Passive Health Monitoring with RadioWaves —In Body and In Home
Name
Zhang-guozhang-PhD-EECS-2022-thesis.pdf
Description
Thesis PDF
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16.86 MB
Format
Adobe PDF
Checksum (MD5)
ad3788ec751ed36f60e125a1e0e223e6
Author(s)
Zhang, Guo
Advisor(s)
Katabi, Dina
Date Issued
September 2022
Publisher
Massachusetts Institute of Technology
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.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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