ArticleSensors (Basel, Switzerland)2015
Investigating Driver Fatigue versus Alertness Using the Granger Causality Network.
Article in Sensors (Basel, Switzerland), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Beyond the time-on-task: an EEG-driven approach for effective physiological assessment of mental fatigue in simulated and real driving.Frontiers in bioengineering and biotechnology · 2025Article
- Reorganization of Brain Functional Network during Task Switching before and after Mental Fatigue.Sensors (Basel, Switzerland) · 2022Article
- Improving EEG-Based Driver Distraction Classification Using Brain Connectivity Estimators.Sensors (Basel, Switzerland) · 2022Article
- Directed Brain Network Analysis for Fatigue Driving Based on EEG Source Signals.Entropy (Basel, Switzerland) · 2022Article
- EEG Connectivity during Active Emotional Musical Performance.Sensors (Basel, Switzerland) · 2022Article
- EEG-based brain functional connectivity representation using amplitude locking value for fatigue-driving recognition.Cognitive neurodynamics · 2022Article
- EEG-Based Index for Timely Detecting User's Drowsiness Occurrence in Automotive Applications.Frontiers in human neuroscience · 2022Article
- Detecting Unfavorable Driving States in Electroencephalography Based on a PCA Sample Entropy Feature and Multiple Classification Algorithms.Entropy (Basel, Switzerland) · 2020Article
- A framework to quantify controlled directed interactions in network physiology applied to cognitive function assessment.Scientific reports · 2020Article
- Decoding Analysis of Alpha Oscillation Networks on Maintaining Driver Alertness.Entropy (Basel, Switzerland) · 2020Article
- Modulation of Brain Functional Connectivity and Efficiency During an Endurance Cycling Task: A Source-Level EEG and Graph Theory Approach.Frontiers in human neuroscience · 2020Article
- Alterations of Cerebral Hemodynamics and Network Properties Induced by Newsvendor Problem in the Human Prefrontal Cortex.Frontiers in human neuroscience · 2020Article
- Prediction of epilepsy seizure from multi-channel electroencephalogram by effective connectivity analysis using Granger causality and directed transfer function methods.Cognitive neurodynamics · 2019Article
- Lightweight Driver Monitoring System Based on Multi-Task Mobilenets.Sensors (Basel, Switzerland) · 2019Article
- Spontaneous electromagnetic induction promotes the formation of economical neuronal network structure via self-organization process.Scientific reports · 2019Article
- Brain Complex Network Characteristic Analysis of Fatigue during Simulated Driving Based on Electroencephalogram Signals.Entropy (Basel, Switzerland) · 2019Article
- EEG Classification of Motor Imagery Using a Novel Deep Learning Framework.Sensors (Basel, Switzerland) · 2019Article
- The Dynamic EEG Microstates in Mental Rotation.Sensors (Basel, Switzerland) · 2018Article
- Sensor Technologies for Intelligent Transportation Systems.Sensors (Basel, Switzerland) · 2018Review
- Evaluating Pro- and Re-Active Driving Behavior by Means of the EEG.Frontiers in human neuroscience · 2018Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Driving fatigue has been identified as one of the main factors affecting drivers' safety. The aim of this study was to analyze drivers' different mental states, such as alertness and drowsiness, and find out a neurometric indicator able to detect drivers' fatigue level in terms of brain networks. Twelve young, healthy subjects were recruited to take part in a driver fatigue experiment under different simulated driving conditions. The Electroencephalogram (EEG) signals of the subjects were recorded during the whole experiment and analyzed by using Granger-Causality-based brain effective networks. It was that the topology of the brain networks and the brain's ability to integrate information changed when subjects shifted from the alert to the drowsy stage. In particular, there was a significant difference in terms of strength of Granger causality (GC) in the frequency domain and the properties of the brain effective network i.e., causal flow, global efficiency and characteristic path length between such conditions. Also, some changes were more significant over the frontal brain lobes for the alpha frequency band. These findings might be used to detect drivers' fatigue levels, and as reference work for future studies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.