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Conference Paper: Mobile technologies and physical activity behaviour: an example of what you can do with your accelerometry and GPS data

TitleMobile technologies and physical activity behaviour: an example of what you can do with your accelerometry and GPS data
Authors
Issue Date2013
PublisherGhent University.
Citation
The 12th Annual meeting of the International Society for Behavioral Nutrition and Physical Activity (ISBNPA 2013), Ghent, Belgium, 22-25 May 2013. In Abstracts Book, 2013, p. 110-111, abstract S25.3 How to Cite?
AbstractPURPOSE: The ability of mobile technologies to continuously collect a large amount of objective data on physical activity (PA) and their correlates can assist the identification of potential determinants of PA behaviour. However, modeling such data, with multiple sources of dependency, can be challenging. METHOD: Objective data on PA and locations were collected on a sample of 95preschoolers using accelerometers and Global Positioning System (GPS) mon…
DescriptionConference Theme: Promoting Healthy Eating and Activity Worldwide
Session - S25 Always in touch: physical activity promotion via social media and modern technology: abstract S25.3
Persistent Identifierhttp://hdl.handle.net/10722/188043

 

DC FieldValueLanguage
dc.contributor.authorCerin, Een_US
dc.date.accessioned2013-08-21T07:26:48Z-
dc.date.available2013-08-21T07:26:48Z-
dc.date.issued2013en_US
dc.identifier.citationThe 12th Annual meeting of the International Society for Behavioral Nutrition and Physical Activity (ISBNPA 2013), Ghent, Belgium, 22-25 May 2013. In Abstracts Book, 2013, p. 110-111, abstract S25.3en_US
dc.identifier.urihttp://hdl.handle.net/10722/188043-
dc.descriptionConference Theme: Promoting Healthy Eating and Activity Worldwide-
dc.descriptionSession - S25 Always in touch: physical activity promotion via social media and modern technology: abstract S25.3-
dc.description.abstractPURPOSE: The ability of mobile technologies to continuously collect a large amount of objective data on physical activity (PA) and their correlates can assist the identification of potential determinants of PA behaviour. However, modeling such data, with multiple sources of dependency, can be challenging. METHOD: Objective data on PA and locations were collected on a sample of 95preschoolers using accelerometers and Global Positioning System (GPS) mon…-
dc.languageengen_US
dc.publisherGhent University.-
dc.relation.ispartofAnnual Meeting of the International Society for Behavioral Nutrition & Physical Activity, ISBNPA 2013en_US
dc.titleMobile technologies and physical activity behaviour: an example of what you can do with your accelerometry and GPS dataen_US
dc.typeConference_Paperen_US
dc.identifier.emailCerin, E: ecerin@hku.hken_US
dc.identifier.authorityCerin, E=rp00890en_US
dc.description.naturepostprint-
dc.identifier.hkuros218480en_US
dc.identifier.spage110, abstract S25.3-
dc.identifier.epage111-
dc.publisher.placeBelgium-

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