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dc.contributor.authorPratiwi, Puspa S
dc.contributor.authorTjondronegoro, Dian W
dc.contributor.authorXu, Yue
dc.contributor.authorLi, Yuefeng
dc.contributor.authorTrost, Stewart
dc.contributor.authorClanchy, Kelly
dc.date.accessioned2019-06-14T01:30:56Z
dc.date.available2019-06-14T01:30:56Z
dc.date.issued2018
dc.identifier.isbn9781538663295
dc.identifier.doi10.1109/ICoIAS.2018.8494163
dc.identifier.urihttp://hdl.handle.net/10072/382855
dc.description.abstractExisting activity coaching systems and applications already can offer adaptive feedback on behaviors which are usually represented by using visualization and historical data summaries. This paper proposes a new framework that leveraged ubiquitous, open source cloud-based platform, and risk-factors monitoring escalated by intelligent rule-based reasoning approach. We present a new framework for promoting proactive lifestyle to promote physical activity using the acquisition of multiple lifestyle sensor data. Our proposed architecture framework utilizes the combination of multi lifestyle behavior relationship variables (manual & sensor-based) to reliably generate personalized coaching in the form of coaching process, particularly for the promotion of physical activity. For ensuring to provide personalized coaching, our system architecture framework includes automatic intelligent mechanisms to process user-centered data and extract interpretable information by including the direct interaction capabilities between users and the e-coaching, as well as the knowledge provided by healthcare specialists.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherIEEE
dc.relation.ispartofconferencenameInternational Conference on Intelligent Autonomous Systems (ICoIAS)
dc.relation.ispartofconferencetitle2018 INTERNATIONAL CONFERENCE ON INTELLIGENT AUTONOMOUS SYSTEMS (ICOIAS)
dc.relation.ispartofdatefrom2018-03-01
dc.relation.ispartofdateto2018-03-03
dc.relation.ispartoflocationSingapore, SINGAPORE
dc.relation.ispartofpagefrom88
dc.relation.ispartofpagefrom4 pages
dc.relation.ispartofpageto91
dc.relation.ispartofpageto4 pages
dc.subject.fieldofresearchArtificial Intelligence and Image Processing
dc.subject.fieldofresearchcode0801
dc.titleAutomated e-Coaching System Architecture Framework for Promoting Physical Activity
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
dc.description.versionAccepted Manuscript (AM)
gro.rights.copyright© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
gro.hasfulltextFull Text
gro.griffith.authorClanchy, Kelly M.
gro.griffith.authorTjondronegoro, Dian W.


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    Contains papers delivered by Griffith authors at national and international conferences.

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