So, Seth
(2021)
Characterization and Determination of Flexible Cardiovascular Biosensors for
Facile Detection of Patient BNP.
Master's Thesis, University of Pittsburgh.
(Unpublished)
Abstract
The sheer amount of individual patient data can often be inundative. However, filtering through large amounts of data quickly would unlock a powerful key to providing effective and personalized treatments, both proactive and reactive. A great area of interest is improving early diagnosis and management strategies for cardiovascular disease (CVD), the leading cause of death in the world. Treatment is often inhibited by analysis delays, but rapid testing and determination can help increase frequency for real-time monitoring. Thus an improvement to the form factor of collection methods is also needed. In this research, a flexible nano-biosensor was developed and characterized for sensitivity and specificity for single and continuous sampling. Additionally two methods are presented in order to better utilize raw patient data. First, a machine learning (ML) implementation of quadratic discriminant analysis (QDA) was trained on sensor characterization data to develop a model for digital determination. Second, a tunable ultrasensitive bio-signal amplification circuit with a simple LED output was designed for analog determination. Both methods were tested on human blood serum samples from 30 University of Pittsburgh Medical Center patients. The ML algorithm yielded 95% power when separating samples, comparable to 3-dimensional principal component analysis (PCA) results. The circuit was able to accurately identify each sample as one of three categories: sub-threshold, analog, and saturation regions, corresponding to 0 < [C] < 500 pg/mL (LEDoff ), 500 < [C] < 1000 pg/mL (LEDdim), and 1000
pg/mL < [C] (LEDbright).
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Details
| Item Type: |
University of Pittsburgh ETD
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| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
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| Date: |
13 June 2021 |
| Date Type: |
Publication |
| Defense Date: |
26 March 2021 |
| Approval Date: |
13 June 2021 |
| Submission Date: |
17 March 2021 |
| Access Restriction: |
2 year -- Restrict access to University of Pittsburgh for a period of 2 years. |
| Number of Pages: |
56 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
Swanson School of Engineering > Electrical Engineering |
| Degree: |
MS - Master of Science |
| Thesis Type: |
Master's Thesis |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
biosensor, BNP, cardiovascular, LED, ISFET, nanomaterial, point-of-care.
iv |
| Date Deposited: |
13 Jun 2021 18:40 |
| Last Modified: |
13 Jun 2023 05:15 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/40386 |
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