Why study movement variability in autism?

Autism has been defined as a disorder of social cognition, interaction and communication where ritualistic, repetitive behaviors are commonly observed. But how should we understand the behavioral and cognitive differences that have been the main focus of so much autism research? Can high-level cognitive processes and behaviors be identified as the core issues people with autism face, or do these characteristics perhaps often rather reflect individual attempts to cope with underlying physiological issues? Much research presented in this volume will point to the latter possibility, i.e. that people on the autism spectrum cope with issues at much lower physiological levels pertaining not only to Central Nervous Systems (CNS) function, but also to peripheral and autonomic systems (PNS, ANS) (Torres, Brincker, et al. 2013). The question that we pursue in this chapter is what might be fruitful ways of gaining objective measures of the large-scale systemic and heterogeneous effects of early atypical neurodevelopment; how to track their evolution over time and how to identify critical changes along the continuum of human development and aging. We suggest that the study of movement variability—very broadly conceived as including all minute fluctuations in bodily rhythms and their rates of change over time (coined micro-movements (Figure 1A-B) (Torres, Brincker, et al. 2013))—offers a uniquely valuable and entirely objectively quantifiable lens to better assess, understand and track not only autism but cognitive development and degeneration in general. This chapter presents the rationale firstly behind this focus on micro-movements and secondly behind the choice of specific kinds of data collection and statistical metrics as tools of analysis (Figure 1C). In brief the proposal is that the micro-movements (defined in Part I – Chapter 1), obtained using various time scales applied to different physiological data-types (Figure 1), contain information about layered influences and temporal adaptations, transformations and integrations across anatomically semi-independent subsystems that crosstalk and interact. Further, the notion of sensorimotor re-afference is used to highlight the fact that these layered micro-motions are sensed and that this sensory feedback plays a crucial role in the generation and control of movements in the first place. In other words, the measurements of various motoric and rhythmic variations provide an access point not only to the “motor systems”, but also access to much broader central and peripheral sensorimotor and regulatory systems. Lastly, we posit that this new lens can also be used to capture influences from systems of multiple entry points or collaborative control and regulation, such as those that emerge during dyadic social interactions

Icanlearn: A Mobile Application For Creating Flashcards And Social Stories\u3csup\u3etm\u3c/sup\u3e For Children With Autistm

The number of children being diagnosed with Autism Spectrum Disorder (ASD) is on the rise, presenting new challenges for their parents and teachers to overcome. At the same time, mobile computing has been seeping its way into every aspect of our lives in the form of smartphones and tablet computers. It seems only natural to harness the unique medium these devices provide and use it in treatment and intervention for children with autism. This thesis discusses and evaluates iCanLearn, an iOS flashcard app with enough versatility to construct Social StoriesTM. iCanLearn provides an engaging, individualized learning experience to children with autism on a single device, but the most powerful way to use iCanLearn is by connecting two or more devices together in a teacher-learner relationship. The evaluation results are presented at the end of the thesis

The Return of a Voice: Implementing Smart Technology to Provide an Outlet that Aids in Communication for Non-Verbal Children with Autism

The Current state of communication based software designed to aid those with non-verbal autism is extremely limited or overly complex. The purpose of this research is to look into the world of communication based software aids that provide accessibility options for those with non-verbal autism. This paper looks to assess what is currently availability draw conclusions regarding gaps within the research and technology in order to derive a solution in the form of a mobile phone application that can serve to fill in the aforementioned gaps. The major focus of this study is to pinpoint exactly what elements of design work best regarding UI, UX, and aesthetics along with which elements do not. The goal is to then synthesize and amalgamate these elements into a visual solution that can serve the designated demographic in the best way possible. This thesis study looks at several different cases regarding accessibility based technology and draws many of its conclusions from the success rate of these projects in order to find what is believed to be the best solution in the form of a multi-platform mobile phone application that is both easy to use and widely distributed

Personalization of Affective Models to Enable Neuropsychiatric Digital Precision Health Interventions: A Feasibility Study

