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Activity sensing in the wild: a field trial of ubifit garden
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Conference on Human Factors in Computing Systems archive
Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems table of contents
Florence, Italy
SESSION: Personal Health table of contents
Pages 1797-1806  
Year of Publication: 2008
ISBN:978-1-60558-011-1
Authors
Sunny Consolvo  Intel Research Seattle, Seattle, WA, USA
David W. McDonald  University of Washington, Seattle, USA
Tammy Toscos  Intel Resear h Seattle, Seattle, USA
Mike Y. Chen  Intel Research Seattle, Seattle, USA
Jon Froehlich  University of Washington, Seattle, USA
Beverly Harrison  Intel Research Seattle, Seattle, USA
Predrag Klasnja  Intel Research Seattle, Seattle, USA
Anthony LaMarca  Intel Research Seattle, Seattle, USA
Louis LeGrand  Intel Research Seattle, Seattle, USA
Ryan Libby  University of Washington, Seattle, USA
Ian Smith  Intel Research Seattle, Seattle, USA
James A. Landay  University of Washington, Seattle, USA
Sponsors
ACM: Association for Computing Machinery
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 59,   Downloads (12 Months): 320,   Citation Count: 18
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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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Anderson, L.H. et al., "Health Care Changes Associated with Physical Inactivity, Overweight, and Obesity," Preventing Chronic Disease, 2(4), (Oct 2005).
 
2
Bao, L. & Intille, S.S., "Activity Recognition from User-Annotated Acceleration Data," Proceedings of Pervasive '04, (May 2004), 1--17.
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Choudhury, T., et al., "The Mobile Sensing Platform: An Embedded System for Capturing and Recognizing Human Activities," To appear in IEEE Pervasive Computing: Special Issue on Activity-Based Computing (Apr-Jun 2008).
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DeJong, G., Sheppard, L., Lieber, M., & Chenoweth, D., "The Economic Cost of Physical Inactivity in Michigan," Michigan Fitness Foundation, (2003).
 
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Lester, J. Choudhury, T., & Borriello, G., "A Practical Approach to Recognizing Physical Activities," Proceedings of Pervasive '06, (2006), 1--16.
 
10
Lin, J.J., et al. "Fish'n'Steps: Encouraging Physical Activity with an Interactive Computer Game," Proceedings of UbiComp '06, (Sep 2006), 261--78.
 
11
Logan, B., et al., "A Long-Term Evaluation of Sensing Modalities for Activity Recognition," Proceedings of UbiComp '07, Innsbruck, Austria (Sep 2007).
 
12
Maitland, J., et al., "Increasing the Awareness of Daily Activity Levels with Pervasive Computing," Proceedings of Pervasive Health '06, (Nov/Dec 2006).
 
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20
Sohn, T., et al., "Mobility Detection Using Everyday GSM Traces," In Proceedings of UbiComp '06, (2006), 212--24.
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CITED BY  18

Collaborative Colleagues:
Sunny Consolvo: colleagues
David W. McDonald: colleagues
Tammy Toscos: colleagues
Mike Y. Chen: colleagues
Jon Froehlich: colleagues
Beverly Harrison: colleagues
Predrag Klasnja: colleagues
Anthony LaMarca: colleagues
Louis LeGrand: colleagues
Ryan Libby: colleagues
Ian Smith: colleagues
James A. Landay: colleagues