Optical correlator based algorithm for driver drowsiness detection
Sign Up to like & getrecommendations! Published in 2020 at "Optik"
DOI: 10.1016/j.ijleo.2019.164102
Abstract: Abstract The human eye and its characteristics (texture, gaze, and movement) have shown to be reliable in expressing human emotional states. A non-invasive eye tracking and state (open/close) estimation system is, consequently, fundamental for developing… read more here.
Keywords: detection; driver drowsiness; drowsiness detection; optical correlator ... See more keywords
A subject-transfer framework for obviating inter- and intra-subject variability in EEG-based drowsiness detection
Sign Up to like & getrecommendations! Published in 2018 at "NeuroImage"
DOI: 10.1016/j.neuroimage.2018.03.032
Abstract: ABSTRACT Inter‐ and intra‐subject variability pose a major challenge to decoding human brain activity in brain‐computer interfaces (BCIs) based on non‐invasive electroencephalogram (EEG). Conventionally, a time‐consuming and laborious training procedure is performed on each new… read more here.
Keywords: subject transfer; drowsiness detection; framework; inter intra ... See more keywords
Privacy-Preserving Federated Transfer Learning for Driver Drowsiness Detection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3192454
Abstract: Drowsiness affects the drivers’ sensory, cognitive, and psychomotor abilities, which are necessary for safe driving. Drowsiness detection is a critical technique to avoid traffic accidents. Federated learning (FL) can solve the problem of insufficient driver… read more here.
Keywords: transfer learning; privacy preserving; drowsiness detection;
Smart Edge-Based Driver Drowsiness Detection in Mobile Crowdsourcing
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3250834
Abstract: Traffic accidents caused by drowsy drivers represent a crucial threat to public safety. Recent statistics show that drowsy drivers cause an estimated 15.5% of fatal accidents. With the widespread use of mobile devices and roadside… read more here.
Keywords: detection; driver drowsiness; drowsiness detection; smart edge ... See more keywords
A Hybrid Scheme for Drowsiness Detection Using Wearable Sensors
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Sensors Journal"
DOI: 10.1109/jsen.2019.2904222
Abstract: The problem addressed in this paper is the detection of drowsiness based on signals acquired using non-invasive and wearable sensors. A combination of signals from electroencephalography (EEG) electrodes, accelerometer, and gyroscope is acquired through a… read more here.
Keywords: hybrid scheme; detection using; drowsiness detection; detection ... See more keywords
A Smartphone-Based Drowsiness Detection and Warning System for Automotive Drivers
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2018.2879609
Abstract: This paper presents a smartphone-based system for the detection of drowsiness in automotive drivers. The proposed framework uses three-stage drowsiness detection. The first stage uses the percentage of eyelid closure (PERCLOS) obtained through images captured… read more here.
Keywords: system; smartphone based; drowsiness detection; stage ... See more keywords
Driver Drowsiness Detection Using Condition-Adaptive Representation Learning Framework
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2018.2883823
Abstract: We propose a condition-adaptive representation learning framework for driver drowsiness detection based on a 3D-deep convolutional neural network. The proposed framework consists of four models: spatio-temporal representation learning, scene condition understanding, feature fusion, and drowsiness… read more here.
Keywords: representation; adaptive representation; condition; drowsiness detection ... See more keywords
Learning Multimodal Representations for Drowsiness Detection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2021.3105326
Abstract: 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 detection system.… read more here.
Keywords: multimodal representations; machine learning; drowsiness detection; detection ... See more keywords
Intelligent Driver Drowsiness Detection for Traffic Safety Based on Multi CNN Deep Model and Facial Subsampling
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2021.3134222
Abstract: Facts reveal that numerous road accidents worldwide occur due to fatigue, drowsiness, and distraction while driving. Few works on the automated drowsiness detection problem, propose to extract physiological signals of the driver including ECG, EEG,… read more here.
Keywords: driver drowsiness; intelligent driver; drowsiness detection; model ... See more keywords
A Systemic Review of Available Low-Cost EEG Headsets Used for Drowsiness Detection
Sign Up to like & getrecommendations! Published in 2020 at "Frontiers in Neuroinformatics"
DOI: 10.3389/fninf.2020.553352
Abstract: Drowsiness is a leading cause of traffic and industrial accidents, costing lives and productivity. Electroencephalography (EEG) signals can reflect awareness and attentiveness, and low-cost consumer EEG headsets are available on the market. The use of… read more here.
Keywords: low cost; drowsiness detection; eeg;
Driving drowsiness detection using spectral signatures of EEG-based neurophysiology
Sign Up to like & getrecommendations! Published in 2023 at "Frontiers in Physiology"
DOI: 10.3389/fphys.2023.1153268
Abstract: Introduction: Drowsy driving is a significant factor causing dire road crashes and casualties around the world. Detecting it earlier and more effectively can significantly reduce the lethal aftereffects and increase road safety. As physiological conditions… read more here.
Keywords: driving drowsiness; spectral signatures; detection using; brain ... See more keywords