Using Cognitive Workload Analysis to Predict and Mitigate Workload for Training Simulation

Jones, Randolph M.; Wray, Robert E.; Zaientz, Jack; Bachelor, Ben; Newton, Charles R.

doi:10.1016/j.promfg.2015.07.825

Cited by 8 publications

(5 citation statements)

References 3 publications

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“…Monitoring cognitive overload is therefore important owing to the effect it has on teleoperator performance. To predict and mitigate workload for training simulation, Jones et al (2015) employed cognitive workload analysis to identify factors that cause cognitive overloading. Due to the fact that existing approaches allow for subjective assessment and may be susceptible to user physiology and environmental influences; Kosch et al (2018) explored the use of gaze data for monitoring cognitive workload.…”

Section: Related Workmentioning

confidence: 99%

“…Due to the fact that existing approaches allow for subjective assessment and may be susceptible to user physiology and environmental influences; Kosch et al (2018) explored the use of gaze data for monitoring cognitive workload. They found that there were higher deviations of gaze points at higher cognitive workload levels during smooth pursuit eye movements for specific trajectory types ( Jones et al, 2015 ). Jones et al (2015) were able to predict cognitive workload through smooth pursuit with an accuracy of 99.5% between low and high workload using an SVM classifier.…”

Section: Related Workmentioning

confidence: 99%

“…They found that there were higher deviations of gaze points at higher cognitive workload levels during smooth pursuit eye movements for specific trajectory types ( Jones et al, 2015 ). Jones et al (2015) were able to predict cognitive workload through smooth pursuit with an accuracy of 99.5% between low and high workload using an SVM classifier. Using gaze data (gaze duration and the fixation count), we therefore set out to monitor cognitive workload for different stages of a teleoperation task in this study.…”

Section: Related Workmentioning

confidence: 99%

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Assessing the Role of Gaze Tracking in Optimizing Humans-In-The-Loop Telerobotic Operation Using Multimodal Feedback

et al. 2021

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A key challenge in achieving effective robot teleoperation is minimizing teleoperators’ cognitive workload and fatigue. We set out to investigate the extent to which gaze tracking data can reveal how teleoperators interact with a system. In this study, we present an analysis of gaze tracking, captured as participants completed a multi-stage task: grasping and emptying the contents of a jar into a container. The task was repeated with different combinations of visual, haptic, and verbal feedback. Our aim was to determine if teleoperation workload can be inferred by combining the gaze duration, fixation count, task completion time, and complexity of robot motion (measured as the sum of robot joint steps) at different stages of the task. Visual information of the robot workspace was captured using four cameras, positioned to capture the robot workspace from different angles. These camera views (aerial, right, eye-level, and left) were displayed through four quadrants (top-left, top-right, bottom-left, and bottom-right quadrants) of participants’ video feedback computer screen, respectively. We found that the gaze duration and the fixation count were highly dependent on the stage of the task and the feedback scenario utilized. The results revealed that combining feedback modalities reduced the cognitive workload (inferred by investigating the correlation between gaze duration, fixation count, task completion time, success or failure of task completion, and robot gripper trajectories), particularly in the task stages that require more precision. There was a significant positive correlation between gaze duration and complexity of robot joint movements. Participants’ gaze outside the areas of interest (distractions) was not influenced by feedback scenarios. A learning effect was observed in the use of the controller for all participants as they repeated the task with different feedback combination scenarios. To design a system for teleoperation, applicable in healthcare, we found that the analysis of teleoperators’ gaze can help understand how teleoperators interact with the system, hence making it possible to develop the system from the teleoperators’ stand point.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Assessing the Role of Gaze Tracking in Optimizing Humans-In-The-Loop Telerobotic Operation Using Multimodal Feedback

et al. 2021

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“…The game design approach attempts to mitigate potential negative effects in three ways. First and most importantly, we designed Skipper and present it as a supplement to analytic and empirical methods for evaluating the technology [2,12]. Thus, the game is one tool available to help stakeholders understand the technology but not the only one.…”

Section: Serious-game Requirementsmentioning

confidence: 99%

Using a Serious Game to Illustrate Supervisory Control Technology

Wray¹,

Bachelor²,

Newton³

et al. 2016

Engineering Psychology and Cognitive Ergonomics

Self Cite

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We describe the development of a serious game designed to illustrate the impact of a supervisory control technology. The technology is designed to help human operators deliver better training experiences in simulation. It automates low-level control tasks, thus reducing operator workload. The serious game embeds the technology and simulation in a different context. In the game, the player directs several aircraft in a simulation toward specific geographic points while avoiding "obstacles" and obeying "speed limits" in certain areas. The player's score is maximized when the player adjusts aircraft flight to the constraints, which change dynamically during gameplay. The supervisory control is employed as an "autopilot" to enable aircraft to automatically obey geographical restrictions. Users can play the game with and without the supervisory control technology. These modes allow the players to experience directly both overload and the workload reduction enabled by supervisory control. We contend that direct experience with a technology such as this can supplement design reviews and empirical piloting, helping stakeholders gain a more complete perspective of the desired operational role of the technology.

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“…A research without a theoretical framework can at most be considered as a case study. For this reason, we intend to use cognitive workload analysis [21] and Dreyfus's model for adult skill acquisition [22], [23] to develop a theoretical model explaining what we find in both the desktop and VR learning environment in this application. The findings of these three stages can be used to determine the validity of the theoretical framework proposed.…”

Section: Stage Threementioning

confidence: 99%

Board 83 : A Tale of the Robot: Will Virtual Reality Enhance Student Learning of Industrial Robotics?

Chang¹,

Devine²

2018 ASEE Annual Conference &Amp; Exposition Proceedings

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He received a MSME degree from Carnegie Mellon University, a MSIE degree and a PhD degree in Technology, both from Purdue University. Dr. Chang has worked with several international corporations including Boeing, DaimlerChrysler, and Dassualt Systemes, as well as multiple small to medium size companies in both US and Asia. His current field of focus is in product innovation, process improvement, and technology diffusion.

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Using Cognitive Workload Analysis to Predict and Mitigate Workload for Training Simulation

Cited by 8 publications

References 3 publications

Assessing the Role of Gaze Tracking in Optimizing Humans-In-The-Loop Telerobotic Operation Using Multimodal Feedback

Assessing the Role of Gaze Tracking in Optimizing Humans-In-The-Loop Telerobotic Operation Using Multimodal Feedback

Using a Serious Game to Illustrate Supervisory Control Technology

Board 83 : A Tale of the Robot: Will Virtual Reality Enhance Student Learning of Industrial Robotics?

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