dc.contributor.advisor | Lalana Kagal. | en_US |
dc.contributor.author | Paulos, Jason(Jason G.) | en_US |
dc.contributor.other | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. | en_US |
dc.date.accessioned | 2020-09-15T21:58:57Z | |
dc.date.available | 2020-09-15T21:58:57Z | |
dc.date.copyright | 2020 | en_US |
dc.date.issued | 2020 | en_US |
dc.identifier.uri | https://hdl.handle.net/1721.1/127459 | |
dc.description | Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, May, 2020 | en_US |
dc.description | Cataloged from the official PDF of thesis. | en_US |
dc.description | Includes bibliographical references (pages 53-56). | en_US |
dc.description.abstract | Electronic healthcare records are the new standard for storing healthcare data due to their ability to be easily and quickly accessed. Additionally, a new class of fitness records have been created in recent years due to the rise of wearable devices by companies like Fitbit, Apple, and Google. Yet these fitness records are all stored in different formats and can be difficult to extract from the proprietary systems in which they are stored. There are great potential benefits for individuals, healthcare professionals, and researchers to combine this new source of fitness data with traditional patient records in a secure way. The Solid project offers a solution to this problem by allowing individuals to store and manage their health data through the use of personal data stores. The main contributions of this thesis are extending Solid libraries to support the development of mobile Solid applications, developing the functionality to integrate sensor data from phones and wearables into Solid and model it using the FHIR RDF specification, and creating Solid Health, a proof-of-concept decentralized mobile health application. | en_US |
dc.description.statementofresponsibility | by Jason Paulos. | en_US |
dc.format.extent | 56 pages | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Massachusetts Institute of Technology | en_US |
dc.rights | MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. | en_US |
dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
dc.subject | Electrical Engineering and Computer Science. | en_US |
dc.title | Investigating decentralized management of health and fitness data | en_US |
dc.type | Thesis | en_US |
dc.description.degree | M. Eng. | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
dc.identifier.oclc | 1192966772 | en_US |
dc.description.collection | M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science | en_US |
dspace.imported | 2020-09-15T21:58:56Z | en_US |
mit.thesis.degree | Master | en_US |
mit.thesis.department | EECS | en_US |