Target eccentricity and form influences disparity vergence eye movements responses: A temporal and dynamic analysis

Yaramothu, Chang; Jaswal, Rajbir; Alvarez, Tara L.

doi:10.16910/jemr.12.4.7

Cited by 3 publications

(1 citation statement)

References 56 publications

(71 reference statements)

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“…In most LSCD ailment eyes, a frail contrast is found between the cornea and sclera especially that the sclera tends to be more yellowish. Therefore, an image contrast correction method namely gamma correction will be utilized on the captured RGB converted to RGB image [33]. The correction method will correct the captured image brightness.…”

Section: Image Contrast Correction Methodsmentioning

confidence: 99%

Computerized Detection of Limbal Stem Cell Deficiency from Digital Cornea Images

Mahmoud¹,

Khafga²,

Alharbi³

2022

Computer Systems Science and Engineering

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Limbal Stem Cell Deficiency (LSCD) is an eye disease that can cause corneal opacity and vascularization. In its advanced stage it can lead to a degree of visual impairment. It involves the changing in the semispherical shape of the cornea to a drooping shape to downwards direction. LSCD is hard to be diagnosed at early stages. The color and texture of the cornea surface can provide significant information about the cornea affected by LSCD. Parameters such as shape and texture are very crucial to differentiate normal from LSCD cornea. Although several medical approaches exist, most of them requires complicated procedure and medical devices. Therefore, in this paper, we pursued the development of a LSCD detection technique (LDT) utilizing image processing methods. Early diagnosis of LSCD is very crucial for physicians to arrange for effective treatment. In the proposed technique, we developed a method for LSCD detection utilizing frontal eye images. A dataset of 280 eye images of frontal and lateral LSCD and normal patients were used in this research. First, the cornea region of both frontal and lateral images is segmented, and the geometric features are extracted through the automated active contour model and the spline curve. While the texture features are extracted using the feature selection algorithm. The experimental results exhibited that the combined features of the geometric and texture will exhibit accuracy of 95.95%, sensitivity of 97.91% and specificity of 94.05% with the random forest classifier of n = 40. As a result, this research developed a Limbal stem cell deficiency detection system utilizing features' fusion using image processing techniques for frontal and lateral digital images of the eyes.

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Section: Image Contrast Correction Methodsmentioning

confidence: 99%

Computerized Detection of Limbal Stem Cell Deficiency from Digital Cornea Images

Mahmoud¹,

Khafga²,

Alharbi³

2022

Computer Systems Science and Engineering

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Using immersive virtual reality to modify body image

Irvine

Maalin

et al. 2020

Body Image

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We tested the efficacy of a training programme, delivered in virtual reality (VR), to modify the perceptualboundary between what participants classify as a fat versus a thin body. Three cohorts of 20 female volunteers 4 with high body image concerns were recruited to two intervention groups and one control group. All participants 5 completed a 4-day training programme in VR where they categorised a series of 3D models as either thin or fat; 6 one intervention group was presented with the stimuli briefly, while the other group had no time limits imposed. 7Both intervention groups were given inflationary feedback to shift their categorisations of the stimulus models 8 towards higher BMIs. Our results show that, compared to controls, both intervention groups shifted their 9 categorical boundaries between Day 1 and follow-up on Day 14. Unlimited stimulus presentation times were 10 associated with a larger training effect. Furthermore, both intervention groups experienced statistically significant 11 reductions in their concerns about their own body shape, weight and eating habits. However, only in the group 12 with longer stimulus presentation times were these reductions consistent with a clinically meaningful effect. These 13 findings suggest that manipulating categorical perception in VR might provide a complementary addition to 14 existing treatments for eating disorders.

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Eye-hand movement in 3D displays: A structural equation modeling approach

Prasetyo

Widyaningrum

2021

IOP Conf. Ser.: Mater. Sci. Eng.

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Eye-hand movements are two important parameters to evaluate the User Experience (UX) in the stereoscopic display (3D). The current study utilized structural equation modeling (SEM) to derive the causal relationship between parallax, index of difficulty (ID), eye movement, hand movement, eye index performance (IP eye), and hand index performance (IP hand) simultaneously. 10 participants voluntarily participated in the current study and they were asked to perform a multi-directional Fitts’ Law task in the projection-based stereoscopic display. The results indicated that parallax had significant effects on eye movement time and hand movement time. In addition, ID was found to have significant effects on eye movement time and hand movement time. Interestingly, parallax and ID were found to have significant effects on IP eye, however, no significant effects were found on IP hand. These findings could be very beneficial for UX researchers and projection-based stereoscopic display developers especially in terms of evaluating UX of an interface.

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Target eccentricity and form influences disparity vergence eye movements responses: A temporal and dynamic analysis

Cited by 3 publications

References 56 publications

Computerized Detection of Limbal Stem Cell Deficiency from Digital Cornea Images

Computerized Detection of Limbal Stem Cell Deficiency from Digital Cornea Images

Using immersive virtual reality to modify body image

Eye-hand movement in 3D displays: A structural equation modeling approach

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