Skip to main content


eCommons@Cornell

eCommons@Cornell >
College of Engineering >
Biological and Environmental Engineering >
BEE 4530 - Computer-Aided Engineering >
BEE 4530 - 2008 Student Papers >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1813/11136
Title: Modeling and Optimization of a Bioartificial Implant to Alleviate Diabetes
Authors: Hung, Ben
Fe, Alex
Schmidt, Greg
Keywords: Diabetes
Beta-cells
Insulin delivery
Issue Date: 23-Jul-2008
Series/Report no.: BEE 453
Abstract: Diabetes is a chronic disease that is characterized by a person having too high blood sugar levels due to the deficiency of insulin. If left untreated, there is serious risk for development of cardiovascular diseases, renal failure, blindness, nerve damage, etc. Currently, this condition is treated by constant monitoring combined with insulin injection. Given that the various forms of this treatment have negative effects on overall quality of life, this paper focuses on modeling a different type of treatment that can potentially reduce the need for constant blood monitoring and reduce the need for insulin supplementation. The treatment involves surgically implanting a shunt with Beta-islet cells next to a blood vessel in the body [1]. Here, the Beta-islet cells release insulin that follows a bell-shaped curve when graphed vs. time [2], and this insulin diffuses across a semi-permeable membrane and into the bloodstream. After analyzing the results of the model, it was determined that insulin levels with the implant matched very closely with natural physiological levels, making this treatment a viable one. This treatment also showed the ability to emit a variety of insulin levels making it suitable for a wide variety of patients. This makes this a potentially important avenue of research and worthy of further study.
URI: http://hdl.handle.net/1813/11136
Appears in Collections:BEE 4530 - 2008 Student Papers

Files in This Item:

File Description SizeFormat
Group 9.pdf748.36 kBAdobe PDFView/Open

Refworks Export

Items in eCommons are protected by copyright, with all rights reserved, unless otherwise indicated.

 

© 2014 Cornell University Library Contact Us