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I like to log: a questionnaire study towards accessible lifelogging for older users

Caprani, Niamh, Gurrin, Cathal orcid logoORCID: 0000-0003-2903-3968 and O'Connor, Noel E. orcid logoORCID: 0000-0002-4033-9135 (2010) I like to log: a questionnaire study towards accessible lifelogging for older users. In: Assets 2010 - 12th International ACM SIGACCESS Conference on Computers and Accessibility, 25-27 October, 2010, Orlando, FL, USA. ISBN 978-1-60558-881-0

Abstract
Lifelogging is the capture and storage of everyday experiences and the act of reviewing lifelog data can significantly support episodic memory, which is particularly vulnerable to the effects of ageing. To design an accessible lifelogging application for older users we firstly need to explore what lifelogging features the application should include. We carried out a questionnaire study to investigate what lifelogging items people from different age groups are currently collecting. Also of interest to us was what items the participants would like to collect and the differences in lifelogging choices between age groups. The results from this questionnaire will contribute to the design of a lifelogging application which focuses on older users' preferences, motivations and abilities.
Metadata
Item Type:Conference or Workshop Item (Poster)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:older adults;
Subjects:Computer Science > Lifelog
DCU Faculties and Centres:Research Institutes and Centres > CLARITY: The Centre for Sensor Web Technologies
Published in: Proceedings of the 12th international ACM SIGACCESS conference on Computers and accessibility. . Association for Computing Machinery. ISBN 978-1-60558-881-0
Publisher:Association for Computing Machinery
Official URL:http://dx.doi.org/10.1145/1878803.1878862
Copyright Information:©2010 Association for Computing Machinery
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Irish Research Council for Science Engineering and Technology, Science Foundation Ireland, Microsoft Research
ID Code:15781
Deposited On:25 Nov 2010 13:38 by Niamh Caprani . Last Modified 15 Dec 2021 16:51
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