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Massachusetts Institute of Technology

Signal Processing Techniques Applied to Biomedical Diagnostics

Abstract

dc:description.abstract

An effective way to combat cancer and infectious disease in resource-poor settings is to implement rapid and accurate diagnostic tests that can be administered at the point of care (POC). Developing such miniaturized, portable, and low-cost systems requires innovative approaches in both assay and device design. In this thesis, we construct a novel phase-sensitive "lock-in" amplifier (LIA) based on the Fast Walsh-Hadamard Transform (FWHT), and evaluate its ability to boost the signal-to-noise ratio of optical fluorescence signals. The LIA is designed to be resilient in challenging environments containing high/unpredictable ambient noise. We then develop two rapid diagnostic systems that pair this technology with isothermal CRISPR-Cas12a-based DNA/RNA amplification to detect clinically relevant targets with high specificity. Finally, we evaluate the clinical performance of our systems in detecting target genes for (1) SARS-CoV-2, the virus responsible for the COVID-19 pandemic, and (2) Human Papilloma Virus (HPV), the causal agent of cervical cancer.

Degree

thesis:*
Name thesis:degree_name
Doctoral
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2022

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Degani, Ismail
Advisor dc:contributor.advisor
  • Lee, Hakho

Rights

dc:rights
Statement dc:rights
  • In Copyright - Educational Use Permitted
  • Copyright MIT

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/143262
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/143262

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Degani, Ismail. Signal Processing Techniques Applied to Biomedical Diagnostics. Massachusetts Institute of Technology, 2022. https://hdl.handle.net/1721.1/143262