• DocumentCode
    3746226
  • Title

    An interactive healthcare system with personalized diet and exercise guideline recommendation

  • Author

    Jerry C.C. Tseng;Bo-Hau Lin;Yu-Feng Lin;Vincent S. Tseng;Miin-Luen Day;Shyh-Chyi Wang;Kuen-Rong Lo;Yi-Ching Yang

  • Author_Institution
    Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan City, Taiwan (R.O.C.)
  • fYear
    2015
  • Firstpage
    525
  • Lastpage
    532
  • Abstract
    Recently people pay more and more attention on how to effectively and efficiently analyze the result of regular physical examinations to provide the most helpful information for individual health management. In this paper, we design and develop an interactive system of virtual healthcare assistant to help people, especially for those who suffer from chronic diseases (e.g., metabolic syndrome) to easily understand their health conditions and then well manage it. This system analyzes the result of regular physical examination to evaluate the health risk and provide personalized healthcare services for users in terms of diet and exercise guideline recommendations. We developed some interactive ways for users to easily feedback their vital signs to the system and quickly get the suggestions for health management from the system. Besides the browser-based system, we also developed a mobile App that can regularly remind users to carry out the recommendations, which are provided by the system. To prove the system is feasible in the real-world clinical environment, we also applied the Institutional Review Board (IRB) for a human subject research to validate this system. Other than the functional features, there are also several important non-functional features of the extensibility and the convenience for use. First, we use the physical examination result as the raw data to be analyzed. It´s very convenient for users with very low cost. Second, the system design is extendable, so it can be easily adjusted to work for any chronic ills, even other kinds of diseases. Moreover, it can be extended to provide other kinds of healthcare guideline recommendations as well. These features constitute the main contributions of this work.
  • Keywords
    "Guidelines","Diseases","Real-time systems","Physiology","Databases","Cities and towns"
  • Publisher
    ieee
  • Conference_Titel
    Technologies and Applications of Artificial Intelligence (TAAI), 2015 Conference on
  • Electronic_ISBN
    2376-6824
  • Type

    conf

  • DOI
    10.1109/TAAI.2015.7407106
  • Filename
    7407106