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Utilising contextual memory retrieval cues and the ubiquity of the cell phone to review lifelogged physiological activities

Doherty, Aiden R. orcid logoORCID: 0000-0003-4395-7702, Tolle, Kristin M. and Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 (2009) Utilising contextual memory retrieval cues and the ubiquity of the cell phone to review lifelogged physiological activities. In: IMCE 2009 - International Workshop on Interactive Multimedia for Consumer Electronics, 23 Oct 2009, Beijing, China.

In today's healthcare world where we react to conditions that have already developed, lifelogging technologies may offer a glimpse into a future world of proactive healthcare where symptoms of conditions are detected at much earlier stages. At the end of last year it was estimated that there were 4 billion cell phones in the world, in comparison to just over 1 billon PCs. In this paper we discuss a framework, which leverages the ubiquity of the cell phone, to aggregate data from multiple wearable biological sensors. This physiological lifelogged data can then be queried via an interface which utilises contextual memory retrieval cues to assist people remember what type of activity they were doing at a particular time. This may be helpful in the diagnosis of potential medical conditions or encourage wellness behaviours.
Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Uncontrolled Keywords:cell phone ubiquity; lifelogging; physiological user interfaces; sensor data aggregation;
Subjects:Computer Science > Lifelog
Computer Science > Information technology
Computer Science > Multimedia systems
DCU Faculties and Centres:Research Institutes and Centres > Centre for Digital Video Processing (CDVP)
Research Institutes and Centres > CLARITY: The Centre for Sensor Web Technologies
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Published in: IMCE '09: Proceedings of the 1st International workshop on Interactive multimedia for consumer electronics. . Association for Computing Machinery.
Publisher:Association for Computing Machinery
Official URL:https://dx.doi.org/10.1145/1631040.1631044
Copyright Information:© 2009 ACM
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland, Microsoft Research
ID Code:4723
Deposited On:31 Jul 2009 10:23 by Dr Aiden Doherty . Last Modified 05 Jan 2022 13:46

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