Assessing real world imagery in virtual environments for people with cognitive disabilities

People with cognitive disabilities are often socially excluded. We propose a system based on Virtual and Augmented Reality that has the potential to act as an educational and support tool in everyday tasks for people with cognitive disabilities. Our solution consists of two components: the first that enables users to train for several essential quotidian activities and the second that is meant to offer real time guidance feedback for immediate support. In order to illustrate the functionality of our proposed system, we chose to train and support navigation skills. Thus, we conducted a preliminary study on people with Down Syndrome (DS) based on a navigation task. Our experiment was aimed at evaluating the visual and spatial perception of people with DS when interacting with different elements of our system. We provide a preliminary evaluation that illustrates how people with DS perceive different landmarks and types of visual feedback, in static images and videos. Although we focused our study on people with DS, people with different cognitive disabilities could also benefit from the features of our solution. This analysis is mandatory in the design of a virtual intelligent system with several functionalities that aims at helping disabled people in developing basic knowledge in every day tasks

Assessing real world imagery in virtual environments for people with cognitive disabilities

People with cognitive disabilities are often socially excluded. We propose a system based on Virtual and Augmented Reality that has the potential to act as an educational and support tool in everyday tasks for people with cognitive disabilities. Our solution consists of two components: the first that enables users to train for several essential quotidian activities and the second that is meant to offer real time guidance feedback for immediate support. In order to illustrate the functionality of our proposed system, we chose to train and support navigation skills. Thus, we conducted a preliminary study on people with Down Syndrome (DS) based on a navigation task. Our experiment was aimed at evaluating the visual and spatial perception of people with DS when interacting with different elements of our system. We provide a preliminary evaluation that illustrates how people with DS perceive different landmarks and types of visual feedback, in static images and videos. Although we focused our study on people with DS, people with different cognitive disabilities could also benefit from the features of our solution. This analysis is mandatory in the design of a virtual intelligent system with several functionalities that aims at helping disabled people in developing basic knowledge in every day tasks

Seeing Our Blind Spots: Smart Glasses-Based Simulation to Increase Design Students’ Awareness of Visual Impairment

As the population ages, many will acquire visual impairments. To improve design for these users, it is essential to build awareness of their perspective during everyday routines, especially for design students. Although several visual impairment simulation toolkits exist in both academia and as commercial products, analog, and static visual impairment simulation tools do not simulate effects concerning the user’s eye movements. Meanwhile, VR and video see-through-based AR simulation methods are constrained by smaller fields of view when compared with the natural human visual field and also suffer from vergence-accommodation conflict (VAC) which correlates with visual fatigue, headache, and dizziness. In this paper, we enable an on-the-go, VAC-free, visually impaired experience by leveraging our optical see-through glasses. The FOV of our glasses is approximately 160 degrees for horizontal and 140 degrees for vertical, and participants can experience both losses of central vision and loss of peripheral vision at different severities. Our evaluation (n =14) indicates that the glasses can significantly and effectively reduce visual acuity and visual field without causing typical motion sickness symptoms such as headaches and or visual fatigue. Questionnaires and qualitative feedback also showed how the glasses helped to increase participants’ awareness of visual impairment

Instructional Message Design: Theory, Research, and Practice

Message design is all around us, from the presentations we see in meetings and classes, to the instructions that come with our latest tech gadgets, to multi-million-dollar training simulations. In short, instructional message design is the real-world application of instructional and learning theories to design the tools and technologies used to communicate and effectively convey information. This field of study pulls from many applied sciences including cognitive psychology, industrial design, graphic design, instructional design, and human performance technology to name just a few. In this book we visit several foundational theories that guide our research, look at different real-world applications, and begin to discuss directions for future best practice. For instance, cognitive load and multimedia learning theories provide best practice, PowerPoint and simulations are only a few of the multitude of applications, and special needs learners and designing for cultural inclusiveness are only two of many areas where effective messages design can improve outcomes. Studying effective instructional message design tools and techniques has and will continue to be a critical aspect of the overall instructional design process. Hopefully, this book will serve as an introduction to these topics and inspire your curiosity to explore further

Enhancement of Real-Time Object Detection and Tracking in Collaborative Environment using AI and Mixed Reality

