Driver Distraction Detection Methods: A Literature Review and Framework
IEEE Access, 2021 Driver inattention and distraction are the main causes of road accidents, many of which result in fatalities. To reduce road accidents, the development of information systems to detect driver inattention and distraction is essential.
Alexey Kashevnik +3 more
doaj +3 more sources
Driver Monitoring System Using Computer Vision for Real-Time Detection of Fatigue, Distraction and Emotion via Facial Landmarks and Deep Learning [PDF]
SensorsCar accidents remain a leading cause of death worldwide, with drowsiness and distraction accounting for roughly 25% of fatal crashes in Ecuador. This study presents a real-time driver monitoring system that uses computer vision and deep learning to ...
Tamia Zambrano +4 more
doaj +2 more sources
Applied Sciences, 2022 In the last decade, distraction detection of a driver gained a lot of significance due to increases in the number of accidents. Many solutions, such as feature based, statistical, holistic, etc., have been proposed to solve this problem.
Tahir Abbas +6 more
doaj +3 more sources
High-wearable EEG-based distraction detection in motor rehabilitation [PDF]
Scientific Reports, 2021 A method for EEG-based distraction detection during motor-rehabilitation tasks is proposed. A wireless cap guarantees very high wearability with dry electrodes and a low number of channels.
Andrea Apicella +3 more
doaj +2 more sources
The influence of target detection on recognition memory during memory retrieval [PDF]
BMC PsychologyThis study developed a target detection delayed response task to investigate the impact of target detection on recognition memory. Participants performed a word recognition task accompanied by a target detection task, where they identified targets but ...
Dandan Tang +5 more
doaj +2 more sources
Deformable Pyramid Sparse Transformer for Semi-Supervised Driver Distraction Detection [PDF]
SensorsEnsuring sustained driver attention is critical for intelligent transportation safety systems; however, the performance of data-driven driver distraction detection models is often limited by the high cost of large-scale manual annotation. To address this
Qiang Zhao +6 more
doaj +2 more sources
Robust Deep Learning-Based Driver Distraction Detection and Classification
IEEE Access, 2021 Driver distraction is a major cause of road accidents. Distracting activities while driving include text messaging and talking on the phone. In this paper, we propose a robust driver distraction detection system that extracts the driver’s state ...
Amal Ezzouhri +3 more
doaj +3 more sources
EFFNet-CA: An Efficient Driver Distraction Detection Based on Multiscale Features Extractions and Channel Attention Mechanism [PDF]
Sensors, 2023 Sokjoon Lee, Gyuho Choi
exaly +2 more sources
ERP Biomarkers of Auditory–Visual Distraction in Aging and Cognitive Impairment [PDF]
Brain SciencesBackground/Objectives: Distraction is a form of impaired selective attention that becomes more pronounced with normal aging and in pathological conditions such as mild cognitive impairment (MCI) and Alzheimer’s disease (AD).
Valentina Gumenyuk +5 more
doaj +2 more sources
Early or late distractions hurt working memory differently depending on how long you look [PDF]
Scientific ReportsVisual Working Memory (VWM) is essential for temporarily retaining goal-relevant visual information, yet its limited capacity renders it vulnerable to distraction.
Guofang Ren +6 more
doaj +2 more sources