Analyzing Eye Movement Complexity in Virtual Reality Environments | Chapter 3 | Science and Technology- Recent Updates and Future Prospects Vol. 6

This chapter advances the analysis of gaze dynamics by employing Multiscale Entropy (MSE) to evaluate 5020 binocular eye movement recordings from 407 college-aged participants. Utilizing the comprehensive GazeBaseVR dataset, this study investigates the complexity of user interactions across a variety of virtual reality (VR) tasks such as vergence, smooth pursuit, video viewing, reading, and random saccades. The data, collected at 250 Hz using an ET-enabled VR headset, provides a robust foundation for understanding the predictability and complexity of gaze patterns. By incorporating a longitudinal perspective from recordings taken up to six times over a 26-month period, this analysis deepens our understanding of eye movement behavior in VR environments. This chapter highlights the potential of MSE in crafting more intuitive and immersive VR interfaces, thereby enhancing user experience. Recent advancements and additional references have been included to discuss the evolving role of MSE in optimizing VR technology for personalized and comfortable user interactions.

 

Author (s) Details

Sahar Zandi

Department of Architecture, Texas A&M University, College Station, TX 77843, USA.

Gregory Luhan

Department of Architecture, Texas A&M University, College Station, TX 77843, USA.

 

Please see the book here:- https://doi.org/10.9734/bpi/strufp/v6/739

The Rich Afterimage Illusions under Head-Image Tilting and the Internal Visual Space Model. A New Theoretical Comprehending | Chapter 10 | Current Aspects in Pharmaceutical Research and Development Vol. 1

 Some features of the illusions arising from the movement of the observer’s eyes and/or head under the background of the positive afterimage of the entire visual scene (rich afterimage-rAI) when the head and/or afterimage are tilted are described. There are impairments of visual direction constancy and stability not just in the visual field but also in the near extrapersonal area under these situations. This can also happen when the eyes are in a fixed location in the orbits and the fixation point is changed by head movements. On the background of an inclined rAI, the illusion of a violation of the visual vertical is also described. It turns found that throughout a wide variety of ocular vergence states, the synthesis of the field of rAI is unaffected. The characteristics of the so-called "residual illusion" are detailed. After the rAI has been entirely attenuated, all phenomena that have developed against the background of rAI persist in total darkness for tens of seconds. This also pertains to skewed optical vertical perception. It is offered to explore the theory, implying full nonparticipation of the efferent oculomotor subsystem signals in the mechanisms of visual field constancy and gaze direction, based on the examination of the rAI illusions and special qualities of the rich afterimage itself. constancy. According to the hypothesis, the visually rich picture allows the visual system to create a stable visual field and calculate the observer's gaze direction only based on the signals in the visual flow. The hypothesis enables a logical interpretation of the key events seen in the experiments. When the head is tilted to the shoulder, an oblique 3-D rAI is observed, indicating that the internal visual space (IVS) model, not the images on the retinas, is the object of vision.

Author (S) Details

Gary M. Zenkin
Institute for Information Transmission Problems, (Kharkevich Institute) of Russian Academy of Sciences, Moscow, Russian Federation.

View Book :- https://stm.bookpi.org/CAPRD-V1/article/view/3321

An Efficient Machine Learning Model for Prediction of Dyslexia from Eye Fixation Events | Chapter 15 | New Approaches in Engineering Research Vol. 10

 Dyslexia is not curable, although dyslexics can achieve great success in school and in life with the right remedial support. Eye movement patterns during reading can help you understand dyslexia-related reading issues better. An eye-tracker can be used to capture eye movements and deduce the relationship between how eyes move in response to the words they read. In this study, raw eye tracking data was used to construct a collection of binocular fixation and saccade features based on statistical measurements. In this study, raw eye tracking data was used to construct a collection of binocular fixation and saccade features based on statistical measurements. To develop classification models for dyslexia prediction, machine learning techniques such as the Random Forest Classifier (RF), the Support Vector Machine (SVM) for classification, and the K-Nearest Neighbor (KNN) for prediction of dyslexia were examined. KNN exhibited 95 percent accuracy over a limited feature set related with fixations and saccades, compared to SVM and RF. These properties of the eyes can be used to create dyslexia prediction screening tools. Early discovery of dyslexia can help children get the treatment they need, helping them to succeed in school.

Author (S) Details

A. Jothi Prabha
Jyothishmathi Institute of Technology & Science, India.

R. Bhargavi
Vellore Institute of Technology University, Chennai, India.

B. Harish
VIT University, Chennai Campus, India.

View Book :- https://stm.bookpi.org/NAER-V10/article/view/2991

Study of the Rich Afterimage Illusions as an Instrument for Learning of Inflow On-screen Mechanisms for Visual Orientation in Space | Chapter 12 | Technological Innovation in Pharmaceutical Research Vol. 11

 In the article, Eye movements lead to a transformation of the 3-D visual field, representing a complex rotation and scale transformation of the near extrapersonal space with a centre somewhere in the region of a hypothetical "cyclopean eye," when using a complex 3-D configuration of reference points in the presence of structural rich afterimage (rAI) of the entire visual scene. Experiments have revealed that this also leads in the recalculation of the observer's gaze direction coordinates, purely based on input information and independent of oculomotor and even proprioceptive efferent system signals. Under distinct sorts of eye motions, three types of rAI illusions are described. These events are thought to be the work of "contextually" independent Screen Constancy Mechanisms (SCM), which function at the hypothetical Constant Visual Screen (CVS) level, according to a model proposed after 1976. This level of the visual system can still be called "pseudo-sensory," as it occurs before the creation (appearance) of the object-structured visual field. Certain circumstances impacting the degree of afterimage structural "richness" have also been examined in tests.

Author (S) Details

Gary M. Zenkin
Institute for Information Transmission Problems, (Kharkevich Institute) of Russian Academy of Sciences, Moscow, Russian Federation, Russia.

View Book :- https://stm.bookpi.org/TIPR-V11/article/view/3134