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Analyzing Accelerometer Data for Epilepsy Episode Recognition

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10th International Conference on Soft Computing Models in Industrial and Environmental Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 368))

Abstract

Epilepsy is one of the main neurological disorders with high impact in the patient’s everyday life. An incorrect treatment or a lack in monitoring might produce cognitive damage and depression. Therefore, developing a wearable device for epilepsy monitoring would eventually complete the anamnesis, enhancing the medical staff diagnosing and treatment setting. This study shows the preliminary results in epilepsy onset recognition based on wearable tri-axial accelerometers and simple fuzzy set learnt using genetic algorithms. A complete experimentation for learning the fuzzy set is detailed. According to the obtained results, some generalized feasible solutions are discussed. Results show a very interesting researching area that might be easily transferred to embedded devices and online health care systems.

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Acknowledgments

This research has been funded by the Spanish Ministry of Science and Innovation, under projects TIN2011-24302 and TIN2014-56967-R, Fundación Universidad de Oviedo project FUO-EM-340-13, Junta de Castilla y León projects BIO/BU09/14 and SACYL 2013 GRS/822/A/13.

Author information

Authors and Affiliations

  1. Computer Science Department, University of Oviedo, Oviedo, Spain

    José R. Villar & Enrique de la Cal

  2. Morphology and Cellular Biology Department, Oviedo, Spain

    Manuel Menéndez

  3. Instituto Tec. de Castilla Y León, Burgos, Spain

    Javier Sedano

  4. Electrical Engineering Department, University of Oviedo, Oviedo, Spain

    Víctor M. González

Authors
  1. José R. Villar
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  2. Manuel Menéndez
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  3. Javier Sedano
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  4. Enrique de la Cal
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  5. Víctor M. González
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Corresponding author

Correspondence to José R. Villar .

Editor information

Editors and Affiliations

  1. Department of Civil Engineering, University of Burgos, Burgos, Spain

    Álvaro Herrero

  2. C/ López Bravo 70, Pol. Ind. Villalonquejar, Technological Institute of Castilla y León, Burgos, Spain

    Javier Sedano

  3. Department of Civil Engineering, University of Burgos, Burgos, Spain

    Bruno Baruque

  4. University of Salamanca, Salamanca, Spain

    Héctor Quintián

  5. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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© 2015 Springer International Publishing Switzerland

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Villar, J.R., Menéndez, M., Sedano, J., de la Cal, E., González, V.M. (2015). Analyzing Accelerometer Data for Epilepsy Episode Recognition. In: Herrero, Á., Sedano, J., Baruque, B., Quintián, H., Corchado, E. (eds) 10th International Conference on Soft Computing Models in Industrial and Environmental Applications. Advances in Intelligent Systems and Computing, vol 368. Springer, Cham. https://doi.org/10.1007/978-3-319-19719-7_4

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  • DOI: https://doi.org/10.1007/978-3-319-19719-7_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19718-0

  • Online ISBN: 978-3-319-19719-7

  • eBook Packages: EngineeringEngineering (R0)

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