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Monitoring and Measuring Sedentary Behaviour with the Aid of Human Digital Memories

Dobbins, C, Fergus, P, Merabti, M and Llewellyn-Jones, D (2012) Monitoring and Measuring Sedentary Behaviour with the Aid of Human Digital Memories. In: 2012 IEEE CONSUMER COMMUNICATIONS AND NETWORKING CONFERENCE (CCNC) . (IEEE Consumer Communications and Networking Conference (CCNC), 14 January 2012 - 17 January 2012, Las Vegas, NV).

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Abstract

There is growing global concern over the growing levels of obesity and the fact that people in general are not as active as they once were. Many believe that this is directly related to poor diet and our increasing reliance on technology, such as television, social networking, computer games, and voice activated home control systems. These kinds of activities increase sedentary behaviour across all age groups and is considered one of the main contributors to obesity and poor health. For this reason decreasing sedentary behaviour is considered a crucial theme within many research programs in health. Ironically, there is general agreement that the use of technology is likely to help researchers understand this type of behaviour. One interesting approach is based upon the use of human digital memories to provide visual lifelogs of a user’s activity and to identify the behaviour patterns of individuals. In this way visual lifelogs provide a way for user’s to evaluate their lifestyle choices. This paper discusses some of the key technologies used to achieve this and considers some of the challenges that still need to be addressed.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Science & Technology; Technology; Engineering, Electrical & Electronic; Telecommunications; Engineering; Lifelogging; Sedentary Behaviour; Digital Memory; Sensor; PHYSICAL-ACTIVITY; ADULTS; LIFE; RELIABILITY; VALIDITY; PATTERNS; STREAMS
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
Divisions: Computer Science & Mathematics
Publisher: IEEE
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Date Deposited: 01 Nov 2016 15:43
Last Modified: 13 Apr 2022 15:14
URI: https://researchonline.ljmu.ac.uk/id/eprint/2183
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