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Annals of Computer Science and Information Systems, Volume 9

Position Papers of the 2016 Federated Conference on Computer Science and Information Systems

Balance recognition on the basis of EEG measurement.

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DOI: http://dx.doi.org/10.15439/2016F561

Citation: Position Papers of the 2016 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 9, pages 241244 ()

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Abstract. Although electroencephalography (EEG) is not typically used for verifying the sense of balance, it can be used for analysing cortical signals responsible for this phenomenon. Simple balance tasks can be proposed as a good indicator of whether the sense of balance is acting more or less actively. This article presents preliminary results for the potential of using EEG to balance sensing. The results are not unequivocal and further research is required.

References

  1. S. Chaudhuri, H. Thompson, and G. Demiris, “Fall Detection Devices and their Use with Older Adults: A Systematic Review”, J Geriatr Phys Ther. 2014; 37(4): 178–196
  2. M. Kaczmarek, A. Bujnowski, J. Wtorek, A. Polinski, “Multimodal Platform for Continuous Monitoring of the Elderly and Disabled”, Journal of Medical Imaging and Health Informatics, Volume 2, Number 1, March 2012, pp. 56-63(8)
  3. Y. Yi F. Tse, J. S. Petrofsky, L. Berk, N. Daher, E. Lohman, M. S. Laymon, P. Cavalcanti, “Postural sway and rhythmic electroencephalography analysis of cortical activation during eight balance training tasks”, “Med. Sci. Monitor”, 2013; 19:175-186
  4. Y. Ouchi, H. Okada, E. Yoshikawa, S. Nobezawa, M. Futatsubashi, Brain activation during maintenance of standing postures in humans. J Neurol, 1999; 122 (Pt 2): 329–38
  5. S. Dejardin, The clinical investigation of static and dynamic balance, B-ENT, 2008, 4, Suppl. 8, 29-36
  6. A. V. Oppenheim, G. C. Verghese, “Introduction to Communication, Control, and Signal Processing”, Ch10, 2010
  7. http://www.biosemi.com/
  8. R. E. Challis, R. I. Kitney, Biomedical signal processing (in four parts). Part 3. The power spectrum and coherence function, Med Biol Eng Comput. 1991 May; 29(3):225-41