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Time series analysis of leg movements during freezing of gait in Parkinson's disease: akinesia, rhyme or reason?

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  • Hausdorff, Jeffrey M
  • Balash, Y
  • Giladi, Nir

Abstract

We quantitatively characterized the fluctuations in the forces under the feet during freezing of gait (FOG) in 11 patients with advanced Parkinson's disease. FOG, a leading cause of falls and impaired functional independence, is a poorly understood debilitating phenomenon that is common among persons with advanced Parkinson's disease. During freezing, the feet are “glued” to the ground and the subject is unable to move forward despite effort in what has been described as an absence of movement. Using time series and fractal analysis methods, we found that FOG is not a frozen akinetic state, nor is freezing random, uncorrelated attempts at overcoming motor blockade. Instead, the forces under the feet oscillate in a fairly organized pattern. However, in contrast to walking and resting leg tremor, the spectrum was broadband and more complex. This complex movement pattern may reflect the activation of multiple networks during FOG.

Suggested Citation

  • Hausdorff, Jeffrey M & Balash, Y & Giladi, Nir, 2003. "Time series analysis of leg movements during freezing of gait in Parkinson's disease: akinesia, rhyme or reason?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 321(3), pages 565-570.
    • Handle: RePEc:eee:phsmap:v:321:y:2003:i:3:p:565-570
    DOI: 10.1016/S0378-4371(02)01744-2
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    Citations

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    Cited by:

    1. Pablo Arias & Javier Cudeiro, 2010. "Effect of Rhythmic Auditory Stimulation on Gait in Parkinsonian Patients with and without Freezing of Gait," PLOS ONE, Public Library of Science, vol. 5(3), pages 1-8, March.
    2. Lahmiri, Salim, 2017. "Parkinson’s disease detection based on dysphonia measurements," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 98-105.
    3. de Oliveira, M. Elias & Menegaldo, L.L. & Lucarelli, P. & Andrade, B.L.B. & Büchler, P., 2011. "On the use of information theory for detecting upper limb motor dysfunction: An application to Parkinson’s disease," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4451-4458.

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