The statistical challenge of scan-path analysis

Coco, Moreno I.

doi:10.1109/hsi.2009.5091008

Cited by 10 publications

(8 citation statements)

References 11 publications

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“…Comparing scanpaths of multiple participants can help find regularities or similar patterns between different participants. Many of the presented visualization techniques can be used for scanpath comparison [WHRK06, Coc09, GH10b, TTS10, RHOL13, RHB*14, EYH15]. This is just one example of how the analysis task influences the type of visualization technique for an evaluation.…”

Section: Discussion Of Future Research Directionsmentioning

confidence: 99%

Visualization of Eye Tracking Data: A Taxonomy and Survey

Blascheck

Kurzhals

Raschke

et al. 2017

Computer Graphics Forum

214

115

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This survey provides an introduction into eye tracking visualization with an overview of existing techniques. Eye tracking is important for evaluating user behaviour. Analysing eye tracking data is typically done quantitatively, applying statistical methods. However, in recent years, researchers have been increasingly using qualitative and exploratory analysis methods based on visualization techniques. For this state‐of‐the‐art report, we investigated about 110 research papers presenting visualization techniques for eye tracking data. We classified these visualization techniques and identified two main categories: point‐based methods and methods based on areas of interest. Additionally, we conducted an expert review asking leading eye tracking experts how they apply visualization techniques in their analysis of eye tracking data. Based on the experts' feedback, we identified challenges that have to be tackled in the future so that visualizations will become even more widely applied in eye tracking research.

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Section: Discussion Of Future Research Directionsmentioning

confidence: 99%

Visualization of Eye Tracking Data: A Taxonomy and Survey

Blascheck

Kurzhals

Raschke

et al. 2017

Computer Graphics Forum

214

115

View full text Add to dashboard Cite

show abstract

“…In this study, even the fixation duration was below 200 msec, it was added into consideration. On the other hand, in concentration condition, saccades appear to be visible, in other words, there must be a clear movement between fixations [6]. Fig.…”

Section: Discussionmentioning

confidence: 90%

“…In addition, movements between fixations is called saccades. In their investigation, Goldberg [5] and Coco [6] stated that scan path is a sequence of fixation and saccades.…”

Section: Introductionmentioning

confidence: 99%

Scan Path Based Approach to Detect Learner’s Concentration in Distance Learning System

Kimario¹,

Kamioka²

2017

IJLT

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 Abstract-Distance Learning (DL) systems have been growing recently due to the rapid advancement of Information and Communication Technology (ICT). However, each learner, who is attracted to take distance learning courses due to its convenience is always isolated. Therefore, it would be useful to take care of the learners more if the instructor could get information of the learner's condition such as where the learner is looking at and how long the learner takes to look at that particular point. This information is important to detect learners' concentration to the class, and thus it can be used for designing the content style of the class based on the learner's preference. In this study, the novel automatic approach to detect learner's concentration based on the content preference will be proposed. The main goal is to detect each learner's concentration based on the content style in a distance learning class session. In addition, this study will focus on real time distance learning class systems. During a real time class lesson, biological information such as fixation duration, fixation frequency, and saccade will be recorded in the eye tracking system and these data will be analysed. If the number of learners who are not concentrated on the content is larger than a threshold value, the alerting system will send a message to the instructor's display. Therefore, the instructor will change the content style accordingly. The proposed approach will be very useful in assisting the instructor to understand and determine the best content's model style to be used in the distance learning class based on learners preference.

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“…These recurrence methods are currently employed in many fields [Marwan et al 2013], and specifically have been claimed to be in use in research of eye-tracking data for almost a decade, most notably through the established works of [Richardson and Dale 2005], [Dale and Spivey 2005], , [Richardson and Dale 2006], [Richardson et al 2007], [Coco 2009], [Richardson et al 2009], [Lanatà et al 2011], [Anderson et al 2012], [Anderson et al 2013], and[Reuzel et al 2013] among others.…”

Section: Introductionmentioning

confidence: 99%

Eye-movement sequence statistics and hypothesis-testing with classical recurrence analysis

Keane

Cahill

Pelz

2014

Proceedings of the Symposium on Eye Tracking Research and Applications

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Dynamical systems analysis tools, like Recurrence Plotting (RP), allow for concise mathematical representations of complex systems with relatively simple descriptive metrics. These methods are invariant for phase-space trajectories of a time series from a dynamical system, allowing analyses on simplified data sets which preserve the system model's dynamics. In the past decade, recurrence methods have been applied to eye-tracking, but those analyses avoided Time-Delay Embedding (TDE). Without TDE, we lose the assumption that phase-space trajectories are being preserved in the recurrence plot. Thus, analysis has been typically limited to clustering fixation locations in the image space, instead of clustering data sequences in the phase space. We will show how classical recurrence analysis methods can be extended to allow for multi-modal data visualization and quantification, by presenting an open-source python implementation for analyzing eye movements.

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The statistical challenge of scan-path analysis

Cited by 10 publications

References 11 publications

Visualization of Eye Tracking Data: A Taxonomy and Survey

Visualization of Eye Tracking Data: A Taxonomy and Survey

Scan Path Based Approach to Detect Learner’s Concentration in Distance Learning System

Eye-movement sequence statistics and hypothesis-testing with classical recurrence analysis

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