ArticleSensors (Basel, Switzerland)2021
Driving-Induced Neurological Biomarkers in an Advanced Driver-Assistance System.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Human-Centric Cognitive State Recognition Using Physiological Signals: A Systematic Review of Machine Learning Strategies Across Application Domains.Sensors (Basel, Switzerland) · 2025Pooled it
- Understanding vigilance and its decrement: theoretical, contextual, and neural insights.Frontiers in cognition · 2025Review
- Simulated driving behavior over the adult age span.Frontiers in aging neuroscience · 2025Article
- Beyond Flexible: Unveiling the Next Era of Flexible Electronic Systems.Advanced materials (Deerfield Beach, Fla.) · 2024Review
- A multimodal physiological dataset for driving behaviour analysis.Scientific data · 2024Article
- Interpreting Stroke-Impaired Electromyography Patterns through Explainable Artificial Intelligence.Sensors (Basel, Switzerland) · 2024Article
- Assessment of Drivers' Mental Workload by Multimodal Measures during Auditory-Based Dual-Task Driving Scenarios.Sensors (Basel, Switzerland) · 2024Article
- Reproducible machine learning research in mental workload classification using EEG.Frontiers in neuroergonomics · 2024Review
- Removal of movement artifacts and assessment of mental stress analyzing electroencephalogram of non-driving passengers under whole-body vibration.Frontiers in neuroscience · 2024Article
- A systematic review of privacy-preserving methods deployed with blockchain and federated learning for the telemedicine.Healthcare analytics (New York, N.Y.) · 2023Review
- An Explainable EEG-Based Human Activity Recognition Model Using Machine-Learning Approach and LIME.Sensors (Basel, Switzerland) · 2023Article
- EEG-Based Emotion Classification in Financial Trading Using Deep Learning: Effects of Risk Control Measures.Sensors (Basel, Switzerland) · 2023Article
- The Increase of Theta Power and Decrease of Alpha/Theta Ratio as a Manifestation of Cognitive Impairment in Parkinson's Disease.Journal of clinical medicine · 2023Article
- Driver Attention Assessment Using Physiological Measures from EEG, ECG, and EDA Signals.Sensors (Basel, Switzerland) · 2023Article
- Convolutional Neural Network with a Topographic Representation Module for EEG-Based Brain-Computer Interfaces.Brain sciences · 2023Article
- EEG-Neurofeedback as a Potential Therapeutic Approach for Cognitive Deficits in Patients with Dementia, Multiple Sclerosis, Stroke and Traumatic Brain Injury.Life (Basel, Switzerland) · 2023Review
- An Efficient Machine Learning-Based Emotional Valence Recognition Approach Towards Wearable EEG.Sensors (Basel, Switzerland) · 2023Article
- EEG Emotion Recognition Applied to the Effect Analysis of Music on Emotion Changes in Psychological Healthcare.International journal of environmental research and public health · 2022Article
- A Potential Prognosis Indicator Based on P300 Brain-Computer Interface for Patients with Disorder of Consciousness.Brain sciences · 2022Article
- Phase Lag Index of Resting-State EEG for Identification of Mild Cognitive Impairment Patients with Type 2 Diabetes.Brain sciences · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Physiological signals are immediate and sensitive to neurological changes resulting from the mental workload induced by various driving environments and are considered a quantifying tool for understanding the association between neurological outcomes and driving cognitive workloads. Neurological assessment, outside of a highly-equipped clinical setting, requires an ambulatory electroencephalography (EEG) headset. This study aimed to quantify neurological biomarkers during a resting state and two different scenarios of driving states in a virtual driving environment. We investigated the neurological responses of seventeen healthy male drivers. EEG data were measured in an initial resting state, city-roadways driving state, and expressway driving state using a portable EEG headset in a driving simulator. During the experiment, the participants drove while experiencing cognitive workloads due to various driving environments, such as road traffic conditions, lane changes of surrounding vehicles, the speed limit, etc. The power of the beta and gamma bands decreased, and the power of the delta waves, theta, and frontal theta asymmetry increased in the driving state relative to the resting state. Delta-alpha ratio (DAR) and delta-theta ratio (DTR) showed a strong correlation with a resting state, city-roadways driving state, and expressway driving state. Binary machine-learning (ML) classification models showed a near-perfect accuracy between the resting state and driving state. Moderate classification performances were observed between the resting state, city-roadways state, and expressway state in multi-class classification. An EEG-based neurological state prediction approach may be utilized in an advanced driver-assistance system (ADAS).
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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.