2026-09-19T00:02:35Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1062352022-01-13T07:55:19Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Michael A. Davies.
Lam, Lawrence G
Massachusetts Institute of Technology. Engineering Systems Division.
Massachusetts Institute of Technology. Engineering and Management Program
System Design and Management Program.
2017-01-06T16:13:12Z
2017-01-06T16:13:12Z
2015
2015
http://hdl.handle.net/1721.1/106235
961355696
Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, School of Engineering, System Design and Management Program, Engineering and Management Program, 2015.
Cataloged from PDF version of thesis.
Includes bibliographical references (page 81).
Digital Health-Data is being collected at unprecedented rates today as biometric micro sensors continue to diffuse into our lives in the form of smart devices, wearables, and even clothing. From this data, we hope to learn more about preventative health so that we can spend less money on the doctor. To help users aggregate this perpetual growth of biometric "big" data, Apple HealthKit, Google Fit, and Samsung SAMI were each created with the hope of becoming the dominant design platform for Digital Health-Data. The research for this paper consists of citings from technology strategy literature and relevant journalism articles regarding recent and past developments that pertain to the wearables market and the digitization movement of electronic health records (EHR) and protected health information (PHI) along with their rules and regulations. The culmination of these citations will contribute to my hypothesis where the analysis will attempt to support my recommendations for Apple, Google, and Samsung. The ending chapters will encompass discussions around network effects and costs associated with multi-homing user data across multiple platforms and finally ending with my conclusion based on my hypothesis.
by Lawrence G. Lam.
S.M. in Engineering and Management
81 pages
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Engineering and Management Program.
System Design and Management Program.
Engineering Systems Division.
Digital Health-Data platforms : biometric data aggregation and their potential impact to centralize Digital Health-Data
Biometric data aggregation and their potential impact to centralize Digital Health-Data
Thesis
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Publication
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<Abstract>Digital Health-Data is being collected at unprecedented rates today as biometric micro sensors continue to diffuse into our lives in the form of smart devices, wearables, and even clothing. From this data, we hope to learn more about preventative health so that we can spend less money on the doctor. To help users aggregate this perpetual growth of biometric "big" data, Apple HealthKit, Google Fit, and Samsung SAMI were each created with the hope of becoming the dominant design platform for Digital Health-Data. The research for this paper consists of citings from technology strategy literature and relevant journalism articles regarding recent and past developments that pertain to the wearables market and the digitization movement of electronic health records (EHR) and protected health information (PHI) along with their rules and regulations. The culmination of these citations will contribute to my hypothesis where the analysis will attempt to support my recommendations for Apple, Google, and Samsung. The ending chapters will encompass discussions around network effects and costs associated with multi-homing user data across multiple platforms and finally ending with my conclusion based on my hypothesis.</Abstract>
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