Anticipatory mobile computing for behaviour change interventions

Behavioural change interventions represent a powerful means for tackling a number of health and well-being issues, from obesity to stress and addiction. In the current medical practice, the change is induced through tailored coaching, support and information delivery. However, with the advent of smartphones, innovative ways of delivering interventions are emerging. Indeed, mobile phones, equipped with an array of sensors, and carried by their users at all times, enable therapists to both learn about the user behaviour, and impact the behaviour through the delivery of more relevant and personalised information. In this work we propose harnessing pervasive computing to not only learn from users' past behaviour, but also predict future actions and emotional states, deliver interventions proactively, evaluate their impact at run-time, and over time learn a personal intervention-effect model of a participant.