Continuous advancements in computing technology and artificial intelligence in the past
decade have led to improvements in driver monitoring systems. Numerous experimental …

Internet of Things (IoT) technology has attracted much attention in recent years for its
potential to alleviate the strain on healthcare systems caused by an aging population and a …

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 …

The objective measurement of fatigue is of critical relevance in areas such as occupational
health and safety as fatigue impairs cognitive and motor performance, thus reducing …

With the numerous Internet of Things (IoT) devices, the cloud-centric data processing fails to
meet the requirement of all IoT applications. The limited computation and communication …

The face, an important part of the body, conveys a lot of information. When a driver is in a
state of fatigue, the facial expressions, eg, the frequency of blinking and yawning, are …

Wearable devices are a fast-growing technology with impact on personal healthcare for both
society and economy. Due to the widespread of sensors in pervasive and distributed …

There is currently no standard or widely accepted subset of features to effectively classify
different emotions based on electroencephalogram (EEG) signals. While combining all …

The recent revolutions in Internet of Things (IoT) and big data analytics have unlocked
promising possibilities in biomedical and health care technologies. The current chapter …

In recent years, sleepiness during driving has become a main cause for traffic accidents.
However, the fact is that we know very little yet about the electrophysiological marker for …