Cited 19 times in
Integrated Solution for Physical Activity Monitoring Based on Mobile Phone and PC.
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 유선국 | - |
dc.contributor.author | 지선하 | - |
dc.date.accessioned | 2014-12-20T17:33:45Z | - |
dc.date.available | 2014-12-20T17:33:45Z | - |
dc.date.issued | 2011 | - |
dc.identifier.issn | 2093-3681 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/94833 | - |
dc.description.abstract | OBJECTIVES: This study is part of the ongoing development of treatment methods for metabolic syndrome (MS) project, which involves monitoring daily physical activity. In this study, we have focused on detecting walking activity from subjects which includes many other physical activities such as standing, sitting, lying, walking, running, and falling. Specially, we implemented an integrated solution for various physical activities monitoring using a mobile phone and PC. METHODS: We put the iPod touch has built in a tri-axial accelerometer on the waist of the subjects, and measured change in acceleration signal according to change in ambulatory movement and physical activities. First, we developed of programs that are aware of step counts, velocity of walking, energy consumptions, and metabolic equivalents based on iPod. Second, we have developed the activity recognition program based on PC. iPod synchronization with PC to transmit measured data using iPhoneBrowser program. Using the implemented system, we analyzed change in acceleration signal according to the change of six activity patterns. RESULTS: We compared results of the step counting algorithm with different positions. The mean accuracy across these tests was 99.6 ± 0.61%, 99.1 ± 0.87% (right waist location, right pants pocket). Moreover, six activities recognition was performed using Fuzzy c means classification algorithm recognized over 98% accuracy. In addition we developed of programs that synchronization of data between PC and iPod for long-term physical activity monitoring. CONCLUSIONS: This study will provide evidence on using mobile phone and PC for monitoring various activities in everyday life. The next step in our system will be addition of a standard value of various physical activities in everyday life such as household duties and a health guideline how to select and plan exercise considering one's physical characteristics and condition. | - |
dc.description.statementOfResponsibility | open | - |
dc.format.extent | 76~86 | - |
dc.relation.isPartOf | HEALTHCARE INFORMATICS RESEARCH | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/2.0/kr/ | - |
dc.title | Integrated Solution for Physical Activity Monitoring Based on Mobile Phone and PC. | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Medical Engineering (의학공학) | - |
dc.contributor.googleauthor | Mi Hee Lee | - |
dc.contributor.googleauthor | Jungchae Kim | - |
dc.contributor.googleauthor | Sun Ha Jee | - |
dc.contributor.googleauthor | Sun Kook Yoo | - |
dc.identifier.doi | 10.4258/hir.2011.17.1.76 | - |
dc.admin.author | false | - |
dc.admin.mapping | false | - |
dc.contributor.localId | A02471 | - |
dc.contributor.localId | A03965 | - |
dc.relation.journalcode | J00974 | - |
dc.identifier.eissn | 2093-369X | - |
dc.identifier.pmid | 21818460 | - |
dc.subject.keyword | Walking | - |
dc.subject.keyword | Ambulatory Monitoring | - |
dc.subject.keyword | Cellular Phone | - |
dc.contributor.alternativeName | Yoo, Sun Kook | - |
dc.contributor.alternativeName | Jee, Sun Ha | - |
dc.contributor.affiliatedAuthor | Yoo, Sun Kook | - |
dc.contributor.affiliatedAuthor | Jee, Sun Ha | - |
dc.rights.accessRights | free | - |
dc.citation.volume | 17 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 76 | - |
dc.citation.endPage | 86 | - |
dc.identifier.bibliographicCitation | HEALTHCARE INFORMATICS RESEARCH, Vol.17(1) : 76-86, 2011 | - |
dc.identifier.rimsid | 27782 | - |
dc.type.rims | ART | - |
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