• Architectural research
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• v.22 no.4
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• pp.155-162
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• 2020

Numerous scholars have explored the modeling, control, and optimization of energy systems in buildings, offering new insights about technology and environments that can advance industry innovation. Eye trackers deliver objective eye-gaze data about visual and attentional processes. Due to its flexibility, accuracy, and efficiency in research, eye tracking has a control scheme that makes measuring rapid eye movement in three-dimensional space possible (e.g., virtual reality, augmented reality). Because eye movement is an effective modality for digital interaction with a virtual environment, tracking how users scan a visual field and fix on various digital objects can help designers optimize building environments and materials. Although several scholars have conducted Virtual Reality studies in three-dimensional space, scholars have not agreed on a consistent way to analyze eye tracking data. We conducted eye tracking experiments using objects in three-dimensional space to find an objective way to process quantitative visual data. By applying a 12 × 12 grid framework for eye tracking analysis, we investigated how people gazed at objects in a virtual space wearing a headmounted display. The findings provide an empirical base for a standardized protocol for analyzing eye tracking data in the context of virtual environments.

• Journal of the Ergonomics Society of Korea
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• v.35 no.5
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• pp.391-401
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• 2016

Objective: This study aims to examine domestic literature on eye-tracking in the design area, and to present new eye-tracking application directions. Background: Eye-tracking was introduced in the experimental psychology field for the first time in the 1950s. Eye-tracking has high utilization values in the design application area because eye-tracking can accumulate data on what people see, providing the quantitative values on eye movement. Method: This study examined the papers published in domestic journals, as well as the papers presented in conferences from 2000 to 2016 through DBPIA. Results: Although the use of eye-tracking technology was slightly meager in the product design area, it has been actively used for the evaluation analyses of preference and attention in architecture/public design. Eye-tracking also presented a method to design advertisement that is helpful to advertisement effect measurement, and product salesin the advertisement design area. Since detail psychological analysis is possible, the application of eye-tracking in the studies related with user interface has been active. Conclusion: The eye-tracking technology is projected to be actively used as a new interface means, such as in helping in disabled people's communication and in device control, in addition to conventional application areas. Application: This study would be of help to find future research areas of eye-tracking.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.91-98
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• 2019

The purpose of this study was to develop and test an eye tracker focusing on early childhood participants, based on the characteristics of early childhood eye tracking studies. Eye tracking collects eye movement data of the subject, which provides scientific evidence of human cognition and thinking. The researcher built a Do It Yourself eye tracker camera module from general electronic components, and used Viewpoint analysis software from Arrington Research. The researcher compared the eye tracking data between the DIY eye tracker group and Tobii Pro eye tracker group, which provides a professional eye tracking system. Eye tracking data was collected from 52 five-year old children. The average proportion of valid trials between the two groups was compared with t test, and no significant difference was found. This result indicates that the DIY eye tracker can be used to collect valid eye tracking data from young children under certain research environment.

• Asia Pacific Journal of Corpus Research
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• v.5 no.1
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• pp.23-36
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• 2024

This research centers on the Taiwan Eye-Movement Corpus of Spanish (TECS), a specially created corpus comprising eye-tracking data from Chinese-speaking learners of Spanish as a third language in Taiwan. Its primary purpose is to explore the broad utility of TECS in understanding language learning processes, particularly the initial stages of language learning. Constructing this corpus involves gathering data on eye-tracking, reading comprehension, and language proficiency to develop a machine-learning model that predicts learner behaviors, and subsequently undergoes a predictability test for validation. The focus is on examining attention in input processing and their relationship to language learning outcomes. The TECS eye-tracking data consists of indicators derived from eye movement recordings while reading Spanish sentences with temporal references. These indicators are obtained from eye movement experiments focusing on tense verbal inflections and temporal adverbs. Chinese expresses tense using aspect markers, lexical references, and contextual cues, differing significantly from inflectional languages like Spanish. Chinese-speaking learners of Spanish face particular challenges in learning verbal morphology and tenses. The data from eye movement experiments were structured into feature vectors, with learner behaviors serving as class labels. After categorizing the collected data, we used two types of machine learning methods for classification and regression: Random Forests and the k-nearest neighbors algorithm (KNN). By leveraging these algorithms, we predicted learner behaviors and conducted performance evaluations to enhance our understanding of the nexus between learner behaviors and language learning process. Future research may further enrich TECS by gathering data from subsequent eye-movement experiments, specifically targeting various Spanish tenses and temporal lexical references during text reading. These endeavors promise to broaden and refine the corpus, advancing our understanding of language processing.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.223-224
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• 2019

본 논문에서는 카메라의 실시간 영상에서 얻을 수 있는 데이터를 수집 및 분석하여 일반인들에게 스마트폰의 실제 사용량, 최적화면 표현, 그리고 건조증 위험도의 정보를 제공하는 "i-eye" 응용 앱을 제안하여 눈 건강관리를 가능하게 한다. 제안하는 앱은 발전된 스마트 폰을 기반으로 동작되며 아이트래킹(eye-gaze tracking), 영상거리측정(image distance measurement), 눈 데이터분석(eye data analysis)의 3가지 핵심기술을 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.826-840
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• 2020

