Measurement of viewing distances and angles for eye tracking under different lighting conditions

Paulus, Yesaya Tommy; Hiramatsu, Chihiro; Syn, Yvonne Kam Hwei; Remijn, Gerard B.

doi:10.1109/icacomit.2017.8253386

Cited by 8 publications

(3 citation statements)

References 8 publications

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“…Eye tracking has been used in the last decade, especially in the field of neuromarketing [10][11][12][13][14][15][16]. Recently, research has emerged pointing to the possibilities of its application and use in the educational process [17][18][19][20] or virtual reality [21].…”

Section: Related Workmentioning

confidence: 99%

Application Experiences Using IoT Devices in Education

et al. 2020

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The Internet of Things (IoT) is becoming a regular part of our lives. The devices can be used in many sectors, such as education and in the learning process. The article describes the possibilities of using commonly available devices such as smart wristbands (watches) and eye tracking technology, i.e., using existing technical solutions and methods that rely on the application of sensors while maintaining non-invasiveness. By comparing the data from these devices, we observed how the students’ attention affects their results. We looked for a correlation between eye tracking, heart rate, and student attention and how it all impacts their learning outcomes. We evaluate the obtained data in order to determine whether there is a degree of dependence between concentration and heart rate of students.

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Section: Related Workmentioning

confidence: 99%

Application Experiences Using IoT Devices in Education

et al. 2020

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“…9. Controls moved to the ideal viewing distance and angle relative to the sensor [36], and patients were affected by impaired motor skills.…”

Section: Table 5 Trends For Measured Variables In Patients and Controlsmentioning

confidence: 99%

Eye-tracking control of an adjustable electric bed: construction and validation by immobile patients with multiple sclerosis

Kopeček

Kremláček

2023

J NeuroEngineering Rehabil

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Background In severe conditions of limited motor abilities, frequent position changes for work or passive and active rest are essential bedside activities to prevent further health complications. We aimed to develop a system using eye movements for bed positioning and to verify its functionality in a control group and a group of patients with significant motor limitation caused by multiple sclerosis. Methods The eye-tracking system utilized an innovative digital-to-analog converter module to control the positioning bed via a novel graphical user interface. We verified the ergonomics and usability of the system by performing a fixed sequence of positioning tasks, in which the leg and head support was repeatedly raised and then lowered. Fifteen women and eleven men aged 42.7 ± 15.9 years in the control group and nine women and eight men aged 60.3 ± 9.14 years in the patient group participated in the experiment. The degree of disability, according to the Expanded Disability Status Scale (EDSS), ranged from 7 to 9.5 points in the patients. We assessed the speed and efficiency of the bed control and the improvement during testing. In a questionnaire, we evaluated satisfaction with the system. Results The control group mastered the task in 40.2 s (median) with an interquartile interval from 34.5 to 45.5 s, and patients mastered the task in in 56.5 (median) with an interquartile interval from 46.5 to 64.9 s. The efficiency of solving the task (100% corresponds to an optimal performance) was 86.3 (81.6; 91.0) % for the control group and 72.1 (63.0; 75.2) % for the patient group. Throughout testing, the patients learned to communicate with the system, and their efficiency and task time improved. A correlation analysis showed a negative relationship (rho = − 0.587) between efficiency improvement and the degree of impairment (EDSS). In the control group, the learning was not significant. On the questionnaire survey, sixteen patients reported gaining confidence in bed control. Seven patients preferred the offered form of bed control, and in six cases, they would choose another form of interface. Conclusions The proposed system and communication through eye movements are reliable for positioning the bed in people affected by advanced multiple sclerosis. Seven of 17 patients indicated that they would choose this system for bed control and wished to extend it for another application.

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“…In order to perform password authentication, the participant was standing in the middle in front of the monitor at a viewing distance of approximately 49 cm, as indicated by a floor mark. This viewing distance is close to the border of the operating distance of the eye-tracker device (for details, see [17]), and eye registration was unsuccessful when the participant was standing too close or too far away from the display [18]. The reason the participant performed the task while standing was to simulate a situation in which he/she would use eye tracking to register on an ATM-machine with a password.…”

Section: Apparatusmentioning

confidence: 99%

What Kind of Grid Formations and Password Formats are Useful for Password Authentication with Eye-Gaze-Based Input?

Paulus¹,

Remijn²

2019

J Ergonomics

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This study investigates which grid formations and password formats are useful for password authentication by means of eye-gazebased input. Sixteen grid formations were made, in between 3×3 to 6×6 cells (columns-by-rows), for three password formats. The formats were an alphanumeric format, a pattern format, and a picture format. The participants were asked to memorize a 4-object or a 6-object password and register (Task 1), confirm (Task 2), and log in (Task 4) the password on each of the 16 grids with eye-gaze-based input. In Task 3, the participants evaluated each grid with a rating scale. The results showed that task-completion time was mostly shorter for the alphanumeric password format than for the pattern or picture format. Task-completion time of 4-object or 6-object passwords generally increased as the grid density increased, while the task-success rate at the first attempt decreased when the grid density increased. Task-completion time often was longer for grids with more rows than columns (vertical formations, e.g., 3×4 cells) than for grids with more columns than rows (horizontal formations, e.g., 4×3 cells). These results suggest that password authentication with eye-gaze-based input is best performed on horizontal grids with relatively few cells and a traditional (alphanumeric) format.

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Measurement of viewing distances and angles for eye tracking under different lighting conditions

Cited by 8 publications

References 8 publications

Application Experiences Using IoT Devices in Education

Application Experiences Using IoT Devices in Education

Eye-tracking control of an adjustable electric bed: construction and validation by immobile patients with multiple sclerosis

What Kind of Grid Formations and Password Formats are Useful for Password Authentication with Eye-Gaze-Based Input?

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