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Journal of Neurology

, Volume 259, Issue 1, pp 182–184 | Cite as

Artificial neural network posturography detects the transition of vestibular neuritis to phobic postural vertigo

  • Thomas Brandt
  • Michael Strupp
  • Sergey Novozhilov
  • Siegbert Krafczyk
Letter to the Editors

Dear Sirs,

Artificial neural networks (ANNW), described in detail by Duda et al. [1], can be efficiently used to master complex data sets by applying computational analysis for routine clinical uses, for example, to classify the risk of falls in the elderly on the basis of an analysis of balance control during gait [2]. In an earlier study we used ANNW posturography to identify typical postural sway patterns that allow the diagnosis of various balance disorders [3]. Body sway was measured by means of posturography during ten test conditions of increasing difficulty. These included standing with eyes open or eyes closed, with head extended backward, standing on a slab of foam rubber, and tandem stance. Sixteen values were selected from the calculated parameters of each single condition, such as sway path, root mean square values, and Fourier analysis. This means that a total of 160 values were entered into the artificial neural network (for methods, see [3]). In this way a standard...

Keywords

Vestibular Disorder Vestibular Neuritis Retinal Slip Horizontal Semicircular Canal Caloric Irrigation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The authors thank Judy Benson for copyediting the manuscript. The study was supported by the a BMBF grant (no. 01EO0901) to the IFBLMU and by the Hertie Foundation.

Conflict of interest

None.

References

  1. 1.
    Duda RO, Hart PE, Stork DG (2001) Pattern classification. Wiley, New YorkGoogle Scholar
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    Hahn ME, Chou LS (2005) A model for detecting balance impairment and estimating falls risk in the elderly. Ann Biomed Eng 33:811–820PubMedCrossRefGoogle Scholar
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    Krafczyk S, Tietze S, Swoboda W, Valkovic P, Brandt T (2006) Artificial neural network: a new diagnostic posturographic tool for disorders of stance. Clin Neurophysiol 117:1692–1698PubMedCrossRefGoogle Scholar
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    Brandt T (1996) Phobic postural vertigo. Neurology 46:1515–1519PubMedGoogle Scholar
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    Halmagyi GM, Curthoys IS (1988) A clinical sign of canal paresis. Arch Neurol 45:737–738PubMedCrossRefGoogle Scholar
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    Huppert D, Kunihiro T, Brandt T (1995) Phobic postural vertigo (154 patients): its association with vestibular disorders. J Audiol 4:97–103Google Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Thomas Brandt
    • 1
  • Michael Strupp
    • 2
  • Sergey Novozhilov
    • 3
  • Siegbert Krafczyk
    • 2
  1. 1.Institute for Clinical Neurosciences and Integrated Research and Treatment Center for Vertigo, Balance and Ocular Motor Disorders (IFBLMU)Ludwig Maximilian UniversityMunichGermany
  2. 2.Department of Neurology and Integrated Research and Treatment Center for Vertigo, Balance and Ocular Motor Disorders (IFBLMU)Ludwig Maximilian UniversityMunichGermany
  3. 3.Integrated Research and Treatment Center for Vertigo, Balance and Ocular Motor Disorders (IFBLMU)Ludwig Maximilian UniversityMunichGermany

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