AIMC Topic: Sleepiness

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Multi-body sensor based drowsiness detection using convolutional programmed transfer VGG-16 neural network with automatic driving mode conversion.

Scientific reports Mar 14, 2025
Many traffic accidents occur nowadays as a result of drivers not paying enough attention or being vigilant. We call this driver sleepiness. This results in numerous unfavourable circumstances that negatively impact people's life. The identification o...
Neural Networks, Computer Machine Learning Humans Automobile Driving Sleepiness Sleep Stages Electroencephalography Accidents, Traffic
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A Real-Time Embedded System for Driver Drowsiness Detection Based on Visual Analysis of the Eyes and Mouth Using Convolutional Neural Network and Mouth Aspect Ratio.

Sensors (Basel, Switzerland) Sep 27, 2024
Currently, the number of vehicles in circulation continues to increase steadily, leading to a parallel increase in vehicular accidents. Among the many causes of these accidents, human factors such as driver drowsiness play a fundamental role. In this...
Sleep Stages Accidents, Traffic Mouth Sleepiness Eye Automobile Driving Neural Networks, Computer Humans Artificial Intelligence
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Driver drowsiness is associated with altered facial thermal patterns: Machine learning insights from a thermal imaging approach.

Physiology & behavior Jun 23, 2024
Driver drowsiness is a significant factor in road accidents. Thermal imaging has emerged as an effective tool for detecting drowsiness by enabling the analysis of facial thermal patterns. However, it is not clear which facial areas are most affected ...
Adult Male Female Young Adult Face Body Temperature Thermography Automobile Driving Sleepiness Machine Learning Computer Simulation Humans Sleep Stages
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Physiological signal-based drowsiness detection using machine learning: Singular and hybrid signal approaches.

Journal of safety research Dec 13, 2021
INTRODUCTION: Drowsiness is one of the main contributors to road-related crashes and fatalities worldwide. To address this pressing global issue, researchers are continuing to develop driver drowsiness detection systems that use a variety of measures...
Sleepiness Wakefulness Reproducibility of Results Automobile Driving Humans Machine Learning
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An Evaluation of Sleepiness, Performance, and Workload Among Operators During a Real-Time Reactive Telerobotic Lunar Mission Simulation.

Human factors Dec 5, 2021
OBJECTIVE: We assessed operator performance during a real-time reactive telerobotic lunar mission simulation to understand how daytime versus nighttime operations might affect sleepiness, performance, and workload.
Fatigue Work Schedule Tolerance Sleepiness Sleep Robotics Workload Humans
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A Generic Design of Driver Drowsiness and Stress Recognition Using MOGA Optimized Deep MKL-SVM.

Sensors (Basel, Switzerland) Mar 7, 2020
Driver drowsiness and stress are major causes of traffic deaths and injuries, which ultimately wreak havoc on world economic loss. Researchers are in full swing to develop various algorithms for both drowsiness and stress recognition. In contrast to ...
ROC Curve Support Vector Machine Sleepiness Automobile Driving Humans Algorithms Stress, Psychological
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Adapting artificial neural networks to a specific driver enhances detection and prediction of drowsiness.

Accident; analysis and prevention Sep 20, 2018
Monitoring car drivers for drowsiness is crucial but challenging. The high inter-individual variability observed in measurements raises questions about the accuracy of the drowsiness detection process. In this study, we sought to enhance the performa...
Female Male Automobile Driving Sleepiness Computer Systems Machine Learning Computer Simulation Humans Neural Networks, Computer Wakefulness
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Detection and prediction of driver drowsiness using artificial neural network models.

Accident; analysis and prevention Dec 6, 2017
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 detect drowsiness can also be used to predict when a given drowsine...
Male Wakefulness Neural Networks, Computer Eye Movements Time Factors Young Adult Video Recording Humans Female Sleepiness Adult Distracted Driving
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