Abstract
In this paper the architecture and functionality of a personalized body motion sensitive training system based on auditive feedback is discussed. The system supports recognition of body motion using body worn sensors and gives the user feedback about his or her current status in adaptively selecting audio files accompanying the speed and path of exercise.
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Lukowicz, P., Anliker, U., Ward, J., Troester, G., Hirt, E., Neufelt, C.: Amon: a wearable medical computer for high risk patients. In: Wearable Computers (ISWC 2002). Proceedings of the Sixth International Symposium on Wearable Computers, pp. 133–134 (2002), ISBN: 0-7695-1816-8
Heinz, E.A., Kunze, K., Gruber, M., Bannach, D., Lukowicz, P.: Using wearable sensors for real-time recognition tasks in games of martial arts. In: Proceedings of the 2nd IEEE Symposium on Computational Intelligence and Games (CIG), pp. 98–102. IEEE Press, Los Alamitos (2006)
Lee, S.-W., Mase, K.: Recognition of walking behaviors for pedestrian navigation. In: Control Applications (CCA 2001). Proceedings of the 2001 IEEE International Conference on Control Applications, pp. 1152–1155 (2001), ISBN: 0-7803-6733-2
Lukowicz, P., Ward, J.A., Junker, H., Stäger, M., Tröster, G., Atrash, A., Starner, T.: Recognizing workshop activity using body worn microphones and accelerometers. In: Ferscha, A., Mattern, F. (eds.) PERVASIVE 2004. LNCS, vol. 3001, pp. 18–32. Springer, Heidelberg (2004)
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)
Lukowicz, P., Hanser, F., Szubski, C., Schobersberger, W.: Detecting and interpreting muscle activity with wearable force sensors. In: Fishkin, K.P., Schiele, B., Nixon, P., Quigley, A. (eds.) PERVASIVE 2006. LNCS, vol. 3968, pp. 101–116. Springer, Heidelberg (2006)
Hay, J.G.: The biomechanics of sports techniques. Prentice-Hall, Englewood Cliffs (1978), ISBN: 0-13-077164-3
Beigl, M., Krohn, A., Zimmer, T., Decker, C.: Typical sensors needed in ubiquitous and pervasive computing. In: Proceedings of the First International Workshop on Networked Sensing Systems (INSS 2004), pp. 153–158 (2004)
Jensen, K., Andersen, T.: Beat estimation on the beat. In: Applications of Signal Processing to Audio and Acoustics, 2003 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, pp. 87–90 (2003), ISBN: 0-7803-7850-4
Hainsworth, S.W.: Techniques for the automated analysis of musical audio. Signal Proscessing Group, Department of Engineering, University of Cambridge, Tech. Rep. (December 2003)
Gemperle, F., Kasabach, C., Bauer, J.S.M., Martin, R.: Design for wearability. In: ISWC 1998: Proceedings of the 2nd IEEE International Symposium on Wearable Computers, pp. 116–122. IEEE Computer Society, Los Alamitos (1998)
Estrin, D., Culler, D., Pister, K., Sukhatme, G.: Connecting the physical world with pervasive networks. IEEE Pervasive Computing 1(1), 59–69 (2002)
Dideles, M.: Bluetooth: a technical overview. Crossroads 9(4), 11–18 (2003)
Krassi, B.A.: Reliability of bluetooth. In: Proceedings of the 12th Conference on Extreme Robotics, RTC, St. Petersburg (2001)
Andersen, T.H., Andersen, K.: “Mixxx” (2009), http://www.mixxx.org/
Bringmann, B., Zimmermann, A.: Tree 2 - decision trees for tree structured data. In: Jorge, A.M., Torgo, L., Brazdil, P.B., Camacho, R., Gama, J. (eds.) PKDD 2005. LNCS (LNAI), vol. 3721, pp. 46–58. Springer, Heidelberg (2005)
Cover, T., Hart, P.: Nearest neighbor pattern classification. IEEE Transactions on Information Theory 13(1), 21–27 (1967)
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Hoelzl, G. (2010). A Personalised Body Motion Sensitive Training System Based on Auditive Feedback. In: Phan, T., Montanari, R., Zerfos, P. (eds) Mobile Computing, Applications, and Services. MobiCASE 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 35. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12607-9_2
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DOI: https://doi.org/10.1007/978-3-642-12607-9_2
Publisher Name: Springer, Berlin, Heidelberg
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