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

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 …

Drowsiness or fatigue is a major cause of road accidents and has significant implications for
road safety. Several deadly accidents can be prevented if the drowsy drivers are warned in …

Personal and ubiquitous sensing technologies such as smartphones have allowed the
continuous collection of data in an unobtrusive manner. Machine learning methods have …

Drowsiness when in command of a vehicle leads to a decline in cognitive performance that
affects driver behavior, potentially causing accidents. Drowsiness-related road accidents …

There are several factors for vehicle accidents during driving such as drivers' negligence,
drowsiness, and fatigue. These accidents can be avoided, if drivers are warned in time …

Drowsy driving imposes a high safety risk. Current systems often use driving behavior
parameters for driver drowsiness detection. The continuous driving automation reduces the …

Wearable sensors measuring different parts of people's activity are a common technology
nowadays. In research, data collected using these devices also draws attention …

The exponential growth in road accidents has led to a need for continuous driver monitoring
to enhance road safety. Existing techniques rely on vehicle sensor-based and behavior …

It is well known that blink, yawn, and heart rate changes give clue about a human's mental
state, such as drowsiness and fatigue. In this paper, image sequences, as the raw data, are …