and modifies selected cockpit instrument displays in response to detected increases in anxiety levels.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1999
Accession Number
ADA373270

Entities

People

  • Eva Hudlicka
  • John Billingsley

Tags

Communities of Interest

  • Air Platforms
  • Biomedical
  • Ground and Sea Platforms
  • Human Systems
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Artificial Intelligence
  • Cognition
  • Cognitive Science
  • Cognitive Systems Engineering
  • Cognitive Workload
  • Computer Programming
  • Computers
  • Health Services
  • Human-Computer Interaction
  • Human-Machine Systems
  • Information Processing
  • Medical Personnel
  • Pattern Recognition
  • Psychology
  • Two Dimensional
  • Warning Systems

Readers

  • Computational Modeling and Simulation
  • Mental Health of Military Veterans with Posttraumatic Stress Disorder (PTSD): Risk Factors, Prevalence, Symptoms, and Treatment.
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML