Electroencephalogram assessment of mental fatigue in visual search.

Mental fatigue is considered to be a contributing factor responsible for numerous road accidents and various medical conditions and the efficiency and performance could be impaired during fatigue. Hence, determining how to evaluate mental fatigue is very important. In the present study, ten subjects performed a long-term visual search task with electroencephalogram recorded, and self-assessment and reaction time (RT) were combined to verify if mental fatigue had been induced and were also used as confirmatory tests for the proposed measures. The changes in relative energy in four wavebands (δ,θ,α, and β), four ratio formulas [(α+θ)/β,α/β,(α+θ)/(α+β), and θ/β], and Shannon's entropy (SE) were compared and analyzed between the beginning and end of the task. The results showed that a significant increase occurred in alpha activity in the frontal, central, posterior temporal, parietal, and occipital lobes, and a dip occurred in the beta activity in the pre-frontal, inferior frontal, posterior temporal, and occipital lobes. The ratio formulas clearly increased in all of these brain regions except the temporal region, where only α/β changed obviously after finishing the 60-min visual search task. SE significantly increased in the posterior temporal, parietal, and occipital lobes. These results demonstrate some potential indicators for mental fatigue detection and evaluation, which can be applied in the future development of countermeasures to fatigue.

[1]  Carryl L. Baldwin,et al.  Driver fatigue: The importance of identifying causal factors of fatigue when considering detection and countermeasure technologies , 2009 .

[2]  Lynne M. Coventry,et al.  Human Factors , 2010, Handbook of Financial Cryptography and Security.

[3]  J. O'hanlon,et al.  Comparison of Performance and Physiological Changes Between Drivers who Perform Well and Poorly During Prolonged Vehicular Operation , 1977 .

[4]  R. Heinzer,et al.  [Driver fatigue]. , 2007, Revue medicale suisse.

[5]  D de Waard,et al.  Assessing driver status: a demonstration experiment on the road. , 1991, Accident; analysis and prevention.

[6]  Evangelos Bekiaris,et al.  Using EEG spectral components to assess algorithms for detecting fatigue , 2009, Expert Syst. Appl..

[7]  John A. Detre,et al.  Imaging brain fatigue from sustained mental workload: An ASL perfusion study of the time-on-task effect , 2010, NeuroImage.

[8]  John M. Stern,et al.  Atlas of EEG Patterns , 2004 .

[9]  T. Åkerstedt,et al.  Sleepiness on the job: continuously measured EEG changes in train drivers. , 1987, Electroencephalography and clinical neurophysiology.

[10]  H. Heuer,et al.  Frontal theta activity reflects distinct aspects of mental fatigue , 2014, Biological Psychology.

[11]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[12]  Fernando Jaureguizar,et al.  Subjective assessment of the impact of transmission errors in 3DTV compared to HDTV , 2011, 2011 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON).

[13]  Stuart D Baulk,et al.  Awareness of sleepiness when driving. , 2004, Psychophysiology.

[14]  T. Uehata [Karoshi, death by overwork]. , 2005, Nihon rinsho. Japanese journal of clinical medicine.

[15]  Jianping Liu,et al.  EEG-based estimation of mental fatigue by using KPCA-HMM and complexity parameters , 2010, Biomed. Signal Process. Control..

[16]  Liu Xiaoming,et al.  The EEG changes during night-time driver fatigue , 2009, 2009 IEEE Intelligent Vehicles Symposium.

[17]  D. Dinges An overview of sleepiness and accidents , 1995, Journal of sleep research.

[18]  Chongxun Zheng,et al.  Electroencephalogram and electrocardiograph assessment of mental fatigue in a driving simulator. , 2012, Accident; analysis and prevention.

[19]  T. Sejnowski,et al.  Estimating alertness from the EEG power spectrum , 1997, IEEE Transactions on Biomedical Engineering.

[20]  M. Chung,et al.  Electroencephalographic study of drowsiness in simulated driving with sleep deprivation , 2005 .

[21]  Hyung-Chul O. Li,et al.  Method of Measuring Subjective 3D Visual Fatigue: A Five-Factor Model , 2008 .

[22]  Ashley Craig,et al.  Development of an algorithm for an EEG-based driver fatigue countermeasure. , 2003, Journal of safety research.

[23]  S. Kar,et al.  EEG signal analysis for the assessment and quantification of driver’s fatigue , 2010 .

[24]  A. Belyavin,et al.  Changes in electrical activity of the brain with vigilance. , 1987, Electroencephalography and clinical neurophysiology.

[25]  Daniel Aeschbach,et al.  Dynamics of the human EEG during prolonged wakefulness: evidence for frequency-specific circadian and homeostatic influences , 1997, Neuroscience Letters.

[26]  J. Redman,et al.  Temporal profile of prolonged, night‐time driving performance: breaks from driving temporarily reduce time‐on‐task fatigue but not sleepiness , 2011, Journal of sleep research.

[27]  G. Kecklund,et al.  Sleepiness in long distance truck driving: an ambulatory EEG study of night driving. , 1993, Ergonomics.

[28]  R. Ebstein,et al.  Dopaminergic Polymorphisms Associated with Time-on-Task Declines and Fatigue in the Psychomotor Vigilance Test , 2012, PloS one.