RT Journal Article
A1 Chaofei Zhang
A1 Wenjun Wang
A1 Chaoyang Chen
A1 Chao Zeng
A1 Dennis E. Anderson
A1 Bo Cheng

PB iet
T1 Determination of optimal electroencephalography recording locations for detecting drowsy driving
JN IET Intelligent Transport Systems
VO 12
IS 5
SP 345
OP 350
AB Early detection of drowsy driving is an important issue for driving safety. Quantitative electroencephalography (EEG) is an attractive method for detecting brain activity changes. However, further study is still needed to evaluate the feasibility of wearable devices that can detect drowsy driving in real-world settings. This study sought to determine whether convenient EEG recording locations are sensitive in detecting brain activity changes associated with drowsy driving and to characterise these EEG changes. Twenty-two healthy adult subjects were recruited to participate in a car-following task using a driving simulator. EEG data were recorded from four locations, two frontals (Fp1, Fp2) and two temporals (T3, T4) of the brain while driving. The results showed that the increase of δ activity, decrease of θ and α activity and a decrease of spectral edge frequency at 90% were found in the drowsy state compared to the alert state (paired t-tests, p < 0.05). Effect sizes for EEG changes were larger at the temporal locations compared to frontal locations. This suggests temporal locations can be feasible recording locations for wearable monitoring devices to detect drowsy driving.
K1 drowsy driving detection
K1 spectral edge frequency
K1 temporal locations
K1 optimal electroencephalography recording location determination
K1 brain activity change detection
K1 wearable monitoring devices
K1 driving simulator
K1 quantitative electroencephalography
K1 paired t-tests
K1 car-following task
K1 EEG
DO https://doi.org/10.1049/iet-its.2017.0083
UL https://digital-library.theiet.org/;jsessionid=1e7p6m7kunkw.x-iet-live-01content/journals/10.1049/iet-its.2017.0083
LA English
SN 1751-956X
YR 2018
OL EN