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Using Eye-tracking to Acknowledge Attended Alarms

A lack of alarm management for industrial control rooms has led to frequent alarm floods that have the potential to overwhelm operators within minutes. One approach to managing alarm floods would be altering the salience of alarms that operators might already notice, thereby reducing the disruption on workflow and attention for managing uninformative alarms. This research investigated the central hypothesis that eye fixations could supply passive input to acknowledge alarms anticipated by the operators and thereby improve their overall task performance. A dual-task experiment recruiting 24 participants was conducted to compare three gaze-based alarm acknowledgement methods –Proximity, Prediction, and Entropy- against no acknowledgement across three types of scenarios – Near-threshold, Trending, and Fluctuation. The gaze-based acknowledgement methods reduced visual and auditory salience of alarms as a function of the number of fixations on parameters as well as characteristics of the parameter known to influence operator monitoring behaviors. The participants performed an alarm monitoring task while controlling a continuous parameter within an acceptable range. While participants showed a preference for all of three gaze-based acknowledgment methods, performance of the parameter control task did not improve with gaze-based acknowledgement. Scenario types, as defined by the behavior of the parameters, exhibited a significant effect on the performance of the parameter control task, suggesting a greater influence on participant attention than the reduced salience associated with the gaze-based acknowledgments. Additional analysis revealed that gaze-acknowledgements are higher in scenarios with the most suitable for the gaze-based acknowledgement methods, although the participants did not show any gaze-based acknowledgements and did not make a prediction of an alarm for a significant portion of the trials, suggesting a lack of resource allocation to the alarm monitoring task. This result suggests that the effectiveness of gaze-based acknowledgement may depend on the combination of on-going tasks. Taken together, the experimental results showed some utility of user gaze in managing alarms given how acknowledgement occurred more often when the acknowledgement methods and parameters matched; however, further design research is necessary to translate the utility into clear performance or productivity benefits. / Master of Science / Industrial control rooms are notorious for having too many alarms triggered within minutes and operators are hindered by responding to these alarms as opposed to the actual process faults. Existing alarm management research and applications have already reduced nuisance alarms by filtering out those correlated to one another according to historical data or plant models. However, existing approaches have not eliminated the process parameters that operators already expect to reach alarm thresholds. In other words, current alarm management has not adapted for operator awareness of impending alarms. This study explored how eye-tracking might be used to acknowledge alarms anticipated by operators, thereby reducing uninformative alarms and interruption to operator work. The participants performed an alarm monitoring task while trying to maintain a fluctuating parameter within an acceptable range. While participants liked the gaze-based acknowledgement methods, their performance on the parameter control task did not improve over conditions without any alarm acknowledgement. The alarm monitoring task may not have received sufficient attention to induce an observable benefit. The characteristics of the parameter seemed to have a larger effect on participants' attention than the muted alarm presentation associated with the gaze-based acknowledgment. Further research is necessary to refine the current design to induce the postulated attention and performance benefits with gaze-based acknowledgement.

Identiferoai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/107850
Date21 January 2022
CreatorsHerdt, Katherine Elizabeth
ContributorsIndustrial and Systems Engineering, Lau, Nathan, Klauer, Charlie, LeBlanc, Katya
PublisherVirginia Tech
Source SetsVirginia Tech Theses and Dissertation
LanguageEnglish
Detected LanguageEnglish
TypeThesis
FormatETD, application/pdf, application/pdf
RightsCreative Commons Attribution 4.0 International, http://creativecommons.org/licenses/by/4.0/

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