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Content Provider | IEEE Xplore Digital Library |
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Author | Bamidis, P.D. |
Copyright Year | 2015 |
Description | Author affiliation: Med. Sch., Aristotle Univ. of Thessaloniki, Thessaloniki, Greece (Bamidis, P.D.) |
Abstract | Ageing is a major global demographic trend, which seems to be intensified. The earlier detection of risks associated with ageing, can enable earlier intervention to ameliorate their negative consequences. Many of these recent efforts are associated with the use of Information and Communication Technologies (ICTs) and the stemming from them innovations in the fight against this age related decline and frailty. Ubiquitous unobtrusive monitoring and training (recently much blended by means of exergames) has become reality due to the availability of new mobile sensors and devices and the emergence of new technologies and services. The current piece of work presents the different milestones we have achieved as best practices during the past seven years of piloting training and exergaming ICT components in an effort to support Active and Healthy Aging. Our impact verification and results validation methodologies are revisited here in an effort to outline best practices and build up neuroscientific evidence. Finally, this paper demonstrates how the construction of an Active and Healthy Aging Living Lab was materialised in an attempt to gauge evidence based research in the field of active and health aging. |
Starting Page | 7756 |
Ending Page | 7759 |
File Size | 721893 |
Page Count | 4 |
File Format | |
ISSN | 1557170X |
e-ISBN | 9781424492718 |
DOI | 10.1109/EMBC.2015.7320190 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2015-08-25 |
Publisher Place | Italy |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Aging Training Senior citizens Best practices Sensors Technological innovation Sociology |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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