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In the UK, more than 70% of mobile users now own a smartphone. These increasingly powerful, sensor-rich, and personal devices present an immense opportunity to monitor health-related behaviours and deliver digital behaviour-change interventions at unprecedented scale.

In this talk, I will briefly discuss how computer scientists have been using smartphone sensors to monitor and make inferences about users’ behaviours. I will then present the apps that we have built in this domain, including Emotion Sense (with colleagues in the Dept. of Psychology), an app that tracks users’ mood and sensor data, and Q Sense (with colleagues in the Behavioural Science Group), an app that delivers a context-aware smoking cessation intervention. Emotion Sense has, to date, been downloaded over 35,000 times – providing us with a unique data set of diurnal behaviours and moods.

Finally, designing and building smartphone systems in multi-disciplinary research settings presents a number of challenges to all parties, ranging from understanding smartphone sensor data to understanding each other. I’ll close by discussing some of these experiences to date, and how we have tackled them.

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