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

Mikula, Laura; Mejía-Romero, Sergio; Chaumillon, Romain; Patoine, Amigale; Lugo, Eduardo; Bernardin, Delphine; Faubert, Jocelyn

doi:10.1371/journal.pone.0240201

Cited by 10 publications

(13 citation statements)

References 91 publications

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“…The participant’s gaze behaviour was recorded using a Fovio FX3 eye tracker by 23 , using 60 Hz binocular eye tracking. We positioned the eye tracker under the Primary Flight Display (PFD) and a virtual environment was created using Eyeworks (see Supplementary Figs.…”

Section: Methodsmentioning

confidence: 99%

“…Dealing with gaze recordings proves challenging, as the raw data produced by the eye tracker is subject to noise and artifacts. The CTA-toolbox solution implemented in FaubertLab 23 was used to process the raw data from the eye tracker, interpolate missing data and denoise the recorded traces. The final output of the toolbox was a cleaned-up recording that was used for further analysis.…”

Section: Methodsmentioning

confidence: 99%

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Beyond performance: the role of task demand, effort, and individual differences in ab initio pilots

Darvishi-Bayazi,

Law,

Romero

et al. 2023

Sci Rep

Self Cite

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Aviation safety depends on the skill and expertise of pilots to meet the task demands of flying an aircraft in an effective and efficient manner. During flight training, students may respond differently to imposed task demands based on individual differences in capacity, physiological arousal, and effort. To ensure that pilots achieve a common desired level of expertise, training programs should account for individual differences to optimize pilot performance. This study investigates the relationship between task performance and physiological correlates of effort in ab initio pilots. Twenty-four participants conducted a flight simulator task with three difficulty levels and were asked to rate their perceived demand and effort using the NASA TLX. We recorded heart rate, EEG brain activity, and pupil size to assess changes in the participants’ mental and physiological states across different task demands. We found that, despite group-level correlations between performance error and physiological responses, individual differences in physiological responses to task demands reflected different levels of participant effort and task efficiency. These findings suggest that physiological monitoring of student pilots might provide beneficial insights to flight instructors to optimize pilot training at the individual level.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Beyond performance: the role of task demand, effort, and individual differences in ab initio pilots

Darvishi-Bayazi,

Law,

Romero

et al. 2023

Sci Rep

Self Cite

View full text Add to dashboard Cite

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“…The investigation of visual scanning provides a fundamental window into the nature of visual-cognitive processing while performing naturalistic sensorimotor tasks such as walking and driving [ 3 , 4 ]. The underpinning mechanism of visual scanning and visual-cognitive processing essentially includes the coordination of head and eyes in the procedure of performing sensorimotor tasks [ 5 , 6 , 7 , 8 , 9 ]. Therefore, head–eye coordination can be used as a valid means to study the internal mechanisms of visual scanning and visual cognitive processes.…”

Section: Introductionmentioning

confidence: 99%

“…Notice that, although the research on the dynamics of the coordination of head and eyes in visual scanning attracted a lot of studies recently [ 5 , 6 , 7 , 9 ], there is no quantitative measure on this coordination. The tight connection between the information flow between head motion and eye movement and head–eye coordination leads us to believe that quantifying head–eye coordination based on transfer entropy is feasible.…”

Section: Introductionmentioning

confidence: 99%

Information Difference of Transfer Entropies between Head Motion and Eye Movement Indicates a Proxy of Driving

Zhang,

Xu,

Wang

et al. 2023

Entropy

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Visual scanning is achieved via head motion and gaze movement for visual information acquisition and cognitive processing, which plays a critical role in undertaking common sensorimotor tasks such as driving. The coordination of the head and eyes is an important human behavior to make a key contribution to goal-directed visual scanning and sensorimotor driving. In this paper, we basically investigate the two most common patterns in eye–head coordination: “head motion earlier than eye movement” and “eye movement earlier than head motion”. We utilize bidirectional transfer entropies between head motion and eye movements to determine the existence of these two eye–head coordination patterns. Furthermore, we propose a unidirectional information difference to assess which pattern predominates in head–eye coordination. Additionally, we have discovered a significant correlation between the normalized unidirectional information difference and driving performance. This result not only indicates the influence of eye–head coordination on driving behavior from a computational perspective but also validates the practical significance of our approach utilizing transfer entropy for quantifying eye–head coordination.

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“…It also could construct the immersive 3D scene approaching more realistic reaction of humans in real-time because the 3D objects allow in-scene depth, multiple angles, and variation of material's properties [6]. What's more, estimating gaze position in 3D scene coordinates used eye-tracking device is more accurate [7].…”

Section: Introductionmentioning

confidence: 99%

Eye movement based information system indicates human behavior in virtual driving

Peng

Zhang

et al. 2022

Preprint

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Humans modulate the behavior flexibly after timely receiving and processing information from the environment. To better understand and measure human behavior in the driving process, we integrate humans and the environment as a system. The eye-movement methodologies are used to provide a bridge between humans and environment. Thus, we conduct a goal-directed task in virtual driving to investigate the law of eye-movement that could characterize the humans (internal) and environmental (external) state measured by fixation distribution and optical flows distribution. The analysis of eye-movement data combined with the information-theoretic tool, transfer entropy, active information storage, quantify the humans’ cognitive effort and receiving information, and in fact, there is a balance (optimal) range between two, because of the mutual synergy and inhibition, whose quantified value is named balance of information processing. Subsequently, we update a system-level model, finding that those information measurements, transfer entropy, active information storage, and balance of information processing, all are included. This information set is information flow, which is quantified by the square root of Jensen-Shannon divergence (SRJSD), named information flow gain. What’s more, results also demonstrate that the influence of system-level information flow correlated with behavioral performance stronger than the separate measurements. In conclusion, we research humans’ eye-movement based on information theory to analyze behavioral performance. Besides driving, these measurements may be a predictor for other behaviors such as walking, running, etc. Still, the limitation is that the information flow may be a proxy of determinants of behavior.

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

Cited by 10 publications

References 91 publications

Beyond performance: the role of task demand, effort, and individual differences in ab initio pilots

Beyond performance: the role of task demand, effort, and individual differences in ab initio pilots

Information Difference of Transfer Entropies between Head Motion and Eye Movement Indicates a Proxy of Driving

Eye movement based information system indicates human behavior in virtual driving

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