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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Stratton, G. Murphy, R. Rosenberg, M. Fergus, P. Attwood, A. |
| Copyright Year | 2012 |
| Description | Author affiliation: School of Sport, Health and Exercise Sciences Engineering, University of Western Australia, Australia (Rosenberg, M.) || Research Institute of Sports and Exercise Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK (Stratton, G.; Murphy, R.) || Applied Computing Research Group, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK (Fergus, P.; Attwood, A.) |
| Abstract | It is generally agreed, that an active lifestyle promotes healthy living across different age groups. It helps to combat obesity, reduce the risk of diabetes and heart disease, and support independent living as we age. However, it is difficult to quantify a direct correlation between physical activity and health outcomes. Given that obesity and lifestyle-related illnesses occur over years in contrast to days, weeks or months seeing the effects activity and sedentary behaviour has on individuals in the short term is not always possible. The ubiquitous nature of physical activity makes it extremely difficult to capture as people go about their lives. Consequently, there has been a great deal of debate on the frequency intensity time, and the type of physical activity required by different groups (pre-schoolers, children, adults, older adults, obese, infirm, disabled, and depressed). There is a need to provide effective mechanisms to monitor and manipulate physical activity and sedentary behaviour. Whilst several commercially available products exist to achieve this, compliance is poor. The challenge is to use new and novel technologies that are unobtrusive and natural adjunct to a persons day-to-day activity. This paper builds on existing ideas and explores how activity and sedentary behaviour information can be collected from different environments. We have developed an initial working prototype to evaluate the applicability of our approach. |
| Starting Page | 6111 |
| Ending Page | 6115 |
| File Size | 195217 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781457720529 |
| ISSN | 15503607 |
| e-ISBN | 9781457720536 |
| e-ISBN | 9781457720512 |
| DOI | 10.1109/ICC.2012.6364974 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-06-10 |
| Publisher Place | Canada |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Conferences Mobile computing Mobile communication Medical services Measurement Intelligent Environments Physical Activity Sedentary Behaviour Sensor Networks Monitoring |
| Content Type | Text |
| Resource Type | Article |
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