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

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

Standard

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

Harvard

Hausmann, J, Wac, K & Bonjour, J 2012, Phone in the pocket: Pervasive self-tracking of physical activity levels. in Self-Tracking and Collective Intelligence for Personal Wellness - Papers from the AAAI Spring Symposium. vol. SS-12-05, pp. 17-18, 2012 AAAI Spring Symposium, Stanford, CA, United States, 26/03/2012.

APA

Hausmann, J., Wac, K., & Bonjour, J. (2012). Phone in the pocket: Pervasive self-tracking of physical activity levels. In Self-Tracking and Collective Intelligence for Personal Wellness - Papers from the AAAI Spring Symposium (Vol. SS-12-05, pp. 17-18)

Vancouver

Hausmann J, Wac K, Bonjour J. Phone in the pocket: Pervasive self-tracking of physical activity levels. In Self-Tracking and Collective Intelligence for Personal Wellness - Papers from the AAAI Spring Symposium. Vol. SS-12-05. 2012. p. 17-18

Author

Hausmann, Jody ; Wac, Katarzyna ; Bonjour, Julien. / Phone in the pocket : Pervasive self-tracking of physical activity levels. Self-Tracking and Collective Intelligence for Personal Wellness - Papers from the AAAI Spring Symposium. Vol. SS-12-05 2012. pp. 17-18

Bibtex

@inproceedings{8fd2b2c00b2b4f949a1011fdb581d49b,
title = "Phone in the pocket: Pervasive self-tracking of physical activity levels",
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.",
author = "Jody Hausmann and Katarzyna Wac and Julien Bonjour",
year = "2012",
month = aug,
day = "20",
language = "English",
isbn = "9781577355540",
volume = "SS-12-05",
pages = "17--18",
booktitle = "Self-Tracking and Collective Intelligence for Personal Wellness - Papers from the AAAI Spring Symposium",
note = "2012 AAAI Spring Symposium ; Conference date: 26-03-2012 Through 28-03-2012",

}

RIS

TY - GEN

T1 - Phone in the pocket

T2 - 2012 AAAI Spring Symposium

AU - Hausmann, Jody

AU - Wac, Katarzyna

AU - Bonjour, Julien

PY - 2012/8/20

Y1 - 2012/8/20

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84864965182&partnerID=8YFLogxK

M3 - Article in proceedings

AN - SCOPUS:84864965182

SN - 9781577355540

VL - SS-12-05

SP - 17

EP - 18

BT - Self-Tracking and Collective Intelligence for Personal Wellness - Papers from the AAAI Spring Symposium

Y2 - 26 March 2012 through 28 March 2012

ER -

ID: 203870931