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Sensors 2010, 10(4), 3934-3953; doi:10.3390/s100403934

A Monitoring and Advisory System for Diabetes Patient Management Using a Rule-Based Method and KNN

1 Center for Advanced Image and Information Technology, School of Electronics & Information Engineering, ChonBuk National University, 664-14, 1Ga, DeokJin-Dong, JeonJu, ChonBuk, 561-756, Korea 2 The School of Engineering and Technology, National University, 11255 North Torrey Pines Road, La Jolla, CA 92037, USA 3 Department of Beauty Arts, Koguryeo College, Chonnam, Naju City, Korea
* Author to whom correspondence should be addressed.
Received: 25 January 2010 / Revised: 17 March 2010 / Accepted: 30 March 2010 / Published: 19 April 2010
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Diabetes is difficult to control and it is important to manage the diabetic’s blood sugar level and prevent the associated complications by appropriate diabetic treatment. This paper proposes a system that can provide appropriate management for diabetes patients, according to their blood sugar level. The system is designed to send the information about the blood sugar levels, blood pressure, food consumption, exercise, etc., of diabetes patients, and manage the treatment by recommending and monitoring food consumption, physical activity, insulin dosage, etc., so that the patient can better manage their condition. The system is based on rules and the K Nearest Neighbor (KNN) classifier algorithm, to obtain the optimum treatment recommendation. Also, a monitoring system for diabetes patients is implemented using Web Services and Personal Digital Assistant (PDA) programming.
Keywords: diabetes; monitoring system; KNN classifier algorithm; ubiquitous healthcare diabetes; monitoring system; KNN classifier algorithm; ubiquitous healthcare
This is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Lee, M.; Gatton, T.M.; Lee, K.-K. A Monitoring and Advisory System for Diabetes Patient Management Using a Rule-Based Method and KNN. Sensors 2010, 10, 3934-3953.

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