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Posture as a chaotic system and an application to the Parkinson’s disease

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  • Pascolo, Paolo B.
  • Marini, Alfio
  • Carniel, Roberto
  • Barazza, Fausto

Abstract

In this work we investigate and compare a number of time series of stabilograms of healthy subjects and Parkinsonians. This is carried out by means of the chaos paradigm through the preliminary computation of the first minimum of the mutual information function and the embedding dimension (using false nearest neighbours) in order to obtain the correlation dimension as well as the largest Lyapunov exponent. We show that the postural act is indeed chaotic and especially that the latter two parameters do not allow to discriminate healthy subjects from parkinsonians. Moreover we report a discrepancy of our values with those found in previous works.

Suggested Citation

  • Pascolo, Paolo B. & Marini, Alfio & Carniel, Roberto & Barazza, Fausto, 2005. "Posture as a chaotic system and an application to the Parkinson’s disease," Chaos, Solitons & Fractals, Elsevier, vol. 24(5), pages 1343-1346.
  • Handle: RePEc:eee:chsofr:v:24:y:2005:i:5:p:1343-1346
    DOI: 10.1016/j.chaos.2004.09.062
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    Cited by:

    1. Pascolo, P. & Carniel, R. & Grimaz, S., 2009. "Dynamical models of the human eye and strabismus," Chaos, Solitons & Fractals, Elsevier, vol. 41(5), pages 2463-2470.
    2. Pascolo, Paolo & Barazza, Fausto & Carniel, Roberto, 2006. "Considerations on the application of the chaos paradigm to describe the postural sway," Chaos, Solitons & Fractals, Elsevier, vol. 27(5), pages 1339-1346.
    3. Karkare, Siddharth & Saha, Goutam & Bhattacharya, Joydeep, 2009. "Investigating long-range correlation properties in EEG during complex cognitive tasks," Chaos, Solitons & Fractals, Elsevier, vol. 42(4), pages 2067-2073.
    4. Carniel, Roberto, 2008. "Diagnosing faults and illnesses with a quasi-time-invariant filter transfer function model," Chaos, Solitons & Fractals, Elsevier, vol. 35(1), pages 199-201.

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