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Magnetic phagocyte biosensing framework for point-of-care sepsis diagnostics and monitoring
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Norton, Corey Benjamin. Magnetic phagocyte biosensing framework for point-of-care sepsis diagnostics and monitoring. Retrieved from https://doi.org/doi:10.7282/t3-sxnt-a053

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TitleMagnetic phagocyte biosensing framework for point-of-care sepsis diagnostics and monitoring
NameNorton, Corey Benjamin (author); Hassan, Umer (chair); Gajic, Zoran (internal member); Wu, Chung-Tse (internal member); Rutgers University; School of Graduate Studies
Date Created2020
Other Date2020-05 (degree)
SubjectBiosensor, Septicemia -- Diagnosis, Electrical and Computer Engineering
Extent1 online resource (ix, 45 pages) : illustrations
DescriptionSepsis, a potentially deadly immunoresponse to infection, is a major concern in hospitals in the United States. Current laboratory processes used to diagnose and monitor sepsis are costly, time-consuming, or only provide a small piece of information about the complex condition. In order to develop specific individualized treatments for septic patients that do not heavily depend on the use of broad-spectrum antibiotics, a clinician must be provided with both pathogen information about the underlying infection and patient immunoresponse information. While there has been considerable progress towards biosensor designs that can provide pathogen information, there is still a significant demand for designs that can provide immunoresponse information.

The design of a novel biosensing framework has been proposed for gathering information about a patient’s phagocytes, critical components of the innate immune system that protect the body from infection. The design is composed of electrical, microfluidic, and magnetic subsystems that work together to produce a distinct electrical signature signifying the presence of functional phagocytes in a human blood sample. The device has been simulated, fabricated, and experimentally tested using 17 blood samples collected from patients suspected of bacterial infections. Furthermore, two pattern recognition neural networks were developed to analyze and classify the experimental data. One network detects the presence of functional phagocytes in a biological sample with 88.2% accuracy, and the other network diagnoses sepsis with 88.2% accuracy by analyzing these functional phagocytes. This novel framework presents the potential to reduce the mortality rate of sepsis by allowing for earlier diagnosis and treatment.
NoteM.S.
NoteIncludes bibliographical references
Genretheses, ETD graduate
Persistent URLhttps://doi.org/doi:10.7282/t3-sxnt-a053
LanguageEnglish
CollectionSchool of Graduate Studies Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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