ORCID Identifier(s)

0000-0002-3453-0398

Graduation Semester and Year

2020

Language

English

Document Type

Thesis

Degree Name

Master of Science in Computer Science

Department

Computer Science and Engineering

First Advisor

Fillia Makedon

Second Advisor

Maria Kyrarini

Abstract

With the ubiquitous presence of mobile phones, there is too much data that can be collected for different purposes which can be correlated to monitor multiple more user information. If used responsibly, this data can be used to assess and monitor various mental health conditions. For example, fitness sensors in wearable devices collect step counts, sleep-related data and heart rate; GPS sensors in smartphones continually collect device location, and Android on-device services collect smartphone usage habits of the user. All the data from the previous example relate to exhibited depression symptoms in users. This data, when used in conjugation, has the potential to assess and monitor such symptoms in users. In this study, we collect the mentioned user data anonymously to analyze and inspect our hypotheses.

Keywords

Depression, Mobile application, Azul, Android, PHQ

Disciplines

Computer Sciences | Physical Sciences and Mathematics

Comments

Degree granted by The University of Texas at Arlington

29140-2.zip (423 kB)

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