Background and objective Previous studies suggest that error augmentation may be used as a strategy to achieve longer-term changes in gait deficits after stroke. The purpose of this study was to determine whether longer-term improvements in step length asymmetry could be achieved with repeated split-belt treadmill walking practice using an error augmentation strategy. Methods 13 persons with chronic stroke (>6 months) participated in testing: (1) prior to 12 sessions of split-belt treadmill training, (2) after the training, and (3) in follow-up testing at 1 and 3 months. Step length asymmetry was the target of training, so belt speeds were set to augment step length asymmetry such that aftereffects resulted in reduced step length asymmetry during overground walking practice. Each individual was classified as a “responder” or “nonresponder” based on whether their reduction in step length asymmetry exceeded day-to-day variability. Results For the group and for the responders (7 individuals), step length asymmetry improved from baseline to posttesting (P < .05) through an increased step length on both legs but a relatively larger change on the shorter step side (P < .05). Other parameters that were not targeted (eg, stance time asymmetry) did not change over the intervention. Conclusions This study demonstrates that short-term adaptations can be capitalized on through repetitive practice and can lead to longer-term improvements in gait deficits poststroke. The error augmentation strategy, which promotes stride-by-stride adjustment to reduce asymmetry and results in improved asymmetry during overground walking practice, appears to be critical for obtaining the improvements observed.

The Fitbit Ultra may be a low-cost alternative to measure the stepping activity in level, predictable environments of people with stroke and TBI who can walk at speeds ≥0.58 m/s.

Background/Purpose Many factors appear to be related to physical activity after stroke, yet it is unclear how these factors interact and which ones might be the best predictors. Therefore, the purpose of this study was twofold: 1) to examine the relationship between walking capacity and walking activity, and 2) to investigate how biopsychosocial factors and self-efficacy relate to walking activity, above and beyond walking capacity impairment post-stroke. Methods Individuals greater than 3 months post-stroke (n=55) completed the Yesavage Geriatric Depression Scale (GDS), Fatigue Severity Scale (FSS), Modified Cumulative Illness Rating (MCIR) Scale, Walk 12, Activities Specific Balance Confidence (ABC) Scale, Functional Gait Assessment (FGA), and oxygen consumption testing. Walking activity data was collected via a StepWatch Activity Monitor (SAM). Predictors were grouped into 3 constructs: (1) Walking Capacity: oxygen consumption and FGA; (2) Biopsychosocial: GDS, FSS, and MCIR; (3) Self-Efficacy: Walk 12 and ABC. Moderated sequential regression models were used to examine what factors best predicted walking activity. Results Walking capacity explained 35.9% (p<0.001) of the variance in walking activity. Self-efficacy (ΔR2 = 0.15, p<0.001) and the interaction between the FGA*ABC (ΔR2 = 0.047, p<0.001) significantly increased the variability explained. FGA (β=0.37, p=0.01), MCIR (β=−0.26, p=0.01), and Walk 12 (β=−0.45, p=0.00) were each individually significantly associated with walking activity. Discussion/Conclusion While measures of walking capacity and self-efficacy significantly contributed to "real-world" walking activity, balance self-efficacy moderated the relationship between walking capacity and walking activity. Improving low balance self-efficacy may augment walking capacity and translate to improved walking activity post-stroke.