Pain-related emotions are a major barrier to effective self rehabilitation in chronic pain. Automated coaching systems capable of detecting these emotions are a potential solution. This paper lays the foundation for the development of such systems by making three contributions. First, through literature reviews, an overview of how pain is expressed in chronic pain and the motivation for detecting it in physical rehabilitation is provided. Second, a fully labelled multimodal dataset (named ‘EmoPain’) containing high resolution multiple-view face videos, head mounted and room audio signals, full body 3D motion capture and electromyographic signals from back muscles is supplied. Natural unconstrained pain related facial expressions and body movement behaviours were elicited from people with chronic pain carrying out physical exercises. Both instructed and non-instructed exercises were considered to reflect traditional scenarios of physiotherapist directed therapy and home-based self-directed therapy. Two sets of labels were assigned: level of pain from facial expressions annotated by eight raters and the occurrence of six pain-related body behaviours segmented by four experts. Third, through exploratory experiments grounded in the data, the factors and challenges in the automated recognition of such expressions and behaviour are described, the paper concludes by discussing potential avenues in the context of these findings also highlighting differences for the two exercise scenarios addressed.

Mobile applications (apps) are software developed for use on mobile devices and made available through app stores. App stores are highly competitive markets where developers need to cater to a large number of users spanning multiple countries. This work hypothesizes that there exist country differences in mobile app user behavior and conducts one of the largest surveys to date of app users across the world, in order to identify the precise nature of those differences. The survey investigated user adoption of the app store concept, app needs, and rationale for selecting or abandoning an app. We collected data from more than 15 countries,

Physical activity is important for improving quality of life in people with chronic pain. However, actual or anticipated pain exacerbation, and lack of confidence when doing physical activity, make it difficult to maintain and build towards long-term activity goals. Research guiding the design of interactive technology to motivate and support physical activity in people with chronic pain is lacking. We conducted studies with: (1) people with chronic pain, to understand how they maintained and increased physical activity in daily life and what factors deterred them; and (2) pain-specialist physiotherapists, to understand how they supported people with chronic pain. Building on this understanding, we investigated the use of auditory feedback to address some of the psychological barriers and needs identified and to increase self-efficacy, motivation and confidence in physical activity. We conclude by discussing further design opportunities based on the overall findings.

Background: At present there are no measures to identify the cognitive processes and behaviours that might mediate the outcome of treatment in people with Body Dysmorphic Disorder (BDD). Aims: To develop and validate a process measure that can be used to assess the progress of patients throughout therapy and in research for BDD. Method: The psychometric properties of the Appearance Anxiety Inventory (AAI) was explored in a clinical group of participants diagnosed with BDD (Study 1) and in a non-clinical community group with high appearance concerns (Study 2). Item characteristics, reliability, and factor structure were analysed. Convergent validity with measures of related symptoms was assessed. Results: The AAI was found to have good test-retest reliability and convergent validity in the measurement of appearance anxiety. It was also sensitive to change during treatment. The scale was found to have a two-factor structure in the clinical group, with one factor characterised by avoidance, and a second factor comprised of threat monitoring.However, in the community sample it appeared to have a one-factor structure. Conclusion:The results suggest that the AAI has the psychometric properties to determine if changes in cognitive processes and behaviours can mediate the outcome following treatment in patients with BDD. This supports its potential usefulness in clinical and research settings.