Title

Activity Sensing in the Wild: A Field Trial of UbiFit Garden.

Document Type

Article

Publication Date

4-2008

Publication Source

Proceedings of the 26th Annual ACM Conference on Human Factors in Computing Systems

Inclusive pages

1797-1806

Publisher

ACM Digital Library

Place of Publication

New York

Peer Reviewed

yes

Abstract

Recent advances in small inexpensive sensors, low-power processing, and activity modeling have enabled applications that use on-body sensing and machine learning to infer people’s activities throughout everyday life. To address the growing rate of sedentary lifestyles, we have developed a system, UbiFit Garden, which uses these technologies and a personal, mobile display to encourage physical activity. We conducted a 3-week field trial in which 12 participants used the system and report findings focusing on their experiences with the sensing and activity inference. We discuss key implications for systems that use on-body sensing and activity inference to encourage physical activity.

Disciplines

Science and Technology Studies

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