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Features of parkinsonian and essential tremor of the human hand

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Abstract

Using spectral, wavelet, multifractal, and recurrence analyses we examined the features of involuntary shaking (tremor) that occur during the performance of a given motor task. The task was to maintain the efforts of fingers under isometric conditions by a healthy subject, a patient with primary bilateral parkinsonism, and a patient with essential tremor syndrome. The physiological tremor was characterized by the lowest amplitude, a broad power spectrum, the lowest energy of the wavelet spectrum, the highest degree of multifractality, the lowest degree of determinism, and the highest entropy of the recurrence time density. In the case of the essential tremor we observed a significant enhancement of the wavelet spectrum energy and a decrease of the oscillation complexity. This was evident via the occurrence of clear peaks in the power spectra, a decrease in the degree of multifractality, the emergence of a quasi-periodic structure in the recurrence diagrams, an increase in determinism and a decrease of the entropy of recurrence time density. All these trends were increased for the parkinsonian tremor data. These characteristics enable us to quantitatively estimate the degree of deviation of motor function from the healthy case.

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References

  1. McAuley, J.H. and Marsden, C.D., Physiological and pathological tremors and rhythmic central motor control, Brain, 2000, vol. 123, no. 8, p. 1545.

    Article  PubMed  Google Scholar 

  2. Elble, R.J., Characteristics of physiologic tremor in young and elderly adults, J. Clin. Neurophysiol., 2003, vol. 114, no. 4, p. 624.

    Article  Google Scholar 

  3. Raethjen, J., Pawlas, F., Lindemann, M., et al., Determinants of physiologic tremor in a large normal population, J. Clin. Neurophysiol., 2000, vol. 111, no. 10, p. 1825.

    Article  CAS  Google Scholar 

  4. Pavlov, A.N., Tupitsyn, A.N., Legros, A., et al., Using wavelet analysis to detect the influence of low frequency magnetic fields on human physiological tremor, Physiol. Meas., 2007, vol. 28, no. 3, p. 321.

    Article  CAS  PubMed  Google Scholar 

  5. Shtok, V.N., Levin, O.S., and Fedorova, N.V., Diagnostika i lechenie ekstrapiramidnykh rasstroistv (Diagnosis and Treatment of Extrapyramidal Disorders), Moscow: MIA, 2002.

    Google Scholar 

  6. Golubev, V.L. and Magomedova, R.K., The spectral analysis of the variability of frequency and amplitude characteristics of tremor in patients with essential tremor and tremulous form of Parkinson’s disease, Zh. Nevrol. Psikhiat. im. S.S. Korsakova, 2006, vol. 106, no. 1, p. 43.

    CAS  Google Scholar 

  7. Gresty, M. and Buckwell, D., Spectral analysis of tremor: Understanding the results, J. Neurol. Neurosurg. Psychiat., 1990, vol. 53, no. 11, p. 976.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Elble R.J. Essential tremor frequency decreases with time, Neurology, 2000, vol. 55, no. 10, p. 1547.

    Article  CAS  PubMed  Google Scholar 

  9. Hellwig, B., Mund, P., Schelter, B., et al., A longitudinal study of tremor frequencies in parkinson’s disease and essential tremor, Clin. Neurophysiol., 2009, vol. 120, p. 431.

    Article  CAS  PubMed  Google Scholar 

  10. Growdon, W., Ghika, J., and Henderson, J., Effects of proximal and distal muscles’ groups contraction and mental stress on the amplitude and frequency of physiological finger tremor. An accelerometric study, Electromyogr. Clin. Neurophysiol., 2000, vol. 40, no. 5, p. 295.

    CAS  PubMed  Google Scholar 

  11. Dick, O.E., Romanov, S.P., and Nozdrachev, A.D., Energy and fractal characteristics of physiological and pathological tremors of the human hand, Hum. Physiol., 2010, vol. 36, no. 2, p. 203.

    Article  Google Scholar 

  12. Dick, O.E. and Nozdrachev, A.D., Nonlinear dynamics of involuntary shaking of the human hand under motor dysfunction, Hum. Physiol., 2015, vol. 41, no. 2, p. 156.

