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Dashboard visualisation of lifelog data for summarisation and pattern recognition to promote behavioural change

Duane, Aaron orcid logoORCID: 0000-0002-9825-1654, Gurrin, Cathal orcid logoORCID: 0000-0003-2903-3968 and Monaghan, David orcid logoORCID: 0000-0002-5169-9902 (2016) Dashboard visualisation of lifelog data for summarisation and pattern recognition to promote behavioural change. In: Measuring Behavior 2016, 25-27 May 2016, Dublin, Ireland. ISBN 978-1-873769-59-1

Abstract
Lifelogging is a form of pervasive computing, which is capable of recording a catalogue of the totality of an individual’s experiences. Lifelogging data can take many forms from daily step counts, sleep monitoring and heart rate data to location based information to video/image diaries from cameras embedded into glasses or clothing or worn. From the perspective of behavioural change, lifelog data is an invaluable resource that can contain many potential insights into a person's patterns and experiences. One major issue with Lifelogging is the sheer volume of user generated data and analysing this wealth of data in a coherent and efficient manner can become increasingly difficult as the datasets become larger and more varied. Through utilising data visualisation techniques in a dashboard interface, or similar, one can make high-level analyses and summarisations of this data much more achievable. This visually intuitive approach to disseminating rich datasets alongside automated and algorithmic machine-learning techniques can lead to valuable user insights and the potential to significantly promote behavioural change.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Behavioral Research
Subjects:Computer Science > Computer software
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Official URL:https://www.measuringbehavior.org/mb2016/home.html
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:23052
Deposited On:04 Mar 2019 12:37 by Cathal Gurrin . Last Modified 19 May 2021 11:41
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