Journal: Frontiers in Psychology

Article Title: The Relationship Between Drivers’ Cognitive Fatigue and Speed Variability During Monotonous Daytime Driving

doi: 10.3389/fpsyg.2018.00459

Figure Lengend Snippet: Electroencephalogram (EEG) power spectra for frequencies between 0.5 and 30 Hz during the driving task. Scalp topographies are displayed at the greatest power of delta (0.5∼4 Hz), theta (4∼8 Hz), alpha (8∼13 Hz), and beta (13∼30 Hz) bands for the adaption period, segment 1, segment 2, and segment 3. The delta, theta, and alpha band power shows a positive maximum over the fronto-central electrodes and a negative maximum over bilateral parietal electrodes in each segment, whereas the beta band power shows a positive maximum over the frontal electrodes and a negative maximum over bilateral parietal electrodes.

Article Snippet: Electroencephalogram data were pre-processed using EEGLAB , an open source toolbox running in the MATLAB (v.2010a; The MathWorks, Inc., United States) environment, and in-house MATLAB functions.

Techniques:

Journal: Frontiers in Psychology

Article Title: The Relationship Between Drivers’ Cognitive Fatigue and Speed Variability During Monotonous Daytime Driving

doi: 10.3389/fpsyg.2018.00459

Figure Lengend Snippet: Comparisons of the EEG index between participants with small vs. large variability of speed in three driving segments. Three 15-min driving segments respectively correspond to segment 1, segment 2, and segment 3. Small variability represents participants with small speed variability, whereas large variability represents participants with large speed variability. Data from small and large speed variability groups are marked in black and gray, respectively. Error bars represent the standard errors of the means.

Article Snippet: Electroencephalogram data were pre-processed using EEGLAB , an open source toolbox running in the MATLAB (v.2010a; The MathWorks, Inc., United States) environment, and in-house MATLAB functions.

Techniques: