Literature DB >> 9029225

Altered fractal dynamics of gait: reduced stride-interval correlations with aging and Huntington's disease.

J M Hausdorff1, S L Mitchell, R Firtion, C K Peng, M E Cudkowicz, J Y Wei, A L Goldberger.   

Abstract

Fluctuations in the duration of the gait cycle (the stride interval) display fractal dynamics and long-range correlations in healthy young adults. We hypothesized that these stride-interval correlations would be altered by changes in neurological function associated with aging and certain disease states. To test this hypothesis, we compared the stride-interval time series of 1) healthy elderly subjects and young controls and of 2) subjects with Huntington's disease and healthy controls. Using detrended fluctuation analysis we computed alpha, a measure of the degree to which one stride interval is correlated with previous and subsequent intervals over different time scales. The scaling exponent alpha was significantly lower in elderly subjects compared with young subjects (elderly: 0.68 +/- 0.14; young: 0.87 +/- 0.15; P < 0.003). The scaling exponent alpha was also smaller in the subjects with Huntington's disease compared with disease-free controls (Huntington's disease: 0.60 +/- 0.24; controls: 0.88 +/-0.17; P < 0.005). Moreover, alpha was linearly related to degree of functional impairment in subjects with Huntington's disease (r = 0.78, P < 0.0005). These findings demonstrate that strike-interval fluctuations are more random (i.e., less correlated) in elderly subjects and in subjects with Huntington's disease. Abnormal alterations in the fractal properties of gait dynamics are apparently associated with changes in central nervous system control.

Entities:  

Keywords:  NASA Discipline Cardiopulmonary; Non-NASA Center

Mesh:

Year:  1997        PMID: 9029225     DOI: 10.1152/jappl.1997.82.1.262

Source DB:  PubMed          Journal:  J Appl Physiol (1985)        ISSN: 0161-7567


  169 in total

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10.  Most suitable mother wavelet for the analysis of fractal properties of stride interval time series via the average wavelet coefficient method.

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