ArticleSensors (Basel, Switzerland)2019
Monitoring Pilot's Mental Workload Using ERPs and Spectral Power with a Six-Dry-Electrode EEG System in Real Flight Conditions.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.
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Who cites it
47 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine learning performance in EEG-based mental workload classification across task types: a systematic review.Frontiers in neuroergonomics · 2025Pooled it
- Consumer-Grade Wearable Sensors for Classifying Pilot Workload and Stress During Real Flight Training: A Leave-One-Subject-Out Validation Study.Sensors (Basel, Switzerland) · 2026Article
- To assure aviation safety: the pilot fatigue detection based on short-term multimodal physiological signals.Frontiers in human neuroscience · 2026Article
- Doing the math: detection and neural processing of auditory task-unrelated stimuli while solving arithmetic tasks.Neuroscience of consciousness · 2026Article
- Cognitive state monitoring for neuroadaptive information visualization.Frontiers in human neuroscience · 2026Review
- Workload analysis of pilot steep turn maneuvers using SR20 aircraft and EEG data.Frontiers in neuroscience · 2026Article
- From signal to construct evidence: multimodal consumer-wearable sensing in real general-aviation flight.Frontiers in neuroergonomics · 2026Article
- Examining physiological parameters of mental workload in the cockpit: a multimethod approach.Frontiers in physiology · 2026Article
- ASFT-Transformer: A Fast and Accurate Framework for EEG-Based Pilot Fatigue Recognition.Sensors (Basel, Switzerland) · 2025Article
- Monitoring pilots' mental workload in real flight conditions using multinomial logistic regression with a ridge estimator.Frontiers in robotics and AI · 2025Article
- The state of the art in assessing mental fatigue in the cockpit using head-worn sensing technology.Frontiers in neuroergonomics · 2025Review
- Combined Effects of Moderate Hypoxia and Sleep Restriction on Mental Workload.Clocks & sleep · 2024Article
- Classification of mental workload using brain connectivity and machine learning on electroencephalogram data.Scientific reports · 2024Article
- EEG Dataset Collection for Mental Workload Predictions in Flight-Deck Environment.Sensors (Basel, Switzerland) · 2024Article
- Blink-Related Oscillations Provide Naturalistic Assessments of Brain Function and Cognitive Workload within Complex Real-World Multitasking Environments.Sensors (Basel, Switzerland) · 2024Article
- A systematic narrative review of the involvement of executive functions in flying performance of pilots.Frontiers in neuroergonomics · 2024Review
- MATB for assessing different mental workload levels.Frontiers in physiology · 2024Review
- Task-independent auditory probes reveal changes in mental workload during simulated quadrotor UAV training.Health information science and systems · 2023Article
- The Use of Quantitative Electroencephalography (QEEG) to Assess Post-COVID-19 Concentration Disorders in Professional Pilots: An Initial Concept.Brain sciences · 2023Article
- Multimodal Approach for Pilot Mental State Detection Based on EEG.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Recent technological progress has allowed the development of low-cost and highly portable brain sensors such as pre-amplified dry-electrodes to measure cognitive activity out of the laboratory. This technology opens promising perspectives to monitor the "brain at work" in complex real-life situations such as while operating aircraft. However, there is a need to benchmark these sensors in real operational conditions. We therefore designed a scenario in which twenty-two pilots equipped with a six-dry-electrode EEG system had to perform one low load and one high load traffic pattern along with a passive auditory oddball. In the low load condition, the participants were monitoring the flight handled by a flight instructor, whereas they were flying the aircraft in the high load condition. At the group level, statistical analyses disclosed higher P300 amplitude for the auditory target (Pz, P4 and Oz electrodes) along with higher alpha band power (Pz electrode), and higher theta band power (Oz electrode) in the low load condition as compared to the high load one. Single trial classification accuracy using both event-related potentials and event-related frequency features at the same time did not exceed chance level to discriminate the two load conditions. However, when considering only the frequency features computed over the continuous signal, classification accuracy reached around 70% on average. This study demonstrates the potential of dry-EEG to monitor cognition in a highly ecological and noisy environment, but also reveals that hardware improvement is still needed before it can be used for everyday flight operations.
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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.