Abstract
BackgroundStride-to-stride variability may be used as an indicator in the assessment of gait performance, but the evaluation of this parameter is not trivial. In the gait pattern, a deviation in one stride must be corrected within the next strides (elemental variables) to ensure a steady gait (performance variable). The variance in these elemental and performance variables may therefore be evaluated as adjusting and resulting components of variability. We explored this approach to gait evaluation by matching the velocity of one stride to a subsequent stride with four different time lags ranging from 0.5 to 2 strides with 0.5 stride increments. The time lag values corresponded to the following contralateral stride, the following ipsilateral stride, the second following contralateral stride and the second following ipsilateral stride.MethodsTwenty asymptomatic young adults walked on an instrumented treadmill at their preferred gait speed. The stride velocity was calculated, and variances in the stride-to-stride differences and in the stride-to-stride sums represented the adjusting and the resulting variances, respectively. A ratio between these values of greater than one indicated a meaningful stride-to-stride interaction.ResultsFor the four time lags (0.5, 1, 1.5, and 2 strides), the adjusting/resulting variance ratios (mean and CI 95%) were 1.0 (0.8–1.2), 2.9 (2.3–3.6), 1.2 (1.0–1.4) and 1.2 (0.9–1.4), respectively.ConclusionsThis new approach to the evaluation of stride-to-stride variability suggests that gait velocity adjustments occurred within one full stride cycle during treadmill walking among asymptomatic young adults. The validity of the approach needs to be tested in over-ground walking.
Highlights
Stride-to-stride variability may be used as an indicator in the assessment of gait performance, but the evaluation of this parameter is not trivial
Summary The approach to the gait analysis used in this study evaluated the variation in stride-to-stride velocity differences, i.e., the adjusting variability, relative to the variation in stride-to-stride sums, i.e. the resulting variability of the gait velocity
Moe-Nilssen et al analysed the structure of the time series using an autocorrelation coefficient to detect gait deficits [5]
Summary
Stride-to-stride variability may be used as an indicator in the assessment of gait performance, but the evaluation of this parameter is not trivial. A deviation in one stride must be corrected within the strides (elemental variables) to ensure a steady gait (performance variable). The variance in these elemental and performance variables may be evaluated as adjusting and resulting components of variability. During a clinical examination of the gait, the lack of a steady rhythm in the gait pattern will draw the attention of the clinician Such an observation will often be interpreted as a deficit in the motor planning or in the postural control of the patient. The variability of the gait pattern, based on a discrete time series analysis of a large number of gait cycles, has been proven to be significant and may reveal information about the maturation of gait
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
