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dc.contributor.advisorKatabi, Dina
dc.contributor.authorZhang, Guo
dc.date.accessioned2023-01-19T19:57:05Z
dc.date.available2023-01-19T19:57:05Z
dc.date.issued2022-09
dc.date.submitted2022-10-19T19:11:55.006Z
dc.identifier.urihttps://hdl.handle.net/1721.1/147538
dc.description.abstractCurrent health care is primarily in-clinic, episodic, and semi-empirical. With the development of intelligent devices such as smartphones, smartwatches, and more cutting-edge devices such as in-body devices and contactless in-home sensors, we are beginning to see a paradigm shift in health care. The new paradigm can be summarized under the framework of digital health: health care is becoming more embedded in daily life, using more continuously collected data, and making more data-driven decisions. We will discuss three of our research works about digital health in this thesis: the first one details our system for deep in-body communication and localization using a backscatter scheme, which solves the critical challenges of near-zero-power in-body continuous monitoring. The second one describes our work on digital biomarkers that are developed using passive measurement of in-home unscripted daily gait speed data by our contactless in-home sensors, which shows how this new method of daily continuously-collected health data has the potential to transform the way we assess Parkinson’s disease severity, motor fluctuation, and progression. The final work discusses the application of a wireless non-contact monitoring system for patients with COVID-19, which can be used to remotely monitor their acute and long-term physiological and behavioral symptoms. These three studies on continuous monitoring suggest innovative new directions for the future of digital health.
dc.publisherMassachusetts Institute of Technology
dc.rightsIn Copyright - Educational Use Permitted
dc.rightsCopyright MIT
dc.rights.urihttp://rightsstatements.org/page/InC-EDU/1.0/
dc.titlePassive Health Monitoring with RadioWaves —In Body and In Home
dc.typeThesis
dc.description.degreePh.D.
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.orcidhttps://orcid.org/0000-0003-2228-8175
mit.thesis.degreeDoctoral
thesis.degree.nameDoctor of Philosophy


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