SZodixStudyAcademic Library

Dashboard Shelves Open access My library Inbox Notes Write Learn Alerts

More

Ask your library Notifications Quick cite Review

Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated

Automatic driver sleepiness detection using EEG, EOG and contextual information · Study

ArticleShelves

ArticleAutomatic driver sleepiness detection using EEG, EOG and contextual information

Shaibal Barua2018

Article2018

Automatic driver sleepiness detection using EEG, EOG and contextual information

Shaibal Barua · Mobyen Uddin Ahmed · Christer H. G. Ahlstrom · Shahina Begum

145 citations·0/0 files stored·Expert Systems with Applications

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Sleep and Work-Related Fatigue EEG and Brain-Computer Interfaces Human-Automation Interaction and Safety

Abstract

No abstract was published for this record.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 145 citations exist upstream.

References

1990Subjective and Objective Sleepiness in the Active Individual 2012Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness 1995An overview of sleepiness and accidents 1971A Direct Method of Nonparametric Measurement Selection 2001Sustained attention performance during sleep deprivation: evidence of state instability.2012Detecting Driver Drowsiness Based on Sensors: A Review 2008Using EEG spectral components to assess algorithms for detecting fatigue 1999Vehicle accidents related to sleep: a review.

Cited by

2023Machine learning and deep learning techniques for driver fatigue and drowsiness detection: a review 2020Assessment of the Potential of Wrist-Worn Wearable Sensors for Driver Drowsiness Detection 2022Recognising situation awareness associated with different workloads using EEG and eye-tracking features in air traffic control tasks 2021Physiological signal-based drowsiness detection using machine learning: Singular and hybrid signal approaches 2020

Related works

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

2018Driver Sleepiness Classification Based on Physiological Data and Driving Performance From Real Road Drivingarticle · 14 shared references 2018Effects of the road environment on the development of driver sleepiness in young male driversarticle · 11 shared references 2021Survey and Synthesis of State of the Art in Driver Monitoringreview · 9 shared references 2016Driving performance and EEG fluctuations during on-the-road driving following sleep deprivationarticle · 9 shared references 2020Detecting fatigue in car drivers and aircraft pilots by using non-invasive measures: The value of differentiation of sleepiness and mental fatiguereview · 8 shared references 2016Exploring Neuro-Physiological Correlates of Drivers' Mental Fatigue Caused by Sleep Deprivation Using Simultaneous EEG, ECG, and fNIRS Dataarticle · 8 shared references

Details

Year2018

Typearticle

Published2018-08-03

VenueExpert Systems with Applications

ISSN-L0957-4174

Languageen

Citations145

Files0 public / 0

ShelfSleep and Work-Related Fatigue

Identifiers

doi10.1016/j.eswa.2018.07.054

openalex_workW2886857653

Links

Imported from OpenAlex (CC0) — nothing here is generated.

Applying deep neural networks for multi-level classification of driver drowsiness using Vehicle-based measures

2023A systematic review on detection and prediction of driver drowsiness

2019Comprehensive Drowsiness Level Detection Model Combining Multimodal Information

2021Characteristics of driver fatigue and fatigue-relieving effect of special light belt in extra-long highway tunnel: A real-road driving study