Nudge Better Quantified-Self with Context-Aware and Proactive Services

Guo, Li orcid iconORCID: 0000-0003-1272-8480 (2015) Nudge Better Quantified-Self with Context-Aware and Proactive Services. In: 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing. Institute of Electrical and Electronics Engineers (IEEE), pp. 1527-1532. ISBN 978-1-5090-0154-5

[thumbnail of Author Accepted Manuscript]
PDF (Author Accepted Manuscript) - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.


Official URL:


Abstract—The concept of quantified-self has drawn great attention along with fast developments of smartphones and wearable sensor technologies. Much work has been focused on life data collection and visualization to help with better self-understanding. However, we argue that although (self-awareness/knowledge discovery is an important aspect of quantified-self, knowledge maintenance is more, or at least equally, important. In this paper, we propose a proactive approach that uses the knowledge mined from people’s activity data to nudge them towards a good lifestyle. The trial study is focused on good sleep maintenance. We first use smartphone as an activity detector to collect various features in a non-intrusive manner. We then use those data to learn various activity patterns, including bedding time, wakeup time and sleep duration. Finally, we analyse correlations that may lead to sufficient or insufficient sleeps and provide customised advices through using proactive services at the right time in order to give them better chances to be turned into actions

Repository Staff Only: item control page