Attention-Based Applications in Extended Reality to Support Autistic Users: A Systematic Review

With the rising prevalence of autism diagnoses, it is essential for research to understand how to leverage technology to support the diverse nature of autistic traits. While traditional interventions focused on technology for medical cure and rehabilitation, recent research aims to understand how technology can accommodate each unique situation in an efficient and engaging way. Extended reality (XR) technology has been shown to be effective in improving attention in autistic users given that it is more engaging and motivating than other traditional mediums. Here, we conducted a systematic review of 59 research articles that explored the role of attention in XR interventions for autistic users. We systematically analyzed demographics, study design and findings, including autism screening and attention measurement methods. Furthermore, given methodological inconsistencies in the literature, we systematically synthesize methods and protocols including screening tools, physiological and behavioral cues of autism and XR tasks. While there is substantial evidence for the effectiveness of using XR in attention-based interventions for autism to support autistic traits, we have identified three principal research gaps that provide promising research directions to examine how autistic populations interact with XR. First, our findings highlight the disproportionate geographic locations of autism studies and underrepresentation of autistic adults, evidence of gender disparity, and presence of individuals diagnosed with co-occurring conditions across studies. Second, many studies used an assortment of standardized and novel tasks and self-report assessments with limited tested reliability. Lastly, the research lacks evidence of performance maintenance and transferability.Comment: [Accepted version] K. Wang, S. J. Julier and Y. Cho, "Attention-Based Applications in Extended Reality to Support Autistic Users: A Systematic Review," in IEEE Access, vol. 10, pp. 15574-15593, 2022, doi: 10.1109/ACCESS.2022.314772

Prerequisites for Affective Signal Processing (ASP)

Although emotions are embraced by science, their recognition has not reached a satisfying level. Through a concise overview of affect, its signals, features, and classification methods, we provide understanding for the problems encountered. Next, we identify the prerequisites for successful Affective Signal Processing: validation (e.g., mapping of constructs on signals), triangulation, a physiology-driven approach, and contributions of the signal processing community. Using these directives, a critical analysis of a real-world case is provided. This illustrates that the prerequisites can become a valuable guide for Affective Signal Processing (ASP)

Virtual Reality as a Support Tool for the Treatment of People with Intellectual and Multiple Disabilities: A Systematic Literature Review

Since the emergence of virtual reality (VR) technologies, many researchers have argued on the benefits of their use for people with intellectual and multiple disabilities. However, up to this date there is not a single study that presents a detailed overview of the state of the art in virtual reality as a support tool for the treatment of people with intellectual and multiple disabilities, as well as Autism and Down Syndrome. The aim of this study is to provide a detailed overview of the state of the art in the virtual reality area focusing on people with multiple disabilities, that encompasses intellectual and physical disabilities. There is still no consensus on the effectiveness of VR-based treatments. Virtual reality can offer rich environment and features, but most of the researches focuses only in the experience to be inside a virtual place without taking advantage of what benefits VR provide us. Furthermore, most of our selected studies used non-immersive VR and AR. Thus, immersive VR is an open field with many opportunities to be explored. We believe VR has great potential to be effective in the treatment of people with intellectual and multiple disabilities

Bridging the gap between emotion and joint action

Our daily human life is filled with a myriad of joint action moments, be it children playing, adults working together (i.e., team sports), or strangers navigating through a crowd. Joint action brings individuals (and embodiment of their emotions) together, in space and in time. Yet little is known about how individual emotions propagate through embodied presence in a group, and how joint action changes individual emotion. In fact, the multi-agent component is largely missing from neuroscience-based approaches to emotion, and reversely joint action research has not found a way yet to include emotion as one of the key parameters to model socio-motor interaction. In this review, we first identify the gap and then stockpile evidence showing strong entanglement between emotion and acting together from various branches of sciences. We propose an integrative approach to bridge the gap, highlight five research avenues to do so in behavioral neuroscience and digital sciences, and address some of the key challenges in the area faced by modern societies

Cognitive State Measurement from Eye Gaze Analysis in an Intelligent Virtual Reality Driving System for Autism Intervention

Abstract-Autism Spectrum Disorder (ASD) is a group of neurodevelopmental disabilities with a high prevalence rate. While much research has focused on improving social communication deficits in ASD populations, less emphasis has been devoted to improving skills relevant for adult independent living, such as driving. In this paper, a novel virtual reality (VR)-based driving system with different difficulty levels of tasks is presented to train and improve driving skills of teenagers with ASD. The goal of this paper is to measure the cognitive load experienced by an individual with ASD while he is driving in the VR-based driving system. Several eye gaze features are identified that varied with cognitive load in an experiment participated by 12 teenagers with ASD. Several machine learning methods were compared and the ability of these methods to accurately measure cognitive load was validated with respect to the subjective rating of a therapist. Results will be used to build models in an intelligent VR-based driving system that can sense a participant's real-time cognitive load and offer driving tasks at an appropriate difficulty level in order to maximize the participant's long-term performance

