A review of recent developments in driver drowsiness detection systems

Y Albadawi, M Takruri, M Awad - Sensors, 2022‏ - mdpi.com
Continuous advancements in computing technology and artificial intelligence in the past
decade have led to improvements in driver monitoring systems. Numerous experimental …

A review of psychophysiological measures to assess cognitive states in real-world driving

M Lohani, BR Payne, DL Strayer - Frontiers in human neuroscience, 2019‏ - frontiersin.org
As driving functions become increasingly automated, motorists run the risk of becoming
cognitively removed from the driving process. Psychophysiological measures may provide …

Driving behavior analysis guidelines for intelligent transportation systems

MN Azadani, A Boukerche - IEEE transactions on intelligent …, 2021‏ - ieeexplore.ieee.org
The advent of in-vehicle networking systems as well as state-of-the-art sensors and
communication technologies have facilitated the collection of large volume and almost real …

Detecting fatigue in car drivers and aircraft pilots by using non-invasive measures: The value of differentiation of sleepiness and mental fatigue

X Hu, G Lodewijks - Journal of safety research, 2020‏ - Elsevier
Introduction: Fatigue is one of the most crucial factors that contribute to a decrease of the
operating performance of aircraft pilots and car drivers and, as such, plays a dangerous role …

Machine learning and deep learning techniques for driver fatigue and drowsiness detection: a review

SA El-Nabi, W El-Shafai, ESM El-Rabaie… - Multimedia Tools and …, 2024‏ - Springer
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 …

Detection and prediction of driver drowsiness using artificial neural network models

CJ de Naurois, C Bourdin, A Stratulat, E Diaz… - Accident Analysis & …, 2019‏ - Elsevier
Not just detecting but also predicting impairment of a car driver's operational state is a
challenge. This study aims to determine whether the standard sources of information used to …

EEG-Based driver Fatigue Detection using Spatio-Temporal Fusion network with brain region partitioning strategy

F Hu, L Zhang, X Yang… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
Detecting driver fatigue is critical for ensuring traffic safety. Electroencephalography (EEG) is
the golden standard for brain activity measurement and is considered a good indicator of …

Identification and classification of construction equipment operators' mental fatigue using wearable eye-tracking technology

J Li, H Li, W Umer, H Wang, X **ng, S Zhao… - Automation in …, 2020‏ - Elsevier
In the construction industry, the operator's mental fatigue is one of the most important causes
of construction equipment-related accidents. Mental fatigue can easily lead to poor …

Artificial intelligence, machine learning and reasoning in health informatics—Case studies

MU Ahmed, S Barua, S Begum - Signal Processing Techniques for …, 2021‏ - Springer
Abstract To apply Artificial Intelligence (AI), Machine Learning (ML) and Machine Reasoning
(MR) in health informatics are often challenging as they comprise with multivariate …

Driver mental fatigue detection based on head posture using new modified reLU-BiLSTM deep neural network

S Ansari, F Naghdy, H Du… - IEEE Transactions on …, 2021‏ - ieeexplore.ieee.org
Early detection of driver mental fatigue is one of the active areas of research in smart and
intelligent vehicles. There are various methods, based on measuring the physiological …