Author: Hanqin Yang
Yang, Hanqin, 2019 Design and image processing of home–based medical devices for CKD monitoring, Flinders University, College of Science and Engineering
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Chronic kidney disease (CKD) refers to all conditions of the kidney, lasting at least 3 months. CKD is categorized into 5 stages according to the level of reduced kidney function and evidence of kidney damage. Evidence of kidney damage manifests as either urinary protein or albumin (a type of protein that is a more sensitive and specific marker of kidney disease), blood in the urine, or scarring detected by imaging tests. CKD is often referred to as a "silent disease" because up to 90% of kidney function is lost before symptoms appear. As a result, many people do not know that they have this situation. CKD is largely preventable, as long as a simple test of human blood and urine can determine most of the CKD cases at an early stage of the disease, thereby preventing or slowing its progression. Many of the risk factors for CKD also apply to other chronic diseases such as cardiovascular disease (including coronary heart disease and stroke) and diabetes, which are risk factors for CKD. Traditional CKD monitoring testing requires patients to go to the hospital on a regular basis, which is time consuming, expensive and requires highly trained medical staff and sophisticated diagnostic equipment. Therefore, this project is aim to develop a home-based medical devices for CKD monitoring which patients are able to do the tests at home by themselves with a potable, convenient and affordable device. Aggregation-induced emission (AIE) bioprobe is used to detect human serum albumin (HSA) concentration ranges in urine for early detection of chronic kidney disease. In the presence of HAS, the non luminescent bio probe become emissive and visible. In the black box experiment environment, use ultraviolet light to excite the testing cuvette. Then use camera (TRDB-D5M) to record the level of fluorescence. After image processing of micro controller FPGA (Field Programmable Gate Array), the correlation between light intensity and HSA concentration will be determined. The medical device in this project is low cost, efficiently, reliably, sensitive, fast, user-friendly, and is expected to help users to monitor early stage of chronic kidney disease at home.
Keywords: Image processing, home–based medical devices, Chronic kidney disease (CKD), FPGA (Field Programmable Gate Array)
Subject: Engineering thesis
Thesis type: Masters
Completed: 2019
School: College of Science and Engineering
Supervisor: Professor Youhong Tang