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International Conference on Artificial Intelligence and Soft Computing

ICAISC 2015: Artificial Intelligence and Soft Computing pp 142–150Cite as

Mobile Fuzzy System for Detecting Loss of Consciousness and Epileptic Seizure

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9120))

Abstract

A framework for detecting loss of consciousness and epilepsy attack based on a neuro-fuzzy system embedded in an accelerometer built-in mobile phone is presented. Additional filtering algorithms protect the system against excessive energy consumption. The system has the ability to monitor and control daily user behaviour as well as to react to situations that can be life or health threatening, with a self-learning mechanism that can adjust to motility of human movement. Moreover, an advantage of our system, is a function of quick contact with appropriate services or relatives, by sending health state and location data regarding the person, in case the user loses consciousness or has an epilepsy seizure.

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References

  1. Bruzdzinski, T., Krzyzak, A., Fevens, T., Jelen, Ł.: Web based framework for breast cancer classification. Journal of Artificial Intelligence and Soft Computing Research 4(2), 149–162 (2014)

    Article  Google Scholar 

  2. Hoang, T., Choi, D., Nguyen, T.: Gait authentication on mobile phone using biometric cryptosystem and fuzzy commitment scheme. International Journal of Information Security, 1–12 (2015)

    Google Scholar 

  3. Huynh, Q.T., Nguyen, U.D., Tran, S.V., Nabili, A., Tran, B.Q.: Fall detection system using combination accelerometer and gyroscope. International Journal of Advancements in Electronics and Electrical Engineering 3(1), 15–19 (2014)

    Google Scholar 

  4. International Diabetes Federation: Idf diabetes atlas sixth edition poster update (2014) (accessed March 26, 2015)

    Google Scholar 

  5. Karimi, B., Krzyzak, A.: A novel approach for automatic detection and classification of suspicious lesions in breast ultrasound images. Journal of Artificial Intelligence and Soft Computing Research 3(4), 265–276 (2013)

    Article  Google Scholar 

  6. Kazi, S.B., Sikander, S., Yousafzai, S., Mazhar, S.: Fall detection using single tri-axial accelerometer. In: ASEE 2014 Zone I Conference (2014)

    Google Scholar 

  7. Klapuri, J.: Epileptic Seizure Detection Using a Wrist-Worn Triaxial Accelerometer. University of Helsinki (2013)

    Google Scholar 

  8. Korytkowski, M., Nowicki, R., Scherer, R.: Neuro-fuzzy rough classifier ensemble. In: Alippi, C., Polycarpou, M., Panayiotou, C., Ellinas, G. (eds.) ICANN 2009, Part I. LNCS, vol. 5768, pp. 817–823. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  9. Koshiyama, A.S., Vellasco, M.M.B.R., Tanscheit, R.: Gpfis-control: A genetic fuzzy system for control tasks. Journal of Artificial Intelligence and Soft Computing Research 4(3), 167–179 (2014)

    Article  Google Scholar 

  10. Kwapisz, J.R., Weiss, G.M., Moore, S.A.: Activity recognition using cell phone accelerometers. ACM SigKDD Explorations Newsletter 12(2), 74–82 (2011)

    Article  Google Scholar 

  11. Marquardt, P., Verma, A., Carter, H., Traynor, P.: (sp) iphone: decoding vibrations from nearby keyboards using mobile phone accelerometers. In: Proceedings of the 18th ACM Conference on Computer and Communications Security, pp. 551–562. ACM (2011)

    Google Scholar 

  12. Nowicki, R., Rutkowska, D.: New neuro–fuzzy architectures. In: Proceedings of International Conference on Artificial and Computational Intelligence for Decision, Control and Automation in Engineering and Industrial Applications, AcIDcA 2000, Monastir, Tunisia, pp. 82–87 (March 2000)

    Google Scholar 

  13. Ravi, N., Dandekar, N., Mysore, P., Littman, M.L.: Activity recognition from accelerometer data. In: AAAI, vol. 5, pp. 1541–1546 (2005)

    Google Scholar 

  14. Rigatos, G.G., Siano, P.: Flatness-based adaptive fuzzy control of spark-ignited engines. Journal of Artificial Intelligence and Soft Computing Research 4(4), 231–242 (2014)

    Article  Google Scholar 

  15. Rutkowska, D.: Neuro-fuzzy architectures and hybrid learning, vol. 85. Springer Science & Business Media (2002)

    Google Scholar 

  16. Rutkowski, L.: Computational Intelligence Methods and Techniques. Springer, Heidelberg (2008)

    Book  MATH  Google Scholar 

  17. Scherer, R.: Neuro-fuzzy relational systems for nonlinear approximation and prediction. Nonlinear Analysis 71, e1420–e1425 (2009)

    Google Scholar 

  18. Scherer, R., Rutkowski, L.: Neuro-fuzzy relational classifiers. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds.) ICAISC 2004. LNCS (LNAI), vol. 3070, pp. 376–380. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  19. Sun, L., Zhang, D., Li, B., Guo, B., Li, S.: Activity recognition on an accelerometer embedded mobile phone with varying positions and orientations. In: Yu, Z., Liscano, R., Chen, G., Zhang, D., Zhou, X. (eds.) UIC 2010. LNCS, vol. 6406, pp. 548–562. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  20. Szarek, A., Korytkowski, M., Rutkowski, L., Scherer, R., Szyprowski, J.: Application of neural networks in assessing changes around implant after total hip arthroplasty. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2012, Part II. LNCS, vol. 7268, pp. 335–340. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  21. Szarek, A., Korytkowski, M., Rutkowski, L., Scherer, R., Szyprowski, J.: Forecasting wear of head and acetabulum in hip joint implant. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2012, Part II. LNCS, vol. 7268, pp. 341–346. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  22. World Health Organization: Media centre - epilepsy (2012) (accessed March 26, 2015)

    Google Scholar 

  23. Zhao, W., Lun, R., Espy, D.D., Reinthal, M.A.: Realtime motion assessment for rehabilitation exercises: Integration of kinematic modeling with fuzzy inference. Journal of Artificial Intelligence and Soft Computing Research 4(4), 267–285 (2014)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Institute of Computational Intelligence, Częstochowa University of Technology, Al. Armii Krajowej 36, 42-200, Częstochowa, Poland

    Paweł Staszewski & Piotr Woldan

  2. Computer Science Department, University of Geneva, 7 Route de Drize, Geneva, Switzerland

    Sohrab Ferdowsi

Authors
  1. Paweł Staszewski
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  2. Piotr Woldan
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  3. Sohrab Ferdowsi
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Corresponding author

Correspondence to Paweł Staszewski .

Editor information

Editors and Affiliations

  1. Czestochowa University of Technology, Czestochowa, Poland

    Leszek Rutkowski

  2. Czestochowa University of Technology, Czestochowa, Poland

    Marcin Korytkowski

  3. Czestochova Univ of Technology, Częstochova, Poland

    Rafal Scherer

  4. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. Louisville, Kentucky, USA

    Jacek M. Zurada

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© 2015 Springer International Publishing Switzerland

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Staszewski, P., Woldan, P., Ferdowsi, S. (2015). Mobile Fuzzy System for Detecting Loss of Consciousness and Epileptic Seizure. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2015. Lecture Notes in Computer Science(), vol 9120. Springer, Cham. https://doi.org/10.1007/978-3-319-19369-4_14

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  • DOI: https://doi.org/10.1007/978-3-319-19369-4_14

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19368-7

  • Online ISBN: 978-3-319-19369-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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