Detecting drowsiness in drivers, especially multi-level drowsiness, is a difficult problem that
is often approached using neurophysiological signals as the basis for building a reliable …

Developing reliable and user-friendly electroencephalography (EEG) electrodes remains a
challenge for emerging real-world EEG applications. Classic wet electrodes are the gold …

Objective. Brain–computer interfaces (BCI) enable direct communication with a computer,
using neural activity as the control signal. This neural signal is generally chosen from a …

Objective: This single-arm multisite trial investigates the efficacy of the neurostyle brain
exercise therapy towards enhanced recovery (nBETTER) system, an electroencephalogram …

The use of smart wearables provides an opportunity to improve construction safety and
productivity. Because the healthcare industry has been at the forefront of applying such …

Driver fatigue detection is of great significance for guaranteeing traffic safety and further
reducing economic as well as societal loss. In this article, a novel complex network (CN) …

Fatigued driving is a major cause of road accidents. For this reason, the method in this paper
is based on the steering wheel angles (SWA) and yaw angles (YA) information under real …

Drowsiness is a state of fatigue or sleepiness characterized by a strong urge to sleep. It is
correlated with a progressive decline in response time, compromised processing of …

Electroencephalography (EEG)-based driving fatigue detection has gained increasing
attention recently due to the non-invasive, low-cost, and potable nature of the EEG …

Detecting fatigue driving from electroencephalogram (EEG) signals constitutes a
challenging problem of continuing interest since fatigue driving has caused the majority of …