Semester of Graduation
Fall 2023
Degree
Master of Science in Electrical Engineering (MSEE)
Department
Division of Electrical & Computer Engineering
Document Type
Thesis
Abstract
The research presented in this thesis focuses on the design, development, and evaluation of a fluorescence detection system. The system is implemented primarily as an Android application, Auto Camera, which leverages smartphone cameras to capture and analyze fluorescent images. The application provides a user-friendly interface with some configurable features like exposure time, ISO speed, and storage limit; as well as defining detection thresholds and setting acquisition intervals. This study begins with the architectural framework of the Android application, which is written in Java using Android Studio. The API compatibility is set to version 33, and users are prompted to grant device access permission upon installation. The application allows users to take snipped pictures, categorize captured images, and generate alarm triggers based on specific color criteria for further analysis. There is an underlying methodology consisting of the utilization of distilled water and SYBR Green Supermix as the control samples, with multiple test samples created using the dsDNA-SYBR Green I complex. The prepared holder was filled with the specimen, then an optical unit was used to transmit appropriate light through the samples for excitation. The testing of the combinations of different exposure times and ISO speeds occurred under two lighting conditions to evaluate the fluorescence intensity through capturing images. These experiments demonstrated the functionality of the application, producing data related to green value, alarm conditions, and image quality; which can also be termed as metadata. The results showed that the performance of the application varied with different modes. The fluorescence intensity exhibited decaying patterns across the diluted test samples, indicating the ability of the system to detect and measure fluorescence accurately. Therefore, the research outcomes suggested that the application could effectively detect and analyze fluorescence intensity, achieving the highest accuracy when using specific settings under expert supervision. The research findings provide valuable insights into the performance of the portable and inexpensive system with its potential applications in various scientific research domains. The green fluorescence-based analysis and imaging allows researchers to assess gene expression, cellular health, molecular localization, and much more, making it a valuable technique for understanding and studying biological processes.
Date
11-16-2023
Recommended Citation
Efaz, Erteza T., "Improving Cellphone-based Bio-imaging Technique for Fluorescence Detection" (2023). LSU Master's Theses. 5871.
https://repository.lsu.edu/gradschool_theses/5871
Committee Chair
Dr. Jian Xu
Included in
Biomedical Commons, Controls and Control Theory Commons, Electrical and Electronics Commons, Electromagnetics and Photonics Commons, Electronic Devices and Semiconductor Manufacturing Commons, Nanotechnology Fabrication Commons, Other Electrical and Computer Engineering Commons, Power and Energy Commons, Signal Processing Commons, Systems and Communications Commons, VLSI and Circuits, Embedded and Hardware Systems Commons