• Title/Summary/Keyword: 비쥬얼패스맵

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Visualizing Excercise Prescription Using Visual Path Map (비쥬얼패스맵을 이용한 운동처방 과정 시각화)

  • Ham, Jun-Seok;Jeong, Chan-Soon;Ko, Il-Ju
    • Journal of Korea Multimedia Society
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    • v.14 no.9
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    • pp.1182-1189
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    • 2011
  • We named the system Visual Path Map which visualizes the distribution of clusters according to characteristics and entire process about exercise prescription, and we purpose to visualize a process according to exercise prescription. Visual Path Map visualizes the distribution of clusters according to characteristics, current and object distribution, and changed distribution for prescription. So it visualizes paths from current distribution to object distribution according to prescription. We used SOM in order to express properties along subjects in Visual Path map, and visualized distribution of clusters about physical characteristics, body mass index, and age information of 1,500 ordinary people. Also we visualize practical exercise prescription according to real data of expert of exercise prescription.

Smart Exercise Prescription of Elderly Users using Visual Path Map (비쥬얼패스맵을 이용한 고령자 대상의 스마트 운동처방)

  • Jeong, Chan-Soon;Ham, Jun-Seok;Ko, Il-Ju;Hur, Jun-Soo
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.10
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    • pp.185-196
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    • 2011
  • Exercise programs for elderly users are operated by each department and facility, but it is not enough to visualize exercise prescription and effect followed by elderly users physical conditions. The purpose of this study is to suggest exercise prescription for elderly users with a visual path map. A visual path map is to visually present types of users classified according to physical strength conditions, the process of exercise prescription, and effects of exercise. Exercise prescription is divided into four stages: analysis of physical conditions, exercise prescription by the visual path map, smart exercise prescription, and exercise for elderly users. The first stage, analysis of physical conditions is to classify physical conditions by each type by mechanically learning elderly users' physical test values. The second stage, exercise prescription by the visual path map, is to present exercise prescription suitable for elderly users' physical conditions. The third stage, smart exercise prescription, is to offer exercise prescription of the day when exercise is carried out using elderly users' smart phones in consideration of their situations. The fourth stage, exercise for elderly users, is to provide information by their smart phones when they exercise. In conclusion, this study will be able to induce elderly users to do continuous exercise by motivating them.