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. 2011:2011:3636-9.
doi: 10.1109/IEMBS.2011.6090611.

Design of a wearable physical activity monitoring system using mobile phones and accelerometers

Stephen S Intille  1 , Fahd Albinali, Selene Mota, Benjamin Kuris, Pilar Botana, William L Haskell
Affiliations

Design of a wearable physical activity monitoring system using mobile phones and accelerometers

Stephen S Intille et al. Annu Int Conf IEEE Eng Med Biol Soc. 2011.

Abstract

This paper describes the motivation for, and overarching design of, an open-source hardware and software system to enable population-scale, longitudinal measurement of physical activity and sedentary behavior using common mobile phones. The "Wockets" data collection system permits researchers to collect raw motion data from participants who wear multiple small, comfortable sensors for 24 hours per day, including during sleep, and monitor data collection remotely.

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Figures

Figure 1.
Figure 1.
(Left) An Actigraph GT3X+ (red) in comparison to a Wocket. (Right) Components in a Wocket “kit” include 4 Wockets, a charger, and 4 custom moisture-wicking bands.
See this image and copyright information in PMC

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References

    1. Actigraph. (2010, October 12). Actigraph Activity Monitor Devices. Available: http://www.theactigraph.com
    1. Albinali F, Intille SS, Haskell W, and Rosenberger M, “Using wearable activity type detection to improve physical activity energy expenditure estimation,” in Proceedings of the 12th International Conference on Ubiquitous Computing ed New York: ACM Press, 2010, pp. 311–320. - PMC - PubMed
    1. Bao L and Intille SS, “Activity recognition from user-annotated acceleration data,” in Proc. of PERVASIVE. vol. LNCS 3001, Ferscha A and Mattern F, Eds., ed Berlin: Springer-Verlag, 2004, pp. 1–17.
    1. Lukowicz P, Ward JA, Junker H, Stager M, Troster G, Atrash A, and Starner T, “Recognizing workshop activity using body worn microphone and accelerometers,” in Proceedings of the International Conference in Pervasive Computing. vol. LNCS 3001, Ferscha A and Mattern F, Eds., ed, 2004, pp. 18–32.
    1. Zhang K, Werner P, Sun M, Pi-Sunyer FX, and Boozer CN, “Measurement of human daily physical activity,” Obesity Research, vol. 11, pp. 33–40, January 2003. - PubMed

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