The area of mixed reality has had rapid growth in recent years, with a notable rise in funding. This may be attributed to the rising recognition of the potential advantages associated with the integration of virtual information into the physical environment. The majority of contemporary mixed reality apps that rely on markers use algorithms for local feature identification and tracking. This study aims to enhance the accuracy of object recognition in complicated environment and enable real-time classification operations via the introduction of a unique detection approach known as the lightweight and efficient YOLOv4 model. In the present setting, Computational vision emerges as a very valuable and engaging manifestation of artificial intelligence (AI) that finds widespread application in many aspects of daily existence. The field of computer vision is dedicated to the development of advanced artificial intelligence and computer systems that aim to replace complex elements of the human environment. In recent times, deep neural networks have emerged as a crucial component in several sectors owing to their well-established capacity to process visual input. This study presents a methodology for classifying and identifying objects using the YOLOv4 object detection algorithm. Convolutional neural networks (CNNs) have shown exceptional efficacy in the tasks of object tracking and feature extraction from pictures. Therefore, the enhanced network architecture optimizes both the precision of identification and the speed at which it operates. This research will contribute to developing mixed-reality simulations system for object detection and tracking in collaborative environment that are accessible to everyone, including users in the architectural filed. The model was evaluated in comparison to other object detection approaches. Based on the empirical results, it was observed that the YOLOv4 model exhibited a mean average precision (mAP) of 0.988, surpassing the performance of both YOLOv3 and other object identification models

How a Diverse Research Ecosystem Has Generated New Rehabilitation Technologies: Review of NIDILRR’s Rehabilitation Engineering Research Centers

Over 50 million United States citizens (1 in 6 people in the US) have a developmental, acquired, or degenerative disability. The average US citizen can expect to live 20% of his or her life with a disability. Rehabilitation technologies play a major role in improving the quality of life for people with a disability, yet widespread and highly challenging needs remain. Within the US, a major effort aimed at the creation and evaluation of rehabilitation technology has been the Rehabilitation Engineering Research Centers (RERCs) sponsored by the National Institute on Disability, Independent Living, and Rehabilitation Research. As envisioned at their conception by a panel of the National Academy of Science in 1970, these centers were intended to take a “total approach to rehabilitation”, combining medicine, engineering, and related science, to improve the quality of life of individuals with a disability. Here, we review the scope, achievements, and ongoing projects of an unbiased sample of 19 currently active or recently terminated RERCs. Specifically, for each center, we briefly explain the needs it targets, summarize key historical advances, identify emerging innovations, and consider future directions. Our assessment from this review is that the RERC program indeed involves a multidisciplinary approach, with 36 professional fields involved, although 70% of research and development staff are in engineering fields, 23% in clinical fields, and only 7% in basic science fields; significantly, 11% of the professional staff have a disability related to their research. We observe that the RERC program has substantially diversified the scope of its work since the 1970’s, addressing more types of disabilities using more technologies, and, in particular, often now focusing on information technologies. RERC work also now often views users as integrated into an interdependent society through technologies that both people with and without disabilities co-use (such as the internet, wireless communication, and architecture). In addition, RERC research has evolved to view users as able at improving outcomes through learning, exercise, and plasticity (rather than being static), which can be optimally timed. We provide examples of rehabilitation technology innovation produced by the RERCs that illustrate this increasingly diversifying scope and evolving perspective. We conclude by discussing growth opportunities and possible future directions of the RERC program

Attention and Social Cognition in Virtual Reality:The effect of engagement mode and character eye-gaze

Technical developments in virtual humans are manifest in modern character design. Specifically, eye gaze offers a significant aspect of such design. There is need to consider the contribution of participant control of engagement. In the current study, we manipulated participants’ engagement with an interactive virtual reality narrative called Coffee without Words. Participants sat over coffee opposite a character in a virtual café, where they waited for their bus to be repaired. We manipulated character eye-contact with the participant. For half the participants in each condition, the character made no eye-contact for the duration of the story. For the other half, the character responded to participant eye-gaze by making and holding eye contact in return. To explore how participant engagement interacted with this manipulation, half the participants in each condition were instructed to appraise their experience as an artefact (i.e., drawing attention to technical features), while the other half were introduced to the fictional character, the narrative, and the setting as though they were real. This study allowed us to explore the contributions of character features (interactivity through eye-gaze) and cognition (attention/engagement) to the participants’ perception of realism, feelings of presence, time duration, and the extent to which they engaged with the character and represented their mental states (Theory of Mind). Importantly it does so using a highly controlled yet ecologically valid virtual experience

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion