Eye Movement and EEG Data for Mind Wandering Detection Across Age Groups

251 participants across four studies provide data on eye movement behavior and EEG signals during tasks designed to induce mind wandering. Xiaoru Teng's PhD thesis data includes young adults, older adults, and people with dementia in laboratory and real-world settings. The dataset was last updated on June 1, 2026.

Use Cases

• Train classifiers to detect mind wandering based on eye movement patterns across different task types.
• Compare cognitive aging effects on attention indicators using data from young and older adults.
• Validate laboratory findings in a clinical context using data from dementia patients during virtual therapy.
• Develop multimodal models for engagement prediction by combining eye movement and EEG data from motor imitation tasks.

Strengths

• Includes data from 251 total participants across four distinct studies.
• Covers multiple age groups: 84 young adults, 34 older adults, and 78 older adults with dementia.
• Compares laboratory findings with real-world clinical data from virtual Cognitive Stimulation Therapy.
• Contains multimodal data from Study 4, combining eye movements and EEG signals.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect bias inherent to the specific experimental tasks and participant cohorts.

Provenance

Source

Xiaoru Teng

Collection Method

Experimental data collected from participants performing cognitive and motor tasks.

Freshness

Last updated 2026-06-01 01:48:11