Attention evaluation with eye tracking glasses for EEG-based emotion recognition

Shi, Zhenfeng; Zhou, Chang; Zheng, Wei‐Long; Lu, Bao-Liang

doi:10.1109/ner.2017.8008298

Cited by 10 publications

(12 citation statements)

References 11 publications

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“…To remove unlikely data, we only considered fixations of more than 50 ms to remove unlikely data, following Bläsing and Bornewasser (2020) and Wang et al (2021). The effective fixation duration is regularly more than 50 ms (Shi et al, 2017), whereas a saccade typically lasts less than 50 ms (Godwin et al, 2015). In a recent survey of eye‐movement researchers, Hessels et al (2018) found that the functions associated with fixations are information processing and image stabilization, while the function associated with saccades is a new image on the fovea.…”

Section: Methodsmentioning

confidence: 99%

The influence of anthropomorphic cues in retailing: The moderating effect of the vice versus virtue products

Londoño

Maya

2022

Psychology and Marketing

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In retail environments, consumers are constantly exposed to in‐store marketing communication activities. However, relatively little is known about the attribution of human traits to this communication tool. The current research focuses on how anthropomorphizing retail cues such as dump bins influences consumer behavior and the moderating effect of the vice‐virtue character of the displayed products. Using eye‐tracking technology in an ecological shopping environment, we tracked shoppers' gazes through the store and analyzed their visual attention. Results show that attaching anthropomorphic forms to dump bins positively affects attitudes toward the displayed products. In addition, we demonstrate that displaying a vice product in an anthropomorphic dump bin increases both attitude toward the product and purchase intention, compared to the display of a virtue product. These findings suggest that anthropomorphism has an empathy‐helping underlying psychological mechanism that, when applied to retail communication activities, can contribute to justifying the purchase of vice products.

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Section: Methodsmentioning

confidence: 99%

The influence of anthropomorphic cues in retailing: The moderating effect of the vice versus virtue products

Londoño

Maya

2022

Psychology and Marketing

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“…Attention Monitoring holds publications that focus on monitoring the visual attention behavior over the course of a specific activity or a period of time (Jiang et al, 2016 ; Shi et al, 2017 ; Xu et al, 2018 ; Abdelrahman et al, 2019 ; Khosravan et al, 2019 ; Lounis et al, 2021 ; Xia et al, 2021 ; Peysakhovich et al, 2022 ). This was sometimes related to other tasks, such as reaction or response time prediction (Moacdieh and Sarter, 2017 ; Li et al, 2022 ), or modeling a participant's conversation engagement (Ishii et al, 2013 ).…”

Section: Domains and Tasksmentioning

confidence: 99%

“…We focused on features directly related to scanpaths, fixations, saccades, or AOIs for feature engineering. We excluded any blink features, pupil features, or features computed from additional modalities, such as keyboard keystrokes (Giannakos et al, 2019 ; Wang et al, 2020 ), thermal imaging (Abdelrahman et al, 2019 ), Electroencephalogram (EEG) (Shi et al, 2017 ; Giannakos et al, 2019 ; Moon et al, 2021 ), and physiological monitoring wristbands (Giannakos et al, 2019 ). Moving forward, when we refer to feature or relevant feature, this is what we mean.…”

Section: Machine Learning and Scanpathsmentioning

confidence: 99%

A review of machine learning in scanpath analysis for passive gaze-based interaction

Mohamed Selim,

Barz,

Bhatti

et al. 2024

Front. Artif. Intell.

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The scanpath is an important concept in eye tracking. It refers to a person's eye movements over a period of time, commonly represented as a series of alternating fixations and saccades. Machine learning has been increasingly used for the automatic interpretation of scanpaths over the past few years, particularly in research on passive gaze-based interaction, i.e., interfaces that implicitly observe and interpret human eye movements, with the goal of improving the interaction. This literature review investigates research on machine learning applications in scanpath analysis for passive gaze-based interaction between 2012 and 2022, starting from 2,425 publications and focussing on 77 publications. We provide insights on research domains and common learning tasks in passive gaze-based interaction and present common machine learning practices from data collection and preparation to model selection and evaluation. We discuss commonly followed practices and identify gaps and challenges, especially concerning emerging machine learning topics, to guide future research in the field.

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“…Furthermore, there are 3 articles that used the combination of EEG with fixations in the investigations. In a study by Shi et al (2017), an attention evaluation method is proposed with the combination of EEG, fixations, and scan path for the automated classification of high-and low-quality data using a spatial-temporal scan path analysis. According to a study by Czyzewski et al (2017), they proposed a multimodal approach for polysensory treatment and stimulation of noncommunicative subjects and classified the real and imaginary motion of limbs using gaze fixation points and EEG.…”

Section: Fixationmentioning

confidence: 99%

Eye-Tracking Feature Extraction for Biometric Machine Learning

2022

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ContextEye tracking is a technology to measure and determine the eye movements and eye positions of an individual. The eye data can be collected and recorded using an eye tracker. Eye-tracking data offer unprecedented insights into human actions and environments, digitizing how people communicate with computers, and providing novel opportunities to conduct passive biometric-based classification such as emotion prediction. The objective of this article is to review what specific machine learning features can be obtained from eye-tracking data for the classification task.MethodsWe performed a systematic literature review (SLR) covering the eye-tracking studies in classification published from 2016 to the present. In the search process, we used four independent electronic databases which were the IEEE Xplore, the ACM Digital Library, and the ScienceDirect repositories as well as the Google Scholar. The selection process was performed by using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) search strategy. We followed the processes indicated in the PRISMA to choose the appropriate relevant articles.ResultsOut of the initial 420 articles that were returned from our initial search query, 37 articles were finally identified and used in the qualitative synthesis, which were deemed to be directly relevant to our research question based on our methodology.ConclusionThe features that could be extracted from eye-tracking data included pupil size, saccade, fixations, velocity, blink, pupil position, electrooculogram (EOG), and gaze point. Fixation was the most commonly used feature among the studies found.

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Attention evaluation with eye tracking glasses for EEG-based emotion recognition

Cited by 10 publications

References 11 publications

The influence of anthropomorphic cues in retailing: The moderating effect of the vice versus virtue products

The influence of anthropomorphic cues in retailing: The moderating effect of the vice versus virtue products

A review of machine learning in scanpath analysis for passive gaze-based interaction

Eye-Tracking Feature Extraction for Biometric Machine Learning

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