ArticleBrain sciences2022
Validation of a Light EEG-Based Measure for Real-Time Stress Monitoring during Realistic Driving.
Article in Brain sciences, 2022. 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.
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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
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- Multi-method characterization of neurophysiological and biological stress responses in surgical teams during real surgical procedures.Frontiers in neuroergonomics · 2026Article
- Neuroscience meets food choice: Implicit and explicit consumer responses to plant-based vs animal-based foods.Current research in food science · 2026Article
- Beyond the lab: real-world benchmarking of wearable EEGs for passive brain-computer interfaces.Brain informatics · 2025Article
- Brain-inspired signal processing for detecting stress during mental arithmetic tasks.Brain informatics · 2025Article
- Brain Cortical Area Characterization and Machine Learning-Based Measure of Rasmussen's S-R-K Model.Brain sciences · 2025Article
- EEG dataset for natural image recognition through visual stimuli.Data in brief · 2025Article
- Listening effort and stress in tinnitus: a multidimensional approach.Frontiers in neuroscience · 2025Article
- Cognitive and emotional responses to viewing mummies in an Egyptian museum.Frontiers in neuroscience · 2025Article
- Driving Fatigue Onset and Visual Attention: An Electroencephalography-Driven Analysis of Ocular Behavior in a Driving Simulation Task.Behavioral sciences (Basel, Switzerland) · 2024Article
- Characterization of Cochlear Implant Artifact and Removal Based on Multi-Channel Wiener Filter in Unilateral Child Patients.Bioengineering (Basel, Switzerland) · 2024Article
- Design Decisions for Wearable EEG to Detect Motor Imagery Movements.Sensors (Basel, Switzerland) · 2024Article
- Advances in Neuropsychology: Top Papers Published inBrain sciences · 2024Article
- Bridging the Gap between Psychophysiological and Audiological Factors in the Assessment of Tinnitus: An EEG Investigation in the Beta Band.Brain sciences · 2024Article
- A Neuroergonomic Approach Fostered by Wearable EEG for the Multimodal Assessment of Drivers Trainees.Sensors (Basel, Switzerland) · 2023Article
- Neurophysiological Assessment of An Innovative Maritime Safety System in Terms of Ship Operators' Mental Workload, Stress, and Attention in the Full Mission Bridge Simulator.Brain sciences · 2023Article
- Article
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Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Driver's stress affects decision-making and the probability of risk occurrence, and it is therefore a key factor in road safety. This suggests the need for continuous stress monitoring. This work aims at validating a stress neurophysiological measure-a Neurometric-for out-of-the-lab use obtained from lightweight EEG relying on two wet sensors, in real-time, and without calibration. The Neurometric was tested during a multitasking experiment and validated with a realistic driving simulator. Twenty subjects participated in the experiment, and the resulting stress Neurometric was compared with the Random Forest (RF) model, calibrated by using EEG features and both intra-subject and cross-task approaches. The Neurometric was also compared with a measure based on skin conductance level (SCL), representing one of the physiological parameters investigated in the literature mostly correlated with stress variations. We found that during both multitasking and realistic driving experiments, the Neurometric was able to discriminate between low and high levels of stress with an average Area Under Curve (AUC) value higher than 0.9. Furthermore, the stress Neurometric showed higher AUC and stability than both the SCL measure and the RF calibrated with a cross-task approach. In conclusion, the Neurometric proposed in this work proved to be suitable for out-of-the-lab monitoring of stress levels.
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