Comparing Features Extraction Techniques Using J48 for Activity Recognition on Mobile Phones

  • Gonzalo Blázquez Gil
  • Antonio Berlanga de Jesús
  • José M. Molina Lopéz
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 151)

Abstract

Nowadays, mobile phones are not only used for mere communication such as calling or sending text messages. Mobile phones are becoming the main computer device in people’s lives. Besides, thanks to the embedded sensors (Accelerometer, digital compass, gyroscope, GPS, and so on) is possible to improve the user experience. Activity recognition aims to recognize actions and goals of individual from a series of observations of themselves, in this case is used an accelerometer.

Keywords

Mobile device Activity Recognition Ambient Assisted Living J48 features extraction 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bao, L., Intille, S.S.: Activity Recognition from User-Annotated Acceleration Data. In: Ferscha, A., Mattern, F. (eds.) PERVASIVE 2004. LNCS, vol. 3001, pp. 1–17. Springer, Heidelberg (2004), http://www.springerlink.com/index/9AQFLYK4F47KHYJD.pdf CrossRefGoogle Scholar
  2. 2.
    Barralon, P., Vuillerme, N., Noury, N.: Walk detection with a kinematic sensor: frequency and wavelet comparison. In: Conference Proceedings:... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, vol. 1, pp. 1711–1714 (2006), http://www.ncbi.nlm.nih.gov/pubmed/17945661, doi10.1109/IEMBS.2006.260770
  3. 3.
    Blázquez, G., Berlanga, A., Molina, J.: Incontex to: A fusion architecture to obtain mobile context. In: 2011 Proceedings of the 14th International Conference on Information Fusion (FUSION), pp. 1–8. IEEE (2011)Google Scholar
  4. 4.
    Chon, J.: LifeMap: Smartphone-based Context Provider for Location-based Services. IEEE Pervasive Computing, 1–7 (November 13, 2011), http://www.computer.org/portal/web/csdl/doi/10.1109/MPRV
  5. 5.
    Eagle, N., Pentland, A.: Reality mining: sensing complex social systems. Personal and Ubiquitous Computing 10(4), 255–268 (2006)CrossRefGoogle Scholar
  6. 6.
    Ganti, R., Srinivasan, S., Gacic, A.: Multisensor Fusion in Smartphones for Lifestyle Monitoring. In: 2010 International Conference on Body Sensor Networks (BSN), pp. 36–43. IEEE (2010)Google Scholar
  7. 7.
    Henriksen, M., Lund, H., Moe-Nilssen, R., Bliddal, H., Danneskiod-Samsoe, B.: Test-retest reliability of trunk accelerometric gait analysis. Gait & Posture 19(3), 288–297 (2004)CrossRefGoogle Scholar
  8. 8.
    Korpipaa, P., Mantyjarvi, J., Kela, J., Keranen, H., Malm, E.: Managing context information in mobile devices. IEEE Pervasive Computing 2(3), 42–51 (2003)CrossRefGoogle Scholar
  9. 9.
    Krishnan, N., Juillard, C., Colbry, D., Panchanathan, S.: Recognition of hand movements using wearable accelerometers. Journal of Ambient Intelligence and Smart Environments 1(2), 143–155 (2009)Google Scholar
  10. 10.
    Lester, J., Choudhury, T., Borriello, G.: A practical approach to recognizing physical activities, pp. 1–16 (2006)Google Scholar
  11. 11.
    Liao, L.: Location-based activity recognition. Ph.D. thesis, Citeseer (2006)Google Scholar
  12. 12.
    Miluzzo, E., Lane, N., Fodor, K., Peterson, R., Lu, H., Musolesi, M., Eisenman, S., Zheng, X., Campbell, A.: Sensing meets mobile social networks: the design, implementation and evaluation of the cenceme application. In: Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems, pp. 337–350. ACM (2008)Google Scholar
  13. 13.
    Shadbolt, N.: Ambient intelligence. IEEE Intelligent Systems 18, 2–3 (2003)CrossRefGoogle Scholar
  14. 14.
    Verhagen, C.: Some general remarks about pattern recognition; its definition; its relation with other disciplines; a literature survey. Pattern Recognition 7(3), 109–116 (1975)MATHCrossRefGoogle Scholar
  15. 15.
    Want, R.: You are your cell phone. Pervasive Computing, IEEE 7(2), 2–4 (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Gonzalo Blázquez Gil
    • 1
  • Antonio Berlanga de Jesús
    • 1
  • José M. Molina Lopéz
    • 1
  1. 1.Applied Artificial Intelligence GroupUniversidad Carlos III de MadridMadridSpain

Personalised recommendations