Relationship Between Behavioral Measures in a Driving Simulator and EEG Activity on Day-Shift and Night-Shift Workers

Driver fatigue is a concern that demands a closer investigation into ways of detection and populations at risk. This study examined the relationship between EEG activity and several driving behaviors, as well as differences between day-shift and nightshift workers. Twenty adults, five males and ten females between the ages of 18 and 45, participated in this experiment. Participants included 10 day-shift and 10 night-shift workers. Participants were wired for EEG recording and asked to drive in a 1-hour highway-driving scenario in a driving simulator. Relative powers of alpha, theta and beta were recorded and an EEG index of alertness was computed. Driving measures were also examined. Driving measures included lane position variability, speed variability and steering rate. The measures were sampled continuously throughout the task and also grouped into 10-minute blocks. The hypotheses were: 1) a significant positive correlation would be found between EEG measures and the driving measures, such that as alpha and theta powers increased, variability in the driving measures would increase, 2) across time, alpha and theta would increase, as would variability in the driving measures (beta and the EEG index would decrease across time), and 3) night-shift workers would have more increase in alpha and theta and more variability in the driving measures than the day-shift workers. No significant correlations were found between the driving measures and the EEG measures. Moreover, no significant group effect (i.e. between night and day shift) was found on any of the measures. Also, no group by time interaction was found for any of the measures. However, there was a significant time effect for lane position variability and speed variability. Both lane position variability and speed variability increased across time. There was also a significant time effect for alpha activity. Alpha activity increased across time. Because lane position variability and speed variability as well as alpha activity increased across time, perhaps both groups were fatigued. Because no correlations were found between the driving measures and the EEG measures, more research should be conducted before designing in-car detection devices based on driving measures.