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dc.contributor.advisorRosalind W. Picard.en_US
dc.contributor.authorAyzenberg, Yadiden_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Architecture. Program in Media Arts and Sciences.en_US
dc.date.accessioned2013-03-28T18:15:04Z
dc.date.available2013-03-28T18:15:04Z
dc.date.copyright2012en_US
dc.date.issued2012en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/78206
dc.descriptionThesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2012.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 69-73).en_US
dc.description.abstractIf we are to learn the effects of the environment and our day-to-day actions, and choices on our physiology, we must develop systems that will label biophysiological senor data with contextual information. In this thesis I first present an architecture and implementation of FEEL: a system for the acquisition, processing and visualization of biophysiological signals and contextual information. The system comprises a mobile client application (FMC) and a backend server, The mobile client collects contextual information: phone call details, email reading details, calendar entries, and user location at a fixed interval that is transmitted to the backend server. The backend server stores the contextual information and biophysiological signal data that is uploaded by the user, processes the information and provides a novel interface for viewing the combined data. Next, I present the results of a 10-day user study in which users wore Electrodermal Activity (EDA) wrist sensors that measured their autonomic arousal levels. These users were requested to upload the sensor data and annotate it at the end of the day at first, and then after two days. One group of users had access to both the signal and the full contextual information collected by the mobile phone and the other group could only access the bio physiological signal. At the end of the study the users were asked to fill in a System Usability Scale (SUS) questionnaire, a user experience survey and a Toronto-Alexithymia (TAS-20) questionnaire. My results show that the FEEL system enables the users to annotate bio-physiological signals at a greater effectiveness than the current state of the art. Finally, I showed that there is a correlation between a person's ability to determine their own arousal level and their score on the Toronto-alexithymia test: the less alexythymic they were, the better their correlation between the EDA and their self-reported arousal.en_US
dc.description.statementofresponsibilityby Yadid Ayzenberg.en_US
dc.format.extent92 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectArchitecture. Program in Media Arts and Sciences.en_US
dc.titleFEEL : a system for acquisition, processing and visualization of biophysiological signals and contextual informationen_US
dc.title.alternativeFrequent EDA and Event Loggingen_US
dc.title.alternativeSystem for acquisition, processing and visualization of biophysiological signals and contextual informationen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentProgram in Media Arts and Sciences (Massachusetts Institute of Technology)
dc.identifier.oclc830534892en_US


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