Cognitive Workload 8-level arithmetic

UC San Diego 2026 Dataset Open access

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Authors: Matthew Barras, Liam Booth
DOI: 10.82901/nemar.on007262
Cited by: 0
References: 2

Abstract

This dataset contains multimodal recordings from 18 participants performing a mental arithmetic task across eight levels of difficulty, designed to study cognitive workload. It includes 19-channel EEG, ECG, and Pupil Labs eye-tracking (pupillometry) data synchronized via Lab Streaming Layer and converted to BIDS from XDF recordings. Task events encode difficulty ranges based on Q-values, with a 60-second baseline followed by 70 randomized questions.

Fields of Study & Subjects

Human-Automation Interaction and Safety EEG and Brain-Computer Interfaces Emotion and Mood Recognition

Publication details

Journal / source
UC San Diego
Publication date
30 September 2026
Language
EN
Document type
Dataset