Loss of Lag Response Curvilinearity of Gait Poincare Plot Indices in Neurodegenerative Disorders

Chandrakar Kamath

doi:10.4236/oalib.1101571

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Open Access Library Journal > Vol.2 No.6, June 2015

Loss of Lag Response Curvilinearity of Gait Poincare Plot Indices in Neurodegenerative Disorders ()

Chandrakar Kamath

Shantha Nilaya, Ananthnagar, Manipal, India.

DOI: 10.4236/oalib.1101571 PDF HTML XML 490 Downloads 762 Views Citations

Abstract

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.

Keywords

Gait Signal, Neurodegenerative Disorder, Nonlinear Dynamics, Ordinal Patterns, Symbolic Analysis

Share and Cite:

Kamath, C. (2015) Loss of Lag Response Curvilinearity of Gait Poincare Plot Indices in Neurodegenerative Disorders. Open Access Library Journal, 2, 1-11. doi: 10.4236/oalib.1101571.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Winter, D.A. (2009) Biomechanics and Motor Control of Human Movement. 4th Edition, John Wiley & Sons, Hoboken. http://dx.doi.org/10.1002/9780470549148
[2]	Callisaya, M.L., Blizzard, L., McGinley, J.L., Schmidt, M.D. and Srikanth, V.K. (2010) Sensorimotor Factors Affecting Gait Variability in Older People—A Population-Based Study. Journals of Gerontology—Series A, 65, 386-392. http://dx.doi.org/10.1093/gerona/glp184
[3]	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.
[4]	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
[5]	Hausdorff, J.M., Mitchell, S.L., Firtion, R., Peng, C.K., Cudkowicz, M.E., Wei, J.Y. and Goldberger, A.L. (1997) Altered Fractal Dynamics of Gait: Reduced Stride-Interval Correlations with Aging and Huntington’s Disease. Journal of Applied Physiology, 82, 262-269.
[6]	Hausdorff, J.M., Lertratanakul, A., Cudkowicz, M.E., Peterson, A.L., Kaliton, D. and Goldberger, A.L. (2000) Dynamic Markers of Altered Gait Rhythm in Amyotrophic Lateral Sclerosis. Journal of Applied Physiology, 88, 2045-2053.
[7]	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
[8]	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
[9]	Hahn, G.J. and Shapiro, S.S. (1994) Statistical Models in Engineering. Wiley, Hoboken.
[10]	Brennan, M., Palaniswami, M. and Kamen, P. (2001) Do Existing Measures of Poincare Plot Geometry Reflect Nonlinear Features of Heart Rate Variability? IEEE Transactions on Biomedical Engineering, 48, 1342-1347. http://dx.doi.org/10.1109/10.959330
[11]	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
[12]	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
[13]	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.
[14]	Lerma, C., Infante, O., Perez-Grovas, H. and Jose, M.V. (2003) Poincare Plot Indexes of Heart Rate Variability Capture Dynamic Adaptations after Haemodialysis in Chronic Renal Failure Patients. Clinical Physiology and Functional Imaging, 23, 72-80. http://dx.doi.org/10.1046/j.1475-097X.2003.00466.x
[15]	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
[16]	Gabell, A. and Nayak, U.S.L. (1984) The Effect of Age on Variability in Gait. Journal of Gerontology, 39, 662-666. http://dx.doi.org/10.1093/geronj/39.6.662