Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/21718
Title: Monitor blood glucose levels via breath analysis system and sparse representation approach
Authors: Guo, D
Zhang, D 
Li, N
Issue Date: 2010
Source: Proceedings of IEEE Sensors, 2010, p. 1238-1241 How to cite?
Abstract: It has been reported that the abnormal concentration of acetone in exhaled air is an indicator of diabetes and the concentration rises progressively with the blood glucose level of patients. Therefore, the acetone in human breath can be used to monitor the development of diabetes. In this paper, we introduce a breath analysis system to measure acetone in human breath, and therefore to evaluate the blood glucose levels of diabetics. The system structure, breath collection method, and signal preprocessing method are introduced. To enhance the system performance, we use a novel classification approach, i.e., Sparse Representation based Classification (SRC), to classify diabetics' breath samples into different blood glucose levels. Experimental results show that coupling with SRC, the system is able to classify these levels with satisfactory accuracy.
Description: 9th IEEE Sensors Conference 2010, SENSORS 2010, Waikoloa, HI, 1-4 November 2010
URI: http://hdl.handle.net/10397/21718
ISBN: 9781424481682
DOI: 10.1109/ICSENS.2010.5690611
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