BALLADEER: Multimodal Neurophysiological Data for ADHD Research

BALLADEER integrates EEG, eye tracking, and physiological signals from children and adolescents with ADHD and neurotypical controls. Its controlled protocol uses gamified cognitive tasks like Attention Slackline and CogniFit to elicit responses in attentional control and cognitive flexibility. This dataset supports the development of machine learning models for ADHD classification and the research of digital biomarkers.

Use Cases

• ADHD classification based on integrated EEG, eye-tracking, and physiological signal features
• Cross-modal analysis exploring the interplay between EEG dynamics and autonomic nervous system activity
• Validation of digital biomarkers for objective ADHD assessment derived from attentional task performance
• Research into cognitive flexibility and response inhibition using data from gamified tasks like Attention Robots

Strengths

• Multimodal integration of EEG, eye tracking, and physiological signals, enabling rich cross-modal analysis
• Data collected via a controlled experimental protocol with specific cognitive tasks (e.g., Attention Slackline)
• Publicly available under a permissive CC-BY-4.0 license, enhancing transparency and reproducibility

Limitations

• Column names and exact row counts are not provided, limiting precise understanding of data structure
• The stated last update date (2026-04-17) is in the future, creating uncertainty about data currency

Provenance

Source

Juan Trujillo

Collection Method

Collected using a controlled experimental protocol involving gamified cognitive and attentional tasks.

Freshness

Last updated: 2026-04-17 09:13:11