title: Investigating the correlation between the neural activity and task performance in a psychomotor vigilance test.
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.
authors.forename: Zhongze
authors.initials: Z
authors.lastname: Hu
authors.forename: Yu
authors.initials: Y
authors.lastname: Sun
authors.forename: Julian
authors.initials: J
authors.lastname: Lim
authors.forename: Nitish
authors.initials: N
authors.lastname: Thakor
authors.forename: Anastasios
authors.initials: A
authors.lastname: Bezerianos
mesh_terms: D001288:Attention / Q000502:physiology; D058256:Brain Waves; D062207:Brain-Computer Interfaces; D004569:Electroencephalography / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D005222:Mental Fatigue / Q000503:physiopathology; D008954:Models, Biological; D008959:Models, Neurological; D033281:Nontherapeutic Human Experimentation; D011597:Psychomotor Performance / Q000502:physiology*; D011930:Reaction Time / Q000502:physiology*; D012044:Regression Analysis; D013647:Task Performance and Analysis; D055815:Young Adult