Fatigue is a constant occupational hazard for drivers and it greatly reduces efficiency and performance when one persists in continuing the current activity. Studies have investigated various ...physiological associations with fatigue to try to identify fatigue indicators. The current study assessed the four electroencephalography (EEG) activities, delta (δ), theta (θ), alpha (α) and beta (β), during a monotonous driving session in 52 subjects (36 males and 16 females). Performance of four algorithms, which were: algorithm (i) (θ+α)/β, algorithm (ii) α/β, algorithm (iii) (θ+α)/(α+β), and algorithm (iv) θ/β, were also assessed as possible indicators for fatigue detection. Results showed stable delta and theta activities over time, a slight decrease of alpha activity, and a significant decrease of beta activity (p<0.05). All four algorithms showed an increase in the ratio of slow wave to fast wave EEG activities over time. Algorithm (i) (θ+α)/β showed a larger increase. The results have implications for detecting fatigue.
Impact on industry: The results of this research have the implication for detecting fatigue and can be used for future development of fatigue countermeasure devices.
This study investigated the changes in electroencephalography (EEG) activity in train drivers during a monotonous train-driving session. Four combinations of EEG activities were also compared to ...investigate the difference in performance of these equations. The four equations tested were equation 1 (θ/β), equation 2 (θ/(α+β)), equation 3 ((θ+α)/β), and equation 4 ((θ+α)/(α+β)). A total of fifty male train drivers were recruited to perform a 30-min monotonous train-driving task while 2-channels of EEG (frontal and temporal) were recorded. At the frontal site, significant differences were found for theta (p=0.045) and alpha (0.0001) activities, and at the temporal site, significant differences were found for delta (p=0.007) and theta (0.01) activities. For the average of frontal and temporal site activities, significant differences were found for delta (p=0.004), theta (p=0.001), and beta (p=0.048). Significant difference were found for temporal site for equation 1 (θ/β) (p=0.04), and equation 4 ((θ+α)/(α+β)) (p=0.02), and for the average of frontal and temporal site activities, significant differences were found for all four equations (equation 1 (p=0.001), equation 2 (p=0.006), equation 3 (p=0.04), and equation 4 (p=0.002)). These findings can be utilised as a potential fatigue indicator.
The current study investigated the effect of monotonous driving on inter-hemispheric electroencephalography (EEG) coherence. Twenty-four non-professional drivers were recruited to perform a fatigue ...instigating monotonous driving task while 30 channels of EEG were simultaneously recorded. The EEG recordings were then divided into 5 equal sections over the entire driving period for analysis. Inter-hemispheric coherence was computed from 5 homologous EEG electrode pairs (FP1–FP2, C3–C4, T7–T8, P7–P8, and O1–O2) for delta, theta, alpha and beta frequency bands. Results showed that frontal and occipital inter-hemispheric coherence values were significantly higher than central, parietal, and temporal sites for all four frequency bands (
p
<
0.0001). In the alpha frequency band, significant difference was found between earlier and later driving sections (
p
=
0.02). The coherence values in all EEG frequency bands were slightly increased at the end of the driving session, except for FP1–FP2 electrode pair, which showed no significant change in coherence in the beta frequency band at the end of the driving session.
Electroencephalography (EEG) can be used as an
indicator of fatigue. Several studies have shown that
slow wave brain activities, delta (0-4 Hz) and theta (4-
8 Hz), increase as an individual becomes ...fatigued,
while the fast brain activities, alpha (8-13 Hz) and beta
(13-35 Hz), decrease. However, an EEG is a complex
piece of equipment that is generally used in laboratory
based studies. In order to develop a fatigue
countermeasure device for train drivers using EEG,
there is a need for a simple and wireless EEG monitor.
This paper explains the development of a single
channel wireless EEG device.
Train accidents can have a massive impact towards the surrounding area as well as the general community. Most train accidents can be attributed to fatigue, and hence, development of fatigue ...countermeasure devices that can warn drivers of fatigue status and prevent accidents can greatly benefit train drivers, passengers, society and general community. Electroencephalography (EEG) has been proven to be one of the most reliable indicators of fatigue. This study investigated the change of brain activity during fatigue-instigating monotonous driving session, by extracting the four frequency components (delta, theta, alpha, and beta) using FFT spectral analysis at different brain sites (frontal, central, temporal, parietal, and occipital). Results identified some statistically significant differences between early and later stages of driving in delta, theta and beta activities at different brain sites. The results of the current study may be used for future development of fatigue countermeasure by targeting specific frequency component and brain sites.
Electroencephalography (EEG) can be used as an indicator of fatigue. Several studies have shown that slow wave brain activities, delta (0-4 Hz) and theta (4-8 Hz), increase as an individual becomes ...fatigued, while the fast brain activities, alpha (8-13 Hz) and beta (13-35 Hz), decrease. However, an EEG is a complex piece of equipment that is generally used in laboratory based studies. In order to develop a fatigue countermeasure device for train drivers using EEG, there is a need for a simple and wireless EEG monitor. This paper explains the development of a single channel wireless EEG device.
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