"Sedentary lifestyles are ubiquitous in modern societies. Sitting, watching television and using the computer are examples of sedentary behaviors that are currently common worldwide. Many research results show that the length of time that a person is sedentary is linked with an increased risk of obesity, diabetes, cardiovascular disease, and all-cause mortality. Determining how best to motivate people to become more active is not only necessary but also imperative. The electronic pedometer, as a proven device to increase physical activity, has been widely accepted by consumers for decades. As smartphones are functionally able to run accurate pedometer apps, we explore the potential of leveraging context-aware (e.g. location, identity, activity and time) smartphone application—more advanced pedometer—to help people mitigate sedentary lifestyle. The smartphone application we developed, “On11”, intelligently tracks people’s physical activities and identifies sedentary behaviors. With the knowledge it learns from the users, On11 provides recommendations based on users’ geographic patterns. Our study consists of four steps: (1) a pre-survey that helps us comprehend people’s views on physical activity, how people use their smartphones, and how smartphone applications may help them to be more active, (2) a large scale Twitter study (over 3 months, analyzed 929,825 running-related tweets) that determines how difficult it is for people to keep performing the most popular exercise—running, (3) a 2-week trial of our smartphone app which promotes an easier exercise—walking, and (4) a post-survey for subjects who participated in the app trial to validate if the app works as expected."
| Identifer | oai:union.ndltd.org:wpi.edu/oai:digitalcommons.wpi.edu:etd-theses-2043 |
| Date | 29 September 2014 |
| Creators | He, Qian |
| Contributors | Craig E. Wills, Department Head, Emmanuel O. Agu, Advisor, Candace L. Sidner, Reader |
| Publisher | Digital WPI |
| Source Sets | Worcester Polytechnic Institute |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Masters Theses (All Theses, All Years) |
Page generated in 0.0017 seconds