{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/147538"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/147538","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Passive Health Monitoring with RadioWaves —In Body and In Home","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_html":"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_has_math":false,"creators":["Zhang, Guo"],"institution":"Massachusetts Institute of Technology","degree_name":"Doctoral","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. 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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."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph.D."]},{"key":"dc:title","label":"Title","values":["Passive Health Monitoring with RadioWaves —In Body and In Home"]}]}],"canonical_facts":{"dc:contributor.advisor":["Katabi, Dina"],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science"],"dc:creator":["Zhang, Guo"],"dc:date.accessioned":["2023-01-19T19:57:05Z"],"dc:date.available":["2023-01-19T19:57:05Z"],"dc:date.issued":["2022-09"],"dc:description.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. 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