Emerging issues and current trends in assistive technology use 2007-1010: practising, assisting and enabling learning for all

Following an earlier review in 2007, a further review of the academic literature relating to the uses of assistive technology (AT) by children and young people was completed, covering the period 2007-2011. As in the earlier review, a tripartite taxonomy: technology uses to train or practise, technology uses to assist learning and technology uses to enable learning, was used in order to structure the findings. The key markers for research in this field and during these three years were user involvement, AT on mobile mainstream devices, the visibility of AT, technology for interaction and collaboration, new and developing interfaces and inclusive design principles. The paper concludes by locating these developments within the broader framework of the Digital Divide

Addressing Vehicle Safety for Children with Additional Emotional and Behavioral Needs

Purpose: More than 148,000 children were injured in motor vehicle crashes in 2011 (Center for Disease Control and Prevention, 2014). Currently, while it is understood that transporting children with special needs likely to affect behaviors (SNLAB) provide safety challenges (Yonkman, Lawler, Talty, O’Neil, & Bull, 2013), there is little information regarding how to evaluate and intervene for this significant aspect of daily life. The purpose of this project was to develop an occupational therapy protocol for evaluation and intervention for car safety to be used by occupational therapists working with children who have emotional and behavioral needs. Methodology: An extensive literature review was conducted in order to better understand the targeted population and supports and barriers to providing transportation safety services to this population. Utilizing the Person Environment Occupation Model (PEO) (Law et al., 1996), a systematic analysis of occupational performance issues for riding safely in a car was conducted and was the basis for creating the evaluation and intervention tools to be used by occupational therapists. Results: The Traveling Safely Evaluation and Intervention Protocol was developed to address the issue of vehicle transportation safety for children with SNLAB. This protocol includes an assessment for evaluation and resources to be utilized by the occupational therapist and parent when planning for car safety. Conclusion: This protocol development is only a first step in addressing car safety for children with SNLAB. It is recommended this protocol be piloted and further refined. In addition, there is need for development of resources to assist in problem solving solutions for car safety for children

Affective Computing

This book provides an overview of state of the art research in Affective Computing. It presents new ideas, original results and practical experiences in this increasingly important research field. The book consists of 23 chapters categorized into four sections. Since one of the most important means of human communication is facial expression, the first section of this book (Chapters 1 to 7) presents a research on synthesis and recognition of facial expressions. Given that we not only use the face but also body movements to express ourselves, in the second section (Chapters 8 to 11) we present a research on perception and generation of emotional expressions by using full-body motions. The third section of the book (Chapters 12 to 16) presents computational models on emotion, as well as findings from neuroscience research. In the last section of the book (Chapters 17 to 22) we present applications related to affective computing

Automatic emotion recognition in clinical scenario: a systematic review of methods

none4Automatic emotion recognition has powerful opportunities in the clinical field, but several critical aspects are still open, such as heterogeneity of methodologies or technologies tested mainly on healthy people. This systematic review aims to survey automatic emotion recognition systems applied in real clinical contexts, to deeply analyse clinical and technical aspects, how they were addressed, and relationships among them. The literature review was conducted on: IEEEXplore, ScienceDirect, Scopus, PubMed, ACM. Inclusion criteria were the presence of an automatic emotion recognition algorithm and the enrollment of at least 2 patients in the experimental protocol. The review process followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Moreover, the works were analysed according to a reference model to deeply examine both clinical and technical topics. 52 scientific papers passed inclusion criteria. Most clinical scenarios involved neurodevelopmental, neurological and psychiatric disorders with the aims of diagnosing, monitoring, or treating emotional symptoms. The most adopted signals are video and audio, while supervised shallow learning is mostly used for emotion recognition. A poor study design, tiny samples, and the absence of a control group emerged as methodological weaknesses. Heterogeneity of performance metrics, datasets and algorithms challenges results comparability, robustness, reliability and reproducibility.openPepa, Lucia; Spalazzi, Luca; Capecci, Marianna; Ceravolo, Maria GabriellaPepa, Lucia; Spalazzi, Luca; Capecci, Marianna; Ceravolo, Maria Gabriell