Human-Automation Interaction and Safety

Time-Series Foundation Models for Cognitive Workload Classification using Eye-Tracking Data

This study evaluates two time-series foundation models for cognitive workload classification from eye-tracking data, showing better generalization to unseen individuals than task-specific models.

Pupil Dynamics reflect Compensatory Control during Continuous Motor-Control following Cognitive Demand

This study examines how pupil dynamics reflect compensatory control after cognitive demand and their relation to motor performance.

The absent P3a. Performance monitoring ERPs differentiate trust in humans and autonomous systems.

The paper investigates ERP components related to trust in human vs. autonomous systems, finding an absent P3a component in system monitoring, suggesting reduced frontal attention.

Eye movement patterns under exposure to spatial disorientation illusions during simulated flight

This study identifies eye movement patterns associated with spatial disorientation during flight simulations, showing that instrument focus reduces visual illusions while HUD engagement mitigates vestibular illusions.

The Impact of Instrumental Music on Dual-task Interference in a Simulated Driving Environment

This study examines how instrumental music affects dual-task performance in a simulated driving environment, finding that music can improve accuracy without increasing reaction time, especially with a 600 ms task gap.

Distinct brain mechanisms support trust violations, belief integration, and bias in human-AI teams

This paper identifies neural markers of trust dynamics in human-AI interactions using EEG, showing how confidence and feedback processing influence trust ratings.

The neuro-ocular costs of texting during driving

This study investigates the neurophysiological effects of texting while driving under different working-memory loads, finding altered reaction times, gaze behavior, and brain activity patterns.

Do eyes say it all? Assessing the utility of physiological signals for predicting systemic cognitive states

The paper assesses physiological signals to predict cognitive states, finding that pupil size change is the most reliable biomarker for workload, urgency, and mind wandering.

Disturbance of Information in Superior Parietal Lobe during Dual-task Interference in a Simulated Driving Task

The paper uses MVPA to show that dual-task interference in simulated driving disrupts information processing in the superior parietal lobe, correlating with slower reaction times.

Busy and confused? High risk of missed alerts in the cockpit: an electrophysiological study

This study shows that high mental and auditory loads in simulated aviation tasks significantly increase the risk of missing critical auditory alerts, as indicated by reduced P3b brain responses.

Eye movement based information system indicates human behavior in virtual driving

The paper uses eye-movement data in virtual driving to analyze human behavior through information-theoretic measures, finding that system-level information flow correlates stronger with performance than individual metrics.

Predicting the Degree of Distracted Driving Based on fNIRS Functional Connectivity: A Pilot Study

This study develops a model to predict distracted driving using fNIRS-measured brain activity, finding that specific neural network connections are key predictors of distraction levels.

Fast & Scrupulous: Gesture-Based Alarms Improve Accuracy and Reaction Times Under Various Mental Workload Levels. An ERSP Study.

This study compares gesture and text alarms, finding gesture alarms lead to faster and more accurate responses across different mental workload levels, supported by electrophysiological data.

Unravelling the Physiological Correlates of Mental Workload Variations in Tracking and Collision Prediction Tasks: Implications for Air Traffic Controllers

This study identifies physiological correlates of mental workload variations in ATC tasks and shows neurometrics can inform adaptive systems.

Dual-task Interference in a Simulated Driving Environment: Serial or Parallel Processing?

This study investigates dual-task interference in a simulated driving environment, finding that tasks are processed in a partial-parallel manner.

Eye-head coordination and dynamic visual scanning as indicators of visuo-cognitive demands in driving simulator

This study examines how visual degradation affects eye-head coordination and visual scanning during driving, showing changes in movement patterns under suboptimal vision.

Cognitive Processing dissociation and Mental Effort manipulation in long demanding tasks

This study uses pupillometry to measure mental effort in cognitive tasks, showing that automatic tasks can become more demanding with experimental manipulation and that effort peaks early in trials.

Multimodal Study of the Effects of Varying Task Load Utilizing EEG, GSR and Eye-Tracking

This study investigates how task load affects performance using EEG, GSR, and eye-tracking data, finding that EEG and GSR best predict task performance.