Abstract
As real-life activity data from many aging individuals become available, insights gleaned from such data could be leveraged to foster healthy aging. The emerging field of semantic activity analytics is addressing this challenge.
Martin, Mike; Weibel, Robert; Röcke, Christina; Boker, Steven M (2018). Semantic Activity Analytics for Healthy Aging: Challenges and Opportunities. IEEE Pervasive Computing, 17(3):73-77.
Abstract
As real-life activity data from many aging individuals become available, insights gleaned from such data could be leveraged to foster healthy aging. The emerging field of semantic activity analytics is addressing this challenge.
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| Item Type: | Journal Article, not_refereed, original work |
|---|---|
| Communities & Collections: | 06 Faculty of Arts > Institute of Psychology
07 Faculty of Science > Institute of Geography 08 Research Priority Programs > Dynamics of Healthy Aging |
| Dewey Decimal Classification: | 150 Psychology |
| Scopus Subject Areas: | Physical Sciences > Software
Physical Sciences > Computer Science Applications Physical Sciences > Computational Theory and Mathematics |
| Uncontrolled Keywords: | Computational Theory and Mathematics, Software, Computer Science Applications |
| Language: | English |
| Date: | 1 July 2018 |
| Deposited On: | 17 Dec 2018 14:53 |
| Last Modified: | 20 Sep 2023 01:46 |
| Publisher: | Institute of Electrical and Electronics Engineers |
| ISSN: | 1536-1268 |
| OA Status: | Closed |
| Publisher DOI: | https://doi.org/10.1109/mprv.2018.03367738 |
Martin, Mike