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\u201cTechnology in Support of Healthy Habits\u201d<\/h3>\n
The conference\u2019s opening key note speech was held by Microsoft\u2019s Mary Czerwinsky, a principal researcher and research manager, who spoke about affective computing, wearable-free sensing, conversational UIs, and the importance of attractiveness vs. reliability of chatbots. Already today, enough usage data is being captured for companies being able to draw conclusions about their users\u2019 state of minds and emotions \u2013 by systematically evaluating text semantics, tone of voice, facial expressions, or even the way you type. According to Czerwinsky, the goal is to create digital agents that you want to use, because they know you and thus are able to help you. It\u2019s not about a chatbot pretending to be human, but a digital agent reacting in a human way.<\/p>\n
She continued to present a couple of case studies; starting with ParentGuardian<\/em><\/a><\/span>, which provides parents small hints on how to behave in specific situations with ADHD children, while measuring the parents\u2019 stress-factor using smart bracelets.\u00a0Another example was Chewie<\/em><\/a><\/span>; an app which predicts about-to-eat moments for just in time eating intervention. By combining the ability to identify behavioural patterns with the development of trustworthy, reliable, and attractive conversational user interfaces, even agent-based psychological interventions can and will be created.<\/p>\n One of the personally relevant tracks for me I found on Wednesday \u2013 within Social Computing and Social Media<\/em> I discovered a couple of sessions specifically focusing on activity trackers in the everyday life \u2013 seen from a rather scientific perspective.\u00a0It started with a comparison of different fitness tracking reward programs<\/a><\/span><\/em> in Germany and Australia, giving an outlook about how health insurances might motivate us in sharing even more data with them.\u00a0Another presentation shared insights on data privacy of fitness trackers<\/em><\/a><\/span>, whereas the third presenter talked about the relationship between people\u2019s activity levels and their network sizes<\/em><\/a><\/span>: the more followers you have the more likely you are to repeat exercising.\u00a0The last of this track\u2019s presentation discussed reasons why users join fitness communities<\/em><\/a><\/span> on Facebook.<\/p>\n The main reason, though, for my trip to HCII Las Vegas was presenting EUREKA, based on a paper my colleague Panos and I submitted a couple months back. EUREKA stands for “Engineering Usability Research Empirical Knowledge and Artifacts” and summarises a\u00a0methodology and tool that facilitates a structured yet flexible iterative process to qualitative data analysis. Based on the fact that\u00a0collecting, analysing, sorting, and making sense of the data collected during a usability test study is a time-consuming task that requires a lot of effort, we studied on one hand a methodological perspective to usability tests data analysis and on the other hand created a tool that could provide the features and functionalities to realise this method, in various situations, scenarios and projects. Currently, EUREKA is available as a functional Excel prototype, consisting of five distinctive modules, allowing users to step-by-step analysing their qualitative and quantitative test data, prioritising findings, finding, evaluating and tracking their solutions.<\/p>\nFitness, Health and Wearables<\/h3>\n
Presenting EUREKA<\/h3>\n