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Simple classification of walking activities using commodity smart phones

Published:23 November 2009Publication History

ABSTRACT

People interact with mobile computing devices everywhere, while sitting, walking, running or even driving. Adapting the interface to suit these contexts is important, thus this paper proposes a simple human activity classification system. Our approach uses a vector magnitude recognition technique to detect and classify when a person is stationary (or not walking), casually walking, or jogging, without any prior training. The user study has confirmed the accuracy.

References

  1. Ainsworth, B., Haskell, W., Whitt, M., Irwin, M., Swartz, A., Strath, S., et al. (2000). Compendium of physical activities: classification of energy costs of human physical activities. Medicine & Science in Sports & Exercise, 32 (9), 498--516.Google ScholarGoogle Scholar
  2. Bao, L., & Intille, S. S. (2004). Activity recognition from user-annotated acceleration data. Proceedings of Pervasive 2004: the Second International Conference on Pervasive Computing (pp. 1--17). Vienna, Austria: Springer.Google ScholarGoogle ScholarCross RefCross Ref
  3. Franke, T. (2008). Context Logger. Retrieved March 4, 2009, from http://contextlogger.blogspot.com/Google ScholarGoogle Scholar
  4. Lester, J., Hurvitz, P., Chaudhri, R., Hartung, C., & Borriello, G. (2008). MobileSense - sensing modes of transportation in studies of the built environment. UrbanSense08, (pp. 46--50). Raleigh, North Carolina.Google ScholarGoogle Scholar
  5. Saponas, T., Lester, J., Froehlich, J., Fogarty, J., & Landay, J. (2008). iLearn on the iPhone: Real-Time Human Activity Classification on Commodity Mobile Phones. UW-CSE-08-04-02 Tech Report.Google ScholarGoogle Scholar
  6. Ravi, N., Dandekar, N., Preetham, M., & Littman, M. (2005). Activity recognition from accelerometer data. IAAI-05 (pp. 1541--1546). America: AAAI. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Yi, J., Choi, Y., Jacko, J., & Sears, A. (2005). Context awareness via a single device-attached accelerometer during mobile computing. MobileHCI'05 (pp. 303--306). ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library

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        cover image ACM Other conferences
        OZCHI '09: Proceedings of the 21st Annual Conference of the Australian Computer-Human Interaction Special Interest Group: Design: Open 24/7
        November 2009
        445 pages
        ISBN:9781605588544
        DOI:10.1145/1738826

        Copyright © 2009 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 23 November 2009

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        Acceptance Rates

        OZCHI '09 Paper Acceptance Rate32of60submissions,53%Overall Acceptance Rate362of729submissions,50%

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