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Human Activity Recognition from Accelerometer Data Using a Wearable Device

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Pattern Recognition and Image Analysis (IbPRIA 2011)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6669))

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Abstract

Activity Recognition is an emerging field of research, born from the larger fields of ubiquitous computing, context-aware computing and multimedia. Recently, recognizing everyday life activities becomes one of the challenges for pervasive computing. In our work, we developed a novel wearable system easy to use and comfortable to bring. Our wearable system is based on a new set of 20 computationally efficient features and the Random Forest classifier. We obtain very encouraging results with classification accuracy of human activities recognition of up to 94%.

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References

  1. Ravi, N., Nikhil, D., Mysore, P., Littman, M.L.: Activity recognition from accelerometer data. In: IAAI, pp. 1541–1546 (2005)

    Google Scholar 

  2. Bao, L., Intille, S.S.: Activity recognition from user-annotated acceleration data, pp. 1–17. Springer, Heidelberg (2004)

    Google Scholar 

  3. Choudhury, T., Lamarca, A., Legr, L., Rahimi, A., Rea, A., Borriello, G., Hemingway, B., Koscher, K., Lester, J., Wyatt, D., Haehnel, D.: The Mobile Sensing Platform: An Embedded Activity Recognition System. IEEE Pervasive Computing 7, 32–41 (2008)

    Article  Google Scholar 

  4. Lester, J., Choudhury, T., Borriello, G.: A practical approach to recognizing physical activities. In: Fishkin, K.P., Schiele, B., Nixon, P., Quigley, A. (eds.) PERVASIVE 2006. LNCS, vol. 3968, pp. 1–16. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  5. Mannini, A., Sabatini, A.M.: Machine Learning Methods for Classifying Human Physical Activities from on-body sensors. Sensors 10, 1154–1175 (2010)

    Article  Google Scholar 

  6. Breiman, L.: Random Forests. Machine Learning 45(1), 5–32 (2001)

    Article  MATH  Google Scholar 

  7. Krause, A., Siewiorek, D., Smailagic, A., Farrigdon, J.: Unsupervised, dynamic identification of Physiological and Activity Context in Wearable Computing. In: Fensel, D., Sycara, K., Mylopoulos, J. (eds.) ISWC 2003. LNCS, vol. 2870. Springer, Heidelberg (2003)

    Google Scholar 

  8. Huynh, T., Fritz, M., Schiele, B.: Discovery of Activity Patterns using Topic Models. In: UbiComp 2008, pp. 10–19 (2008)

    Google Scholar 

  9. Clarkson, B., Pentland, A.: Unsupervised Clustering of ambulatory audio and video. In: ICASSP 1999, pp. 3037–3040 (1999)

    Google Scholar 

  10. Casale, P., Pujol, O., Radeva, P.: Face-to-Face Social Activity Detection Using Data Collected with a Wearable Device. In: Araujo, H., Mendonça, A.M., Pinho, A.J., Torres, M.I. (eds.) IbPRIA 2009. LNCS, vol. 5524, pp. 56–63. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

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Author information

Authors and Affiliations

  1. Computer Vision Center, Bellaterra, Barcelona, Spain

    Pierluigi Casale, Oriol Pujol & Petia Radeva

  2. Dept. of Applied Mathematics and Analysis, University of Barcelona, Barcelona, Spain

    Pierluigi Casale, Oriol Pujol & Petia Radeva

Authors
  1. Pierluigi Casale
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  2. Oriol Pujol
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  3. Petia Radeva
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Editor information

Editors and Affiliations

  1. Departament de Matemàtica Aplicada i Anàlisi, Universitat de Barcelona, Facultat de Matemàtiques, Gran Via de les Corts Catalanes 585, 08007, Barcelona, Spain

    Jordi Vitrià

  2. Instituto de Sistemas e Robótica / Instituto Superior Técnico, Av. Rovisco Pais, 1, 1049-001, Lisbon, Portugal

    João Miguel Sanches

  3. Institute for Intelligent Systems and Numerical Applications in Engineering (SIANI), Edificio de Informática y Matemáticas, University of Las Palmas de Gran Canaria, Campus Universitario de Tafira, 35017, Las Palmas, Spain

    Mario Hernández

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© 2011 Springer-Verlag Berlin Heidelberg

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Casale, P., Pujol, O., Radeva, P. (2011). Human Activity Recognition from Accelerometer Data Using a Wearable Device. In: Vitrià, J., Sanches, J.M., Hernández, M. (eds) Pattern Recognition and Image Analysis. IbPRIA 2011. Lecture Notes in Computer Science, vol 6669. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21257-4_36

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  • DOI: https://doi.org/10.1007/978-3-642-21257-4_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21256-7

  • Online ISBN: 978-3-642-21257-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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