2019
DOI: 10.1007/s10439-019-02236-x
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Using Gait Variability to Predict Inter-individual Differences in Learning Rate of a Novel Obstacle Course

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Cited by 12 publications
(5 citation statements)
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“…Our results are also exciting because this portable device could also offer the possibility to study gait under more realistic situations, such as walking with self-regulated and variable gait speeds. It is well-accepted that motor variability can impact motor learning (Wu et al, 2014;Ulman et al, 2019), and walking on a treadmill is less variable compared to overground walking (Dingwell et al, 2001). Thus, having a device that can induce locomotor adaptation overground would help us gain more understanding about the relationship between variability and motor adaptation in walking.…”
Section: Study Implicationsmentioning
confidence: 99%
“…Our results are also exciting because this portable device could also offer the possibility to study gait under more realistic situations, such as walking with self-regulated and variable gait speeds. It is well-accepted that motor variability can impact motor learning (Wu et al, 2014;Ulman et al, 2019), and walking on a treadmill is less variable compared to overground walking (Dingwell et al, 2001). Thus, having a device that can induce locomotor adaptation overground would help us gain more understanding