EYE-CARE: Eye Tracking for Context-Adaptive Systems Based on Activity and Cognitive Load Prediction
Type
conference contribution
Date Issued
2026-06-01
Author(s)
Abstract
With the growing amount of digital data, the importance of systems
that allow humans to exploit such data to obtain insightful
interpretations has skyrocketed. Recent context-adaptive systems
can provide users with assistance by proactively sensing, tracking,
and interacting with them in a seamless, user friendly, and privacy
preserving manner. For example, in an industrial or educational
setting, such a system can detect when a user is challenged and
provide adequate support (e.g., by highlighting task-relevant information
that remains beyond the user’s attention). To maintain such
adaptations, a real-time assessment of the user’s cognitive state
and behavior are required. Such assessments can be addressed in
multiple ways. One particular way to understand user behavior
is to assess their visual perception through gaze-enabled systems.
This half day tutorial will enable participants to analyze an existing
human-activity recognition pipeline that is trained with an exiting
eye movement dataset. The participants will be encouraged to build
groups and discuss how this pipeline (as a proxy environment) can
be extended (e.g., with multi-modal interaction or large language
models) towards providing users with feedback that is potentially
useful in a broad spectrum of personal and professional activities.
that allow humans to exploit such data to obtain insightful
interpretations has skyrocketed. Recent context-adaptive systems
can provide users with assistance by proactively sensing, tracking,
and interacting with them in a seamless, user friendly, and privacy
preserving manner. For example, in an industrial or educational
setting, such a system can detect when a user is challenged and
provide adequate support (e.g., by highlighting task-relevant information
that remains beyond the user’s attention). To maintain such
adaptations, a real-time assessment of the user’s cognitive state
and behavior are required. Such assessments can be addressed in
multiple ways. One particular way to understand user behavior
is to assess their visual perception through gaze-enabled systems.
This half day tutorial will enable participants to analyze an existing
human-activity recognition pipeline that is trained with an exiting
eye movement dataset. The participants will be encouraged to build
groups and discuss how this pipeline (as a proxy environment) can
be extended (e.g., with multi-modal interaction or large language
models) towards providing users with feedback that is potentially
useful in a broad spectrum of personal and professional activities.
Language
English (United States)
Keywords
Eye tracking
human activity recognition
context-adaptive systems
workload
tutorial
HSG Classification
contribution to scientific community
Refereed
Yes
Subject(s)
Division(s)
File(s)![Thumbnail Image]()
Name
EYE_CARE__Tutorial_ETRA_2026.pdf
Size
381.96 KB
Format
Adobe PDF
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