Fastest may not maximize gait quality: differential and individual-specific immediate effects of gait speed on biomechanical variables post-stroke

Abstract

Background: A common perspective in post-stroke gait training is that walking at the fastest safe speed maximizes the quality of gait biomechanics, with limited detrimental effects on compensatory biomechanics and inter-limb asymmetry. This fastest is best perspective is highly relevant to treadmill training paradigms, as mass high-intensity stepping practice with high-quality biomechanics can improve walking function and reinforce desirable gait patterns. However, it is unclear if walking at the fastest safe speed maximizes the quality of (i.e., optimizes) post-stroke gait biomechanics across variables, individuals, and walking function levels, or if there exists a significant cost (i.e., benefit lost) of walking at the fastest speed when fastest is not optimal. Methods: Here, we determined if walking at the fastest speed optimized 16 biomechanical magnitude and inter-limb asymmetry variables, in 14 low- (n=7) and high-functioning (n=7) stroke survivors. Participants walked at six speeds ranging from their self-selected to fastest safe speed. To characterize the relative benefit of optimizing, rather than maximizing, gait speed for each variable, we compared the biomechanical cost (i.e., immediate speed-induced change versus the self-selected speed) of walking at the fastest versus the optimal speed. Finally, we used linear regression to characterize how each variable's quality changed with absolute speed. Results: Across speeds, 50% of magnitude and 17% of asymmetry variables were optimized at the fastest speed, but which variables were optimized differed between participants. Compared to walking at the optimal speed for each variable, the fastest speed elicited large biomechanical costs for some inter-limb asymmetry variables (difference in Cohen's d=0.1-0.9). Both low- and high-function subgroups exhibited significant positive correlations between walking speed and paretic-leg trailing limb angle, peak ankle moment, and peak hip and ankle power magnitudes (all p<0.001), though the magnitude of changes in some variables differed between groups. Changes in inter-limb asymmetry were highly variable, even within-groups. Conclusions: These results refine the perspective that fastest is best, showing that the training speeds that maximize gait quality may not be the fastest for all individuals and biomechanical variables. Individual-specific stroke gait quality metrics encompassing multiple biomechanical variables are needed to guide gait speed optimization for precision rehabilitation.

The Effects of Stroke and Stroke Gait Rehabilitation on Behavioral and Neurophysiological Outcomes:

“…However, these systems still generate a lot of data, subject to interpretation, including multiple joint angles, and over 20-50 spatiotemporal gait metrics. 44 , 45 Thus, another avenue for future research is the development and clinical validation of gait analysis methods that can be applied to clinical settings, while being rapid, objective, intuitive, interpretable, and user-friendly to supplement clinical outcomes.…”

“…However, these systems still generate a lot of data, subject to interpretation, including multiple joint angles, and over 20-50 spatiotemporal gait metrics. 44,45 Thus, another avenue for future research is the development and clinical validation of gait analysis methods that can be applied to clinical settings, while being rapid, objective, intuitive, interpretable, and user-friendly to supplement clinical outcomes. Biomechanical metrics or computational analysis have strong potential for enhancing our understanding of the biomechanical mechanism underlying rehabilitation response, because they can provide valuable insights about restitution versus compensation as well as underlying changes in motor control.…”

Gait signature changes with walking speed are similar among able-bodied young adults despite persistent individual-specific differences

“…To modulate gait speed from slow to a faster pace, individuals can employ various strategies, including taking longer steps, increasing step frequency, and decreasing the swing or stance phase durations, among others [14][15][16][17] . Increasing gait speed has also been associated with complex changes in joint excursions and step length asymmetry in people post-stroke [18,19] . However, previous research demonstrated that speed had little effect on joint-level coordination in injury-free adults [20,21] .…”