Although there is no register of people with autism in the UK, the National Autistic Society estimates that 700,000 people in the UK are on the autistic spectrum. Beyond this, however, almost all of us suffer from anxiety - in some form - during our lifetime. According to Anxiety UK, 1 in 6 people experience some form of 'neurotic health problem', of which the most common are anxiety and depression. Anxiety UK estimates that more than 1 in 10 people are likely to have a 'disabling anxiety disorder' at some stage in their life (http://www.anxietyuk.org.uk/about-anxiety/frequently-asked-questions/). And these figures do not include the many and varied minor forms of anxiety that all of us experience on a regular basis. The aim of this project is to co-design and co-produce, with a cohort of autism sufferers, their friends and family, a tactile digital anxiety management and peer-support tool to assist people with autism in understanding and managing their anxiety in social engagement. The prototype Clasp system will be developed to have three core design components: 1) a tactile digital anxiety object which communicates levels of anxiety to a connected smartphone, implemented using a squeezable Bluetooth-connected digital 'stress ball'; 2) a peer-support network communication facility via SMS and distributed Social Network Service (SNS) status updates; 3) an anxiety data aggregator and visualization for personal and community feedback. If use of the 'stress ball' reaches user-defined thresholds, a user-defined response will be triggered. The user can view their trigger history, which will show times and locations when triggers were reached. Hence, Clasp will allow those with autism to track their anxiety levels over time, to reflect on what made them anxious in different situations, to experiment with interventions that alleviate their anxiety, and to get support from their peers in situations of high anxiety. The specific features of Clasp will come about through an in-depth engagement with a wide variety of stakeholders, including those with autism. Clasp will be underpinned by a study into how anxiety in autistic adults is impacted by and impacts their social engagement and the role digital technology may play in managing anxiety. Clasp will evolve through a process that iteratively and collaboratively captures the requirements for an anxiety management and peer-support system, builds a prototype for such a system, and evaluates key design implications for future development of Clasp and similar digital tools. We will also investigate versions of Clasp targeted to non-autistic users, thus addressing anxiety issues in a broader range of users including those with mental/learning disabilities as well as people more generally.

Autism Spectrum Disorder (ASD) affects 695,000 people in the UK, and about 547,000 of these are 18 or over (1.3% of the adults in working age). The unemployment rate among adults with an ASD is higher than 85%, nearly double the unemployment rate of 48% for the wider disabled population. One reason for this is that people with an ASD struggle to interpret social signals, those expressive behavioural cues through which people manifest what they feel or think (facial expressions, vocalisations, gestures, etc.). This project will develop a Socially-Competent Robot Training Buddy that will help adults with ASD to better deal with social signals in work-related scenarios. The project is inherently interdisciplinary and falls in the new research area of Socially Assistive Robotics, at the crossroads between robotics, psychology, and social signal processing. So far, autonomous robots have largely been seen as functionally engineered to carrying out well-defined tasks in an efficient manner. However Socially Assistive Robots (SARs) must fit into normal human social environments and follow interaction rules that do not disrupt an office or a home or upset their human interaction partners. This project will focus on high-functioning adults with an ASD, and just as physically assistive robots enable people to make movements that are difficult because of physical impairments, the SAR of this project enables people with an ASD to perform social tasks that are difficult - if not impossible - due to social cognition impairments. The main goal is to reduce the cost of Behavioural Skills Training (BST) through the development of a Robot Training Buddy. BST is recognized as one of the most effective approaches to alleviate ASD effects, but cannot be applied extensively because it is labour intensive. Using an autonomous robot would reduce the human effort and cost of BST and make it more widely available. The main technological challenge is the development of a novel affective architecture that makes a robot suitable for behaviour rehearsal, a critical stage of BST. In behaviour rehearsal, the robot must reinforce the use of appropriate social signals by its human interaction partner while inhibiting the use of inappropriate ones. The team will work with stakeholders involved with training for adults with an ASD to develop workplace-relevant scenarios in which to develop and evaluate the Training Buddy with end-users. This work will develop the necessary scientific basis for the introduction of socially-competent robots into human social environments, opening the way to a multitude of domestic, educational and assistive applications.