@article{ref1,
title="Investigating the correlation between the neural activity and task performance in a psychomotor vigilance test",
journal="Conference proceedings - IEEE engineering in medicine and biology society",
year="2015",
author="Zhongze Hu,  and Yu Sun,  and Lim, Julian and Thakor, Nitish and Bezerianos, Anastasios",
volume="2015",
number="",
pages="4725-4728",
abstract="Neural activity is known to correlate with decrements in task performance as individuals enter the state of mental fatigue which might lead to lowered productivity and increased safety risks. Incorporating a passive brain computer interface (BCI) technique that detects changes in subject's neural activity and predicts the behavioral performance when the subject is underperforming might be a promising approach to reduce human error in real-world situations. Here, we developed a reliable model using EEG power spectrum to estimate time-on-task performance in a psychomotor vigilance test (PVT) which can fit across individuals. High correlation between the estimated and actual reaction time was achieved. Hence, our results illustrate the feasibility for modeling time-on-task decrements in performance among different individuals from their brainwave activity, with potential applications in several domains, including traffic and industrial safety.<p /> <p>Language: en</p>",
language="en",
issn="1557-170X",
doi="10.1109/EMBC.2015.7319449",
url="http://dx.doi.org/10.1109/EMBC.2015.7319449"
}