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Dina Katabi. Kabelac, Zachary(Zachary E.) Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2019-07-12T17:41:49Z 2019-07-12T17:41:49Z 2019 2019 https://hdl.handle.net/1721.1/121613 1102048457 Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019 Cataloged from PDF version of thesis. Includes bibliographical references (pages 145-161). Recent years have witnessed a surge of in-home monitoring and sensing systems. They promise to change healthcare as we know it by continuously monitoring patients at home. Yet, despite all of the interest and effort that has gone into designing these systems, their capabilities are rudimentary and long term retention rates remain low. One of the main reasons for this is that they require the user to either wear or interact with the sensor in order to work effectively. This thesis addresses many of the challenges faced by systems today enabling novel applications in both in-home monitoring and healthcare. To overcome these challenges, this thesis introduces a novel hardware / software sensor that uses radio signals to enable patient health monitoring at home. It hangs on the wall like a picture frame and transmits low-power radio signals which reflect off of the user and return back to the device. By capturing and processing the reflected signals, physiological metrics related to mobility and vital signs can be extracted without touching the user in any way. Furthermore, it relates these health signals to symptoms of Parkinson Disease by deploying the sensor in a pilot study and comparing the health metrics to gold standard clinical assessments. by Zachary E. Kabelac. Ph.D. Ph.D. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science 161 pages eng Massachusetts Institute of Technology MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 Electrical Engineering and Computer Science. In-home passive monitoring for medical applications Thesis application/pdf 2019-07-12T17:41:46Z Publication Doctoral EECS unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="e03d7c37-516d-498d-973f-8937e0145755"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>In-home passive monitoring for medical applications</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2019</PublicationDate> <Authors> <Author> <DisplayName>Kabelac, Zachary(Zachary E.)</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Electrical Engineering and Computer Science.</Keyword> <Abstract>Recent years have witnessed a surge of in-home monitoring and sensing systems. They promise to change healthcare as we know it by continuously monitoring patients at home. Yet, despite all of the interest and effort that has gone into designing these systems, their capabilities are rudimentary and long term retention rates remain low. One of the main reasons for this is that they require the user to either wear or interact with the sensor in order to work effectively. This thesis addresses many of the challenges faced by systems today enabling novel applications in both in-home monitoring and healthcare. To overcome these challenges, this thesis introduces a novel hardware / software sensor that uses radio signals to enable patient health monitoring at home. It hangs on the wall like a picture frame and transmits low-power radio signals which reflect off of the user and return back to the device. By capturing and processing the reflected signals, physiological metrics related to mobility and vital signs can be extracted without touching the user in any way. Furthermore, it relates these health signals to symptoms of Parkinson Disease by deploying the sensor in a pilot study and comparing the health metrics to gold standard clinical assessments.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>