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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Myung-kyung Suh Moin, T. Woodbridge, J. Lan, M. Ghasemzadeh, H. Bui, A. Ahmadi, S. Sarrafzadeh, M. |
| Copyright Year | 2012 |
| Description | Author affiliation: Dept. of Med., VA Greater Los Angeles Center of Excellence for the Study of Healthcare Provider Behavior, Los Angeles, CA, USA (Moin, T.) || Div. of Endocrinology, Univ. of California, Los Angeles, Los Angeles, CA, USA (Ahmadi, S.) || Comput. Sci. Dept., Univ. of California, Los Angeles, Los Angeles, CA, USA (Myung-kyung Suh; Woodbridge, J.; Lan, M.; Ghasemzadeh, H.; Sarrafzadeh, M.) || Dept. of Radiol. Sci., Univ. of California, Los Angeles, Los Angeles, CA, USA (Bui, A.) |
| Abstract | Diabetes is the seventh leading cause of death in the United States. In 2010, about 1.9 million new cases of diabetes were diagnosed in people aged 20 years or older. Remote health monitoring systems can help diabetics and their healthcare professionals monitor health-related measurements by providing real-time feedback. However, data-driven methods to dynamically prioritize and generate tasks are not well investigated in the remote health monitoring. This paper presents a task optimization technique used in WANDA (Weight and Activity with Blood Pressure and Other Vital Signs); a wireless health project that leverages sensor technology and wireless communication to monitor the health status of patients with diabetes. WANDA applies data analytics in real-time to improving the quality of care. The developed algorithm minimizes the number of daily tasks required by diabetic patients using association rules that satisfies a minimum support threshold. Each of these tasks maximizes information gain, thereby improving the overall level of care. Experimental results show that the developed algorithm can reduce the number of tasks up to 28.6% with minimum support 0.95, minimum confidence 0.97 and high efficiency. |
| Sponsorship | IEEE Eng. Medicine Biol. Soc. |
| Starting Page | 2223 |
| Ending Page | 2226 |
| File Size | 462298 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424441198 |
| ISSN | 1557170X |
| e-ISBN | 9781457717871 |
| DOI | 10.1109/EMBC.2012.6346404 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-08-28 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Diabetes Monitoring Association rules Biomedical monitoring Algorithm design and analysis Prediction algorithms Blood pressure |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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