Vertigo is one of the most common complaints encountered by physicians and the patients are steadily increasing. These patients are exposed to the risk of secondary accidents such as falls due to vertigo. There are two ways to improve this symptom: medication and rehabilitation. Although temporary symptomatic improvement may be expected in patients treated with medication, vertigo may recur and medication can delay central compensation. In contrast vestibular rehabilitation exploits central mechanisms of neuroplasticity to increase postural stability and enhance visual-vestibular interactions in situations that generate conflicting sensory information. However, vestibular rehabilitation may be compromised by incorrect performance of exercises, and there is a need for active effort and interest from the patient during rehabilitation. To solve these problems, we decided to apply FOVE HMD for eye-tracking and Unity3D to create virtual reality. The proposed eye-tracking based algorithm calculates the concentration of users with eye tracking data and calculates the motion width of the patient with nystagmus, thus the severity of the patient according to the score can be determined. According to our experimental test against healty group and patients group, this result showed the meaningful data to use define the contents result.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.645-654
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• 2019

The purpose of this study was to collect and analyze personal bio data and social network services (SNS) data, derive user preference and user life pattern, and propose intuitive and precise user modeling. This study not only tried to conduct eye tracking experiments using various smart devices to be the ground of the recommendation system considering the attribute of smart devices, but also derived classification preference by analyzing eye tracking data of collected bio data and SNS data. In addition, this study intended to combine and analyze preference of the common classification of the two types of data, derive final preference by each smart device, and based on user life pattern extracted from final preference and collected bio data (amount of activity, sleep), draw the similarity between users using Pearson correlation coefficient. Through derivation of preference considering the attribute of smart devices, it could be found that users would be influenced by smart devices. With user modeling using user behavior pattern, eye tracking, and user preference, this study tried to contribute to the research on the recommendation system that should precisely reflect user tendency.

• Korean Institute of Interior Design Journal
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• v.25 no.3
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• pp.51-59
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• 2016

The technique for Eye-tracking is to trace the movements of pupils so that the eye's exploration response to be digitized. The procedure of Observation Experiment shows a mutual environmental characteristics between men and measuring devices. In order to improve the reliability and to secure the objectivity of the data acquired from eye-tracking, it is very important to analyze the procedures for the experiment to be prepared and the test data to be saved. Based on this viewpoint, the convergent exploration activities at the observation experiment with the objects of sport images were examined to find out what influences the context effect given by experimental environments have on this experiment. In addition, the starting time of attention affecting the reliability of observation data has been estimated. When the observation time is to be subdivided by the unit of second. The attention disperses for the individual characteristics to be appreciated. However, in case of analysis by the overall average, there was the problem that the section of attention dispersed to make it difficult to analyze the subjects' observation features. The study results made it possible to understand the physiological characteristics which were near unconsciousness, when there was an intensive attention for the first 3 seconds and the observation data were shown to be in ordinary range after 4 seconds. The analysis of observation with the focus of the intensive attention enabled the analysis with the first 3 seconds excepted so that it might approach the ordinary range of observation data. The distribution of attention for the first 3 seconds showed the intensive attention, which was on the center. The emergence of intensive attention and the overlapping of the centers can be considered as a context effect due to the correction for the preparing process of experiment. Accordingly, it is thought to be helpful to the security of objectivity and the construction of reliability of eye-tracking data to analyze the observation features shown after the deletion of the data for the first 3 seconds.

• Journal of Fashion Business
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• v.24 no.6
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• pp.63-79
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• 2020

This study analyze consumers' unconscious visual attention to color and images of internet shopping malls by using eye-tracking method. Twenty-nine participants, including 15 females and 14 males, participated. The average ages of the male and female participants were 27.3 years and 27.7 years, respectively. Ten images of five layouts (multi-composition images, single-model images, gender-composed images, videos, and moving banner images) of internet shopping malls were shown on an eye-tracker computer screen. Quantitative analyses of the eye-tracking responses were conducted. SPSS was used to analyze the descriptive characteristics and to conduct an independent-sample t-test, along with an ANOVA. The data analysis showed that the image area generally had the shortest time to first fixation (TFF), the longest duration of fixation (DOF), the highest number of fixations (NOF), and the highest numbers of revisits(NOR).Notably, visual attention towards female models was high among various images. The results can be used to improve credibility and design online shopping layout with a scientific evidence that helps consumers through their purchase decisions.

• Food Science and Preservation
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• v.31 no.3
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• pp.408-422
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• 2024

This study analyzed the factors that influence menu choices through eye-tracking and questionnaires in menu design. Demographic data of subjects coincided with choosing a menu and eye-tracking data. Hot Crispy Chicken Burger is the most popular menu. The study found that regardless of the selected menu, the menu name (35.5 seconds), price (21.6 seconds), and image (16.0 seconds) were viewed the longest, followed by country of origin (8.81 seconds), calories (4.6 seconds), and special indications (p<0.05). The menu name and image were checked more frequently, while calorie information was checked less often. As a result of analyzing various factors that influence menu selection through, Consumer experience and image greatly influenced menu choices. Therefore, if you want to receive a menu selection, it is considered effective to make good use of the menu name and image. In results of principal component analysis (PCA) by gender showed. Men had the longest price in the fixation duration. But, for females, there was a significant difference in gaze fixation when they took the exam, with menu names and special indications being important selection criteria. Since the results show that selection criteria and information acquisition methods differ depending on gender, this research is thought to be able to suggest directions for menu design.