Phone in the pocket: Pervasive self-tracking of physical activity levels

Jody Hausmann; Katarzyna Wac; Julien Bonjour

Phone in the pocket: Pervasive self-tracking of physical activity levels

Jody Hausmann^*, Katarzyna Wac, Julien Bonjour

^*Corresponding author for this work

2 Citations (Scopus)

Abstract

Mobile (smart)phones prevail in our daily life activities, and in our research we aim for it to provide pervasive services for wellness. Therefore, we assess the phone's feasibility to unobtrusively, continuously and in real-time track its user's physical activity and the resulting energy expenditure (EE). Activity Level Estimator (ALE) is an Android OS application developed for that purpose. We have assessed the accuracy of ALE against the BodyMedia SenseWear (SW) device and the gold standard for EE estimation, i.e., an indirect calorimetry (IC) method. ALE has mean accuracy of 86% (vs. SW) to 93% (vs. IC) for walking, and in 24h it underestimates EE by 23% ALE is currently used for a long-term behavioral trends study with the University of Geneva students and faculty.

Original language	English
Title of host publication	Self-Tracking and Collective Intelligence for Personal Wellness - Papers from the AAAI Spring Symposium
Number of pages	2
Volume	SS-12-05
Publication date	20 Aug 2012
Pages	17-18
ISBN (Print)	9781577355540
Publication status	Published - 20 Aug 2012
Event	2012 AAAI Spring Symposium - Stanford, CA, United States Duration: 26 Mar 2012 → 28 Mar 2012

Conference

Conference	2012 AAAI Spring Symposium
Country/Territory	United States
City	Stanford, CA
Period	26/03/2012 → 28/03/2012

Cite this

Phone in the pocket : Pervasive self-tracking of physical activity levels. / Hausmann, Jody; Wac, Katarzyna; Bonjour, Julien.

Self-Tracking and Collective Intelligence for Personal Wellness - Papers from the AAAI Spring Symposium. Vol. SS-12-05 2012. p. 17-18.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Phone in the pocket: Pervasive self-tracking of physical activity levels

Abstract

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