Mobile Health Sensing for Widespread Disease Screening and Chronic Management

dc.contributor.advisorPatel, Shwetak N
dc.contributor.authorWang, Edward Jay
dc.date.accessioned2019-10-15T22:53:51Z
dc.date.available2019-10-15T22:53:51Z
dc.date.submitted2019
dc.descriptionThesis (Ph.D.)--University of Washington, 2019
dc.description.abstractMedical care today revolves mainly around the clinic, with devices and care designed with accuracy as the main metric of success. Many medical tests can be accomplished with just a small vial of blood, and in the ICU we can probe a variety of physiological parameters continuously. In the search for accuracy, accessibility, however, has often taken a backseat. The inability to spread medical sensing out of high-resource regions leads to many medical scenarios that are difficult to care for. A promising approach to increasing people's access to medical sensing and care in diverse situation is to leverage the computing and sensing infrastructure that has been laid out through the adoption of smartphones in the world. I explore using the smartphone as the platform to build a variety of Software as a Medical Device (SaMD), creating solutions for (1) total hemoglobin measurement, (2) personal blood pressure tracking, and (3) Intraocular pressure. In this dissertation, I show that SaMDs enabled by smartphone's built-in sensors has the potential for widespread disease screening and chronic disease and health management through balancing trade-offs between optimizing the sensing solution of the biomarker and addressing practical limitations of designing on real world smartphone devices.
dc.embargo.termsOpen Access
dc.format.mimetypeapplication/pdf
dc.identifier.otherWang_washington_0250E_20737.pdf
dc.identifier.urihttp://hdl.handle.net/1773/44677
dc.language.isoen_US
dc.rightsCC BY
dc.subjectHealth Monitoring
dc.subjectMobile Health
dc.subjectSignal Processing
dc.subjectUbiquitous Computing
dc.subjectUser-Centered Design
dc.subjectElectrical engineering
dc.subjectInformation technology
dc.subjectComputer science
dc.subject.otherElectrical engineering
dc.titleMobile Health Sensing for Widespread Disease Screening and Chronic Management
dc.typeThesis

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