Drowsy driving is one of the common causes road accidents resulting in injuries, even death, and significant economic losses to drivers, users, families, society. There have been many studies carried out an attempt detect drowsiness for alert systems. However, a majority focused on determining eyelid mouth movements, which revealed limitations detection. Besides, physiological measures-based ma...

Drowsiness detection is a crucial step for safe driving. A plethora of efforts has been invested on using pervasive sensor data (e.g., video, physiology) empowered by machine learning to build an automatic drowsiness system. Nevertheless, most the existing methods are based complicated wearables electroencephalogram) or computer vision algorithms eye state analysis), which makes relevant system...

Normal electroencephalographic (EEG) alpha variants appear during relaxed wakefulness with closed eyes, drowsiness period at sleep onset, and rapid eye movement (REM) sleep in bursts without arousal signals. Previous results revealed that fronto-occipital and fronto-frontal alpha coherences became weaker from wakefulness to drowsiness, and finally to REM sleep. The present work was aimed at det...

Fatigue driving is an invisible killer in car accidents and one of the main causes traffic accidents. In order to reduce caused by fatigue, this research has developed a safety assist device prevent such research, non-contact driver drowsiness detection alert system established vehicle cabin. The real-time facial image obtained through camera installed front driver, then input NVIDIA Jetson TX2...

The aim of this study was to identify a useful measure to estimate an arousal level of drivers, to apply the result to develop ITS (Intelligent Transportation System) that can warn drivers of their low arousal state and to prevent driving under low arousal level from occurring and contribute to the reduction of traffic accidents. The EEG(electroencephalography) during a monotonous task was meas...

Drowsiness and fatigue of automobile drivers reduce the drivers’ abilities of vehicle control, natural reflex, recognition and perception. Such diminished vigilance level of drivers is observed at night driving or overdriving, causing accident and pose severe threat to mankind and society. Therefore it is very much necessary in this recent trend in automobile industry to incorporate driver assi...

Driver Drowsiness is one of the leading causes of road accidents. It affects the mental vigilance of the driver and reduces his personal capacity to drive a vehicle in full safety. These factors increase the risk of human errors which could involve deaths and wounds, which highlights the need to develop a system that can alert drivers of their drowsy state prior to accidents. It is important fo...

This paper presents a design of a unique solution for detecting driver drowsiness state in real time, based on eye conditions. Many approaches have been used to address this issue in the past. But this paper presents a simple algorithm based solution with min imum hardware requirements. Under the controlled environment, the proposed system is successfully operated to generate results with appro...

This paper aims to study the phenomenon known as 'highway hypnosis' or 'driving without attention mode', which has been defined as a state showing sleepiness signs and attention slip resulting from driving a motor vehicle for a long period in a highly predictable environment with low event occurrence, this being the case with motorways and very familiar roads [Highway hypnosis: a theoretical an...

BACKGROUND It has been suggested that snoring alone, without conventional sleep apnoea or hypopnoea, may disrupt sleep and produce substantial daytime hypersomnolence. This study addresses this potential relationship. METHOD Eight hundred and fifty men, aged 35-65 years, drawn from one general practice were visited at home and asked a range of questions potentially related to sleepiness, snor...