English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113318/144297 (79%)
Visitors : 50995719      Online Users : 314
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
    •  Adv. Search
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version
    政大機構典藏 > 資訊學院 > 資訊科學系 > 會議論文 >  Item 140.119/98241


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/98241


    Title: Daily Health Assessment System Using Prediction Model for Self-rated Health by Vital Sign Pattern
    Authors: Huang, Kuan-Ling;Chen, Ya-Hung;Liao, Chun-Feng;Fu, Li-Chen
    廖峻鋒
    Contributors: 資科系
    Date: 2014-10
    Issue Date: 2016-06-22 17:15:34 (UTC+8)
    Abstract: With the growing population of aging people around the world, there is an increasing needs for elders to be aware of their health status not only in hospital but also in home environment. Due to recent advances of health monitoring technologies, elder people are able to easily assess their physiological well-being at home. However, most of current physiological monitoring systems focus on the patient with critical situation such as the intensive care unit and there are relatively fewer systems aim to assess these trends in home scenario. Additionally, most of the current home vital sign monitoring systems use pre-determined threshold to identify the dangerous situation over single measurement or just focus on the system architecture as well as communication technique. It is essential to develop a healthcare system that is capable to make an alarm far before elderly people is in acute situation. In this paper, a data model is built for the vital sign trends over certain number of days. In order to determine the dangerous situation, this model is associated with a common health assess tool - self-rated health, which has been confirmed a predictor for mortality over elder population. To demonstrate the feasibility of our system, four subjects aging from 58 to 95 had been participated in experiment and collected vital sign once a day. The result shows that the proposed system is able to identify the poor health condition based on the collected data with high precision.
    Relation: Proc. IEEE Healthcare Innovation Point-Of-Care Technologies Conference, Seattle, Washington, USA, 2014, 95-98
    Data Type: conference
    DOI 連結: http://dx.doi.org/10.1109/HIC.2014.7038883
    DOI: 10.1109/HIC.2014.7038883
    Appears in Collections:[資訊科學系] 會議論文

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML2985View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback