Cognality VR: Exploring a Mobile VR App with Multiple Stakeholders to Reduce Meltdowns in Autistic Children

Many autistic children can have difficulty communicating, understanding others, and interacting with new and unfamiliar environments. At times they may suffer from a meltdown. The major contributing factor to meltdowns is sensory overwhelm. Technological solutions have shown promise in improving the quality of life for autistic children-however little exists to manage meltdowns. In this work with stakeholders, we design and deploy a low cost, mobile VR application to provide relief during sensory discomfort. Through the analysis of surveys from 88 stakeholders from a variety of groups (i.e., autistic adults, children with autism, parents of autistic individuals, and medical practitioners), we identified three key features regarding ways to manage meltdowns: escape, distract, and wait it out. These insights were implementation in a system, then was then remotely deployed with 6 families. Findings and future steps are discussed

Bodily resonance: Exploring the effects of virtual embodiment on pain modulation and the fostering of empathy toward pain sufferers

Globally, around 20% of people suffer from chronic pain, an illness that cannot be cured and has been linked to numerous physical and mental conditions. According to the BioPsychoSocial model of pain, chronic pain presents patients with biological, psychological, and social challenges and difficulties. Immersive virtual reality (VR) has shown great promise in helping people manage acute and chronic pain, and facilitating empathy of vulnerable populations. Therefore, the first research trajectory of this dissertation targets chronic pain patients’ biological and psychological sufferings to provide VR analgesia, and the second research trajectory targets healthy people to build empathy and reduce patients’ social stigma. Researchers have taken the attention distraction approach to study how acute pain patients can manage their condition in VR, while the virtual embodiment approach has mostly been studied with healthy people exposed to pain stimulus. My first research trajectory aimed to understand how embodied characteristics affect users’ sense of embodiment and pain. Three studies have been carried out with healthy people under heat pain, complex regional pain syndrome patients, and phantom limb pain patients. My findings indicate that for all three studies, when users see a healthy or intact virtual body or body parts, they experience significant reductions in their self-reported pain ratings. Additionally, I found that the appearance of a virtual body has a significant impact on pain, whereas the virtual body’s motions do not. Despite the prevalence of chronic pain, public awareness of it is remarkably low, and pain patients commonly experience social stigma. Thus, having an embodied perspective of chronic pain patients is critical to understand their social stigma. Although there is a growing interest in using embodied VR to foster empathy towards gender or racial bias, few studies have focused on people with chronic pain. My second trajectory explored how researchers can foster empathy towards pain patients in embodied VR. To conclude, this dissertation uncovers the role of VR embodiment and dissects embodied characteristics in pain modulation and empathy generation. Finally, I summarized a novel conceptual design framework for embodied VR applications with design recommendations and future research directions

An Overview of Self-Adaptive Technologies Within Virtual Reality Training

This overview presents the current state-of-the-art of self-adaptive technologies within virtual reality (VR) training. Virtual reality training and assessment is increasingly used for five key areas: medical, industrial & commercial training, serious games, rehabilitation and remote training such as Massive Open Online Courses (MOOCs). Adaptation can be applied to five core technologies of VR including haptic devices, stereo graphics, adaptive content, assessment and autonomous agents. Automation of VR training can contribute to automation of actual procedures including remote and robotic assisted surgery which reduces injury and improves accuracy of the procedure. Automated haptic interaction can enable tele-presence and virtual artefact tactile interaction from either remote or simulated environments. Automation, machine learning and data driven features play an important role in providing trainee-specific individual adaptive training content. Data from trainee assessment can form an input to autonomous systems for customised training and automated difficulty levels to match individual requirements. Self-adaptive technology has been developed previously within individual technologies of VR training. One of the conclusions of this research is that while it does not exist, an enhanced portable framework is needed and it would be beneficial to combine automation of core technologies, producing a reusable automation framework for VR training

Accessibility of Health Data Representations for Older Adults: Challenges and Opportunities for Design

Health data of consumer off-the-shelf wearable devices is often conveyed to users through visual data representations and analyses. However, this is not always accessible to people with disabilities or older people due to low vision, cognitive impairments or literacy issues. Due to trade-offs between aesthetics predominance or information overload, real-time user feedback may not be conveyed easily from sensor devices through visual cues like graphs and texts. These difficulties may hinder critical data understanding. Additional auditory and tactile feedback can also provide immediate and accessible cues from these wearable devices, but it is necessary to understand existing data representation limitations initially. To avoid higher cognitive and visual overload, auditory and haptic cues can be designed to complement, replace or reinforce visual cues. In this paper, we outline the challenges in existing data representation and the necessary evidence to enhance the accessibility of health information from personal sensing devices used to monitor health parameters such as blood pressure, sleep, activity, heart rate and more. By creating innovative and inclusive user feedback, users will likely want to engage and interact with new devices and their own data