    Article  Google Scholar 

  13. Eckmann, J.P., Kamphorst, S., and Ruelle, D., Recurrence plots of dynamical systems, Europhys. Lett., 1987, vol. 4, no. 9, p. 973.

    Article  Google Scholar 

  14. Marwan, N., Romano, M.C., Thiel, M., et al., Recurrence plots for the analysis of complex systems, Phys. Rep., 2007, vol. 438, p. 237.

    Article  Google Scholar 

  15. Muzy, J.F., Bacry, E., and Arneodo, A., Multifractal formalism for fractal signals: The structure-function approach versus the wavelet-transform modulus-maxima method, Phys. Rev. E, 1993, vol. 47, p. 875.

    Article  Google Scholar 

  16. Pavlov, A.N. and Anishchenko, V.S., Multifractal analysis of complex signals, Phys.-Usp., 2007, vol. 50, no. 8, p. 819.

    Article  Google Scholar 

  17. Gao, J.B., Recurrence time statistics for chaotic systems and their applications, Phys. Rev. Lett., 1999, vol. 83, p. 3178.

    Article  CAS  Google Scholar 

  18. Little, M.A., McSharry, P.E., Roberts, S.J., et al., Exploiting nonlinear recurrence and fractal scaling properties for voice disorder detection, BioMed. Eng. Online, 2007, vol. 6, p. 23.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Bedrov, Y.A., Dick, O.E., and Romanov, S.P., Role of signal-dependent noise during maintenance of isometric force, BioSystems, 2007, vol. 89, nos. 1–3, p. 50.

    Article  CAS  PubMed  Google Scholar 

  20. Dick, O.E. and Svyatogor, I.A., Potentialities of the wavelet and multifractal techniques to evaluate changes in the functional state of the human brain, Neurocomput. J., 2012, vol. 82, p. 207.

    Article  Google Scholar 

  21. Derguzov, A.V., Makhortykh, S.A., and Semechkin, R.A., Complex diagnosis of Parkinson decease by means of magnetic encephalography, 2000 Issled. Ross. http://zhurnal.ape.relarn.ru/articles/2006/065.pdf

    Google Scholar 

  22. Anninos, P.A., Adamopoulos, A.V., Kotini, A., et al., Nonlinear analysis of brain activity in magnetic influenced Parkinson patients, Brain Topogr., 2000, vol. 13, no. 2, p. 135.

    Article  CAS  PubMed  Google Scholar 

  23. Müller, V., Lutzenberger, W., Preisl, H., et al., Complexity of visual stimuli and non-linear EEG dynamics in humans, Cognit. Brain Res., 2003, vol. 16, p. 104.

    Article  Google Scholar 

  24. Brittain, J.S., Cagnan, H., Mehta, A.R., et al., Distinguishing the central drive to tremor in Parkinson’s disease and essential tremor, J. Neurosci., 2015, vol. 35, no. 2, p. 795.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Stam, C.J., Nonlinear dynamical analysis of EEG and MEG: Review of an emerging field, Clin. Neurophysiol., 2005, vol. 116, no. 10, p. 2266.

    Article  CAS  PubMed  Google Scholar 

  26. Stam, C.J. and de Bruin, E.A., Scale-free dynamics of global functional connectivity in the human brain, Hum. Brain Mapp., 2004, vol. 22, no. 2, p. 97.

    Article  PubMed  Google Scholar 

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Correspondence to A. D. Nozdrachev.

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Original Russian Text © O.E. Dick, A.D. Nozdrachev, 2016, published in Fiziologiya Cheloveka, 2016, Vol. 42, No. 3, pp. 47–55.

The article was translated by the authors.

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Dick, O.E., Nozdrachev, A.D. Features of parkinsonian and essential tremor of the human hand. Hum Physiol 42, 271–278 (2016). https://doi.org/10.1134/S0362119716030063

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  • DOI: https://doi.org/10.1134/S0362119716030063

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