SIMS: Self-adaptive Intelligent Monitoring System for supporting home-based heart failure patients
Paper
Paper/Presentation Title | SIMS: Self-adaptive Intelligent Monitoring System for supporting home-based heart failure patients |
---|---|
Presentation Type | Paper |
Authors | Wang, Hua (Author), Zhang, Ji (Author), Soar, Jeffrey (Author), Tao, Xiaohui (Author) and Huang, Wei (Author) |
Editors | Biswas, Jit, Kobayashi, Hisato, Wong, Lawrence, Abdulrazak, Bessam and Mokhtari, Mounir |
Journal or Proceedings Title | Lecture Notes in Computer Science (Book series) |
ERA Conference ID | 60495 |
Journal Citation | 7910, pp. 322-330 |
Number of Pages | 9 |
Year | 2013 |
Publisher | Springer |
Place of Publication | Heidelberg, Germany |
ISSN | 1611-3349 |
0302-9743 | |
ISBN | 9783642394690 |
9783642394706 | |
Digital Object Identifier (DOI) | https://doi.org/10.1007/978-3-642-39470-6_43 |
Web Address (URL) of Paper | http://www.springer.com/?SGWID=0-102-24-0-0&searchType=EASY_CDA&queryText=ICOST+2013+Singapore |
Conference/Event | 11th International Conference on Smart Homes and Health Telematics (ICOST 2013): Inclusive Society: Health and Wellbeing in Ageing-Friendly Community: eHealth, Telemedicine, Chronic Disease Management and Care at Home |
International Conference on Smart Homes and Health Telematics (ICOST) | |
Event Details | 11th International Conference on Smart Homes and Health Telematics (ICOST 2013): Inclusive Society: Health and Wellbeing in Ageing-Friendly Community: eHealth, Telemedicine, Chronic Disease Management and Care at Home Event Date 19 to end of 21 Jun 2013 Event Location Singapore |
Event Details | International Conference on Smart Homes and Health Telematics (ICOST) ICOST |
Abstract | This paper presents our research work to develop an advanced Self-adaptive Intelligent Monitoring System (SIMS) to help patients, families and clinicians manage chronic conditions associated with heart failure more effectively at home. SIMS takes advantages of a number of advanced technologies from software intelligence, data/knowledge retrieval, data mining and database. SIMS is able to provide a number of advanced functions. It can effectively prioritize patients, provide automatic recommendation for checking frequency and risk assessment, and carry out correlation analysis in order to pinpoint relationships between external factors and the development of patient's heart condition overtime. All these functions can significantly reduce patients' burden for checking, build up their self-confidence of health and enhance their general quality of life. |
Keywords | self-adaptive technology; home-based healthcare; risk analysis; recommender system; correlation analysis |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
400308. Medical devices | |
420399. Health services and systems not elsewhere classified | |
Public Notes | File reproduced in accordance with the copyright policy of the publisher/author. |
Byline Affiliations | Department of Mathematics and Computing |
Faculty of Business and Law | |
Hubei University of Technology, China | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q20ww/sims-self-adaptive-intelligent-monitoring-system-for-supporting-home-based-heart-failure-patients
Download files
1883
total views1267
total downloads1
views this month1
downloads this month