Location-targeted measurement of perceived stress

Modern medicine has made significant advancements in the treatment of acute diseases, disorders, and injury. However, the acute care system rising from the twentieth century medical industry is far less adept in tracking and managing the needs of chronic conditions, especially that of chronic stress. Here we propose utilizing daily behavioral patterns to develop a model of daily stress, predictive of contexts leading to elevated perceived stress within an individual. We identify the smartphone as an effective data logger of daily life, and demonstrate a battery-efficient method of all-day behavior tracking, particularly location and activity, of individuals within an open environment. This behavioral logging is then combined with on-device experience sampling to create and evaluate a model of perceived stress built from extracted features of daily activity, including exercise, social, and sleep.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Bioinformatics

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2013

Author dc:creator

• Gregory, Clay E.

Contributors dc:contributor

• Schatz, Bruce R.

• mHealth
• Mobile health
• Smartphone
• Behavior tracking
• Daily routine
• Psychological stress

Statement dc:rights

• Copyright 2013 Clay Gregory

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/45532

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/45532