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oai:dspace.mit.edu:1721.1/1475382023-01-20T03:02:36Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022

Katabi, Dina Zhang, Guo Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2023-01-19T19:57:05Z 2023-01-19T19:57:05Z 2022-09 2022-10-19T19:11:55.006Z https://hdl.handle.net/1721.1/147538 https://orcid.org/0000-0003-2228-8175 Current 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. Ph.D. Massachusetts Institute of Technology In Copyright - Educational Use Permitted Copyright MIT http://rightsstatements.org/page/InC-EDU/1.0/ Passive Health Monitoring with RadioWaves —In Body and In Home Thesis application/pdf Doctoral Doctor of Philosophy Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="ee84fd94-4b62-4bac-a86c-8af63009cbae"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Title>Passive Health Monitoring with RadioWaves —In Body and In Home</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2022-09</PublicationDate> <Authors> <Author> <DisplayName>Zhang, Guo</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://rightsstatements.org/page/InC-EDU/1.0/</License> <Abstract>Current 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.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>