Mobile digital therapeutics for autism spectrum disorder (ASD) often target emotion recognition and evocation, which is a challenge for children with ASD. While such mobile applications often use computer vision machine learning (ML) models to guide the adaptive nature of the digital intervention, a single model is usually deployed and applied to all children. Here, we explore the potential of model personalization, or training a single emotion recognition model per person, to improve the performance of these underlying emotion recognition models used to guide digital health therapies for children with ASD. We conducted experiments on the Emognition dataset, a video dataset of human subjects evoking a series of emotions. For a subset of 10 individuals in the dataset with a sufficient representation of at least two ground truth emotion labels, we trained a personalized version of three classical ML models on a set of 51 features extracted from each video frame. We measured the importance of each facial feature for all personalized models and observed differing ranked lists of top features across subjects, motivating the need for model personalization. We then compared the personalized models against a generalized model trained using data from all 10 participants. The mean F1-scores achieved by the personalized models were 90.48%, 92.66%, and 86.40%, respectively. By contrast, the mean F1-scores reached by non-personalized models trained on different human subjects and evaluated using the same test set were 88.55%, 91.78%, and 80.42%, respectively. The personalized models outperformed the generalized models for 7 out of 10 participants. PCA analyses on the remaining 3 participants revealed relatively facial configuration differences between emotion labels within each subject, suggesting that personalized ML will fail when the variation among data points within a subjects data is too low

Student proposals for design projects to aid children with severe disabilities

Citation: Warren, S. (2016). Student proposals for design projects to aid children with severe disabilities.Children with severe disabilities have unique individual needs. Technology-based designs intended to quantify the well-being of these children or assist them with learning or activities of daily living are often by nature "one of" designs tightly matched to these needs. For children with severe autism, such designs must be incorporated into their environments in unobtrusive ways to avoid upsetting or distracting these children. This design space and its affiliated challenges offer a rich environment for engineering students to exercise their design creativity. This paper presents an end-of-semester exercise for a Kansas State University Introduction to Biomedical Engineering class, where students propose senior-design projects geared toward children with severe disabilities. The goal of the exercise is to integrate concepts related to biomedical devices, design factors, care delivery environments, and assistive technology into a proposed design with clear practical benefit that can be implemented in prototype form by a senior design team over the span of about two semesters. The deliverable for the design exercise is a four-page paper in two-column IEEE format that adheres to a pre-specified structure. To focus these design-project ideas, students are asked to offer their thoughts within the framework of needs specified by clinical staff at Heartspring in Wichita, KS, a facility that serves severely disabled children, where nearly all of the full-time residents are autistic, and most are nonverbal. In addition to the educational benefits offered by this experience, the author's intent is to help spur ideas for new senior design projects that can be supported with resources from existing NSF-funded grants which provide equipment and materials for such endeavors. Six semesters worth of design ideas are presented here, along with the results of assessment rubrics applied to the final papers. The class is populated by students from various departments within the Kansas State University College of Engineering, so design proposals are varied and incorporate low-level to system-level solutions. Some of these design ideas have been adopted by design teams, whereas others await attention. © American Society for Engineering Education, 2016

A Spectrum of Tech: An Integrated Literature Review of Technologies to Target Social Skills in Students with Autism Spectrum Disorders

Students with autism spectrum disorders (ASD) often have limited social or communication skills and, thus, need extra assistance in learning when and how to engage in appropriate interactions with those around them. However, because there are several different individual skills (e.g., joint attention, emotional expression, etc.) that fall under the categories of social and communication skills, and there are even more options of devices and programs to choose from within assistive technology (AT) and instructional technology (IT), it may seem daunting to find the right technology to meet a specific child’s needs and to determine whether that technology procedures lasting results. The purpose of this integrated literature review was to investigate whether devices used for social skills intervention in PreK-12 students with ASD function as either AT or IT, with the secondary goal of determining which technologies promote better maintenance and generalization than others in social skills interventions in PreK-12 students with ASD. Analysis of published research studies on Virtual Reality, Augmented Reality, Games, Video Modeling, Social Robots, and Wearable Assistive Technologies demonstrate that many of these technologies function as either AT or IT, depending on the context of the situation. Furthermore, it was found that certain devices, specifically Video Modeling and Social Robots, promote better maintenance and generalization