Ocular Indicators of Mental Workload: A Comparison of Scanpath Entropy and Fixations Clustering

Maggi, Piero; Ricciardi, Orlando; Nocera, Francesco Di

doi:10.1007/978-3-030-32423-0_13

Cited by 5 publications

(5 citation statements)

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“…skin sweating increasing, heart rate variability, brain electrical activity increasing in specific rhythms over particular cortical sites) [13][14][15]. Nevertheless, it is evident the need of reducing at minimum the invasiveness related to monitoring methodologies during the working tasks to do not negatively interfere with the workers' activities and comfort [16]. This last consideration is very consistent with the concept of remote and contactless monitoring.…”

Section: Introductionmentioning

confidence: 64%

Contactless Physiological Assessment of Mental Workload During Teleworking-like Task

Ronca

Rossi

Florio³

et al. 2020

Communications in Computer and Information Science

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Human physiological parameters have been proven as reliable and objective indicators of user's mental states, such as the Mental Workload. However, standard methodologies for evaluating physiological parameters generally imply a certain grade of invasiveness. It is largely demonstrated the relevance of monitoring workers to improve their working conditions. A contactless approach to estimate workers' physiological parameters would be highly suitable because it would not interfere with the working activities and comfort of the workers. Additionally, it would be very appropriate for teleworking settings. In this paper, participants' facial videos were recorded while dealing with arithmetic tasks with the aims to 1) evaluate the possibility to estimate their Heart Rate (HR) through facial video analysis, and 2) assess their mental workload under the different experimental conditions. The HR was also estimated through last-generation smartwatches. The results demonstrated that there was no difference between the HR estimated via the contactless technique and smartwatches, and how it was possible to discriminate the two mental workload levels by employing the proposed methodology.

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Section: Introductionmentioning

confidence: 64%

Contactless Physiological Assessment of Mental Workload During Teleworking-like Task

Ronca

Rossi

Florio³

et al. 2020

Communications in Computer and Information Science

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“…The two conditions were: 1) a driving-only condition and 2) a dual-task condition in which secondary mundane tasks (such as radio tuning or navigation setting) were concurrently required. It was expected to find a more grouped fixation pattern in the dual-task condition, as the visuospatial demand is known to produce fixations grouping Maggi, Ricciardi & Di Nocera, 2019). Indeed, changes in task load imposed by the dual-task condition designed for this study is clearly of the visuospatial type (as opposed to the temporal demand that would be in action if the change in taskload was due to a faster pace).…”

Section: Discussionmentioning

confidence: 97%

Scanpath analysis into the wild: the spatiotemporal distribution of fixations as an indicator of driver’s mental workload

Nocera¹,

Ricciardi

Mastrangelo³

et al. 2020

Proceedings of the Human Factors and Ergonomics Society Annual

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Past studies using the distribution of eye fixations as an indicator of mental workload are limited to simulations and laboratory tasks. Hence, this assessment strategy has not yet been proven useful in real- world settings. In order to bridge this gap, in this study eye movements of a group of individuals were recorded while driving a car in a suburban road. Drivers’ scanpaths during driving and during driving while performing mundane secondary tasks were compared in this study. A more grouped pattern of fixations was expected in the dual-task condition than in the driving-only condition. As expected, results showed the effectiveness the spatiotemporal distribution of fixations in correctly discriminating between task load conditions, therefore indicating its usefulness for assessing mental workload also in complex real-world tasks.

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“…The aim of this second study is to perform such a comparison. A preliminary account on this experiment was presented at the H-WORKLOAD 2019 workshop (Maggi et al, 2019 ).…”

Section: Methodsmentioning

confidence: 99%

“…This research was supported by the European Office of Aerospace Research and Development through Grant #FA9550-18-1-0203 awarded to FDN. A preliminary account on Experiment 2 was presented at the H-WORKLOAD 2019 workshop (Maggi et al, 2019 ).…”

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confidence: 99%

Sensitivity of the Spatial Distribution of Fixations to Variations in the Type of Task Demand and Its Relation to Visual Entropy

Maggi

Nocera

2021

Front. Hum. Neurosci.

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Ocular activity is known to be sensitive to variations in mental workload, and recent studies have successfully related the distribution of eye fixations to the mental load. This study aimed to verify the effectiveness of the spatial distribution of fixations as a measure of mental workload and its sensitivity to different types of demands imposed by the task: mental, temporal, and physical. To test the research hypothesis, two experimental studies were run: Experiment 1 evaluated the sensitivity of an index of spatial distribution (Nearest Neighbor Index; NNI) to changes in workload. A sample of 30 participants participated in a within-subject design with different types of task demands (mental, temporal, physical) applied to Tetris game; Experiment 2 investigated the accuracy of the index through the analysis of 1-min epochs during the execution of a visual-spatial task (the “spot the differences” puzzle game). Additionally, NNI was compared to a better-known ocular mental workload index, the entropy rate. The data analysis showed a relation between the NNI and the different workload levels imposed by the tasks. In particular: Experiment 1 demonstrated that increased difficulty, due to higher temporal demand, led to a more dispersed pattern with respect to the baseline, whereas the mental demand led to a more grouped pattern of fixations with respect to the baseline; Experiment 2 indicated that the entropy rate and the NNI show a similar pattern over time, indicating high mental workload after the first minute of activity. That suggests that NNI highlights the greater presence of fixation groups and, accordingly, the entropy indicates a more regular and orderly scanpath. Both indices are sensitive to changes in workload and they seem to anticipate the drop in performance. However, the entropy rate is limited by the use of the areas of interest, making it impossible to apply it in dynamic contexts. Conversely, NNI works with the entire scanpath and it shows sensitivity to different types of task demands. These results confirm the NNI as a measure applicable to different contexts and its potential use as a trigger in adaptive systems implemented in high-risk settings, such as control rooms and transportation systems.

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Ocular Indicators of Mental Workload: A Comparison of Scanpath Entropy and Fixations Clustering

Cited by 5 publications

References 10 publications

Contactless Physiological Assessment of Mental Workload During Teleworking-like Task

Contactless Physiological Assessment of Mental Workload During Teleworking-like Task

Scanpath analysis into the wild: the spatiotemporal distribution of fixations as an indicator of driver’s mental workload

Sensitivity of the Spatial Distribution of Fixations to Variations in the Type of Task Demand and Its Relation to Visual Entropy

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