It is reported in the literature that the temporal structure of gait
variability in healthy subjects exhibits deterministic processes where not only
each stride is correlated with the neighbouring strides (i.e. short-range correlations), but at least on a statistical
basis, with tens and hundreds of preceding and following strides (i.e. long-range correlations). Thus, an
analysis hinging on a conventional gait Poincare plot with lag one which implicitly
assumes that the current stride is influenced by the immediately preceding
stride will likely underestimate the role of the autocovariance function of stride
intervals. This implies that a series of lagged gait Poincare plots can potentially
provide more information by reflecting short-range correlations of gait
variability through the behaviour of Poincare indices in health as well as
disease. Hence, in this study in the context of short-term variability, we
assessed a curvilinear relation between lag (1 - 6) and Poincare indices in
normal subjects and patients with neurodegenerative disorders. We found that
while normal subjects exhibited this curvilinearity, the patients with
neurodegenerative disorders showed its loss.
Cite this paper
Kamath, C. (2015). Loss of Lag Response Curvilinearity of Gait Poincare Plot Indices in Neurodegenerative Disorders. Open Access Library Journal, 2, e1571. doi: http://dx.doi.org/10.4236/oalib.1101571.
Hausdorff, J.M., Peng, C.K., Ladin, Z., Wei,
J.Y. and Goldberger, A.L. (1995) Is Walking a Random
Walk? Evidence for Long-Range Correlations in Stride Interval of Human Gait. Journal of Applied Physiology, 78, 349-358.
Bollens, B., Crevecoeur, F., Nguyen, V.,
Detrembleur, C. and
Lejeune, T. (2010) Does Human Gait Exhibit Comparable and Reproducible Long-Range
Autocorrelations on Level Ground and on Treadmill? Gait and Posture, 32, 369- 373. http://dx.doi.org/10.1016/j.gaitpost.2010.06.011
Hausdorff,
J.M., Cudkowicz, M.E.,
Firtion, R., Wei, J.Y. and Goldberger, A.L.
(1998) Gait Variability and Basal Ganglia Disorders: Stride-to-Stride
Variations in Gait Cycle Timing in Parkinson and Huntington’s Disease. Movement Disorders, 13, 428-437. http://dx.doi.org/10.1002/mds.870130310
Moody, G.B., Mark, R.G. and Goldberger, A.L. (2001) Physio Net:
A Web-Based Resource, for the Study of Physiologic Signals. IEEE Engineering in Medicine and Biology
Magazine, 20, 70-75. http://dx.doi.org/10.1109/51.932728
Brennan, M., Palaniswami, M. and Kamen, P. (2001) Do Existing Measures of
Poincare Plot Geometry Reflect Non- linear Features of Heart Rate Variability? IEEE Transactions on Biomedical Engineering,
48, 1342-1347. http://dx.doi.org/10.1109/10.959330
Karmakar, C., Khandoker, A., Gubbi, J. and Palaniswami, M. (2009) Complex Correlation Measure:
A Novel Descriptor for Poincare Plot. BioMedical
Engineering, 8,
17. http://dx.doi.org/10.1186/1475-925x-8-17
Goshvarpour, A.,
Goshvarpour, A. and
Rahati, S. (2011)
Analysis of Lagged Poincare Plots in Heart Rate Signals during Meditation. Digital Signal Processing, 21, 208-214. http://dx.doi.org/10.1016/j.dsp.2010.06.015
Stein, P.K. and
Reddy, A. (2005) Non-Linear Heart Rate Variability and Risk Stratification in
Cardiovascular Disease. Indian Pacing and
Electrophysiology Journal, 5, 210-220.
Thakre, T.P. and Smith, M.L. (2006) Loss of Lag-Response Curvilinearity
of Indices of Heart Rate Variability in Congestive Heart Failure. BMC Cardiovascular Disorders, 6, 1-10. http://dx.doi.org/10.1186/1471-2261-6-27