A Real-time Unconstrained EEG-Classifier for Mental Workload Monitoring

@inproceedings{Osia2025,
title = {A Real-time Unconstrained EEG-Classifier for Mental Workload Monitoring},
author = {Ali Osia and Zeynab Tahamtan and Lin Zhao and Mahdi Davari and Mikael Nybacka},
editor = {Andras Kemeny and Jean-Rémy Chardonnet and Florent Colombet and Stéphane Espié},
doi = {https://doi.org/10.82157/dsa/2025/3},
isbn = {978-2-9573777-7-0},
year  = {2025},
date = {2025-09-24},
booktitle = {Proceedings of the Driving Simulation Conference 2025 Europe XR},
pages = {29-36},
address = {Stuttgart, Germany},
organization = {Driving Simulation Association},
abstract = {Real-time monitoring of mental workload (MWL) is critical for designing adaptive human-machine systems. This study introduces a subject-independent and task-independent EEG classifier trained on spectral power ratios (delta, theta, alpha, beta) from frontal, parietal, and occipital regions. Using a controlled arithmetic task with labeled difficulty levels (easy/hard), a Gaussian Naive Bayes model achieved 75.4% accuracy (LOSOCV) in distinguishing MWL states. Validated in a driving simulator, the model was highly sensitive to task difficulties and detected higher MWL in urban (overload) vs. rural (underload) scenarios (p < 0.05), aligning with NASA-TLX subjective ratings. Temporal analysis revealed declining MWL over time in both scenarios, reflecting cognitive adaptation, followed by a mental fatigue rise in the cumulative effect of prolonged cognitive effort during the overload scenario. The framework eliminates the need for individualized and task calibration, offering a scalable solution for real-world applications like automotive safety and virtual reality. By bridging controlled lab settings and naturalistic environments, this work advances EEG-based MWL monitoring for adaptive systems in high-stakes domains like driving and aviation.},
keywords = {},
}

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TY  - CONF
TI  - A Real-time Unconstrained EEG-Classifier for Mental Workload Monitoring
AU  - Osia, Ali
AU  - Tahamtan, Zeynab
AU  - Zhao, Lin
AU  - Davari, Mahdi
AU  - Nybacka, Mikael
C1  - Stuttgart, Germany
C3  - Proceedings of the Driving Simulation Conference 2025 Europe XR
DA  - 2025/09/24
PY  - 2025
SP  - 29
EP  - 36
LA  - en-US
PB  - Driving Simulation Association
SN  - 978-2-9573777-7-0
L2  - https://proceedings.driving-simulation.org/proceeding/dsc-2025/a-real-time-unconstrained-eeg-classifier-for-mental-workload-monitoring
ER  - 

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