A new measure for quantifying the bilateral coordination of human gait: effects of aging and Parkinson’s disease
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The bilateral coordination of locomotion has been described in detail in animal studies and to some degree in man; however, the mechanisms that contribute to the bilateral coordination of gait in humans are not fully understood. The objective of the present study was to develop a measure for quantifying the bilateral coordination of gait and to evaluate the effects of aging and Parkinson’s disease (PD) on this new metric. To this end, we compared the gait of healthy older adults to that of healthy young adults and patients with PD. Specifically, we defined the stride duration of one foot as a gait cycle or 360°, determined the relative timing of contra-lateral heel-strikes, and defined this as the phase, ϕ (ideally, ϕ = 180° for every step). The sum of the coefficient of variation of ϕ and the mean absolute difference between ϕ and 180° was defined as the phase coordination index (PCI), representing variability and inaccuracy, respectively, in phase generation. PCI values were higher (poorer bilateral coordination) in patients with PD in comparison to the healthy older adults (P < 0.006). Although gait speed and stride time variability were similar in the healthy young and older adults, PCI values were significantly higher among the healthy elderly subjects compared to the young adults (P < 0.001). Regression analysis suggests that only about 40% of the variance in the values of PCI can be explained by the combination of gait asymmetry (as defined by the differences in each leg’s swing times), gait speed and stride time variability, pointing to the independent nature of this new metric. This study demonstrates that bilateral coordination of gait deteriorates with aging, further deteriorates in PD, and is not strongly associated with other spatio-temporal features of gait.
KeywordsBlateral coordination Aging Parkinson’s disease Gait
We thank the subjects for their participation, time and effort. We thank Ms. Galit Yogev, Ms. Michal Leshem and Mr. Ronny Bartsch for their invaluable assistance and Dr. Eli Plotnik for mathematical advice. This work was supported in part by the Inheritance Fund of the Israeli Ministry of Health, NIH grants AG-14100, RR-13622, HD-39838 and AG-08812, by the US-Israel Bi-National Science Foundation, by the Parkinson’s Disease Foundation (PDF), New York and the National Parkinson Foundation (NPF), Miami USA, and by the European Union Sixth Framework Program, FET contract no. 018474-2, Dynamic Analysis of Physiological Networks (DAPHNet).
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