Citation

Zhongze Hu, Yu Sun, Lim J, Thakor N, Bezerianos A. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2015; 2015: 4725-4728.

Copyright

(Copyright © 2015, IEEE (Institute of Electrical and Electronics Engineers))

DOI

10.1109/EMBC.2015.7319449

PMID

26737349

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.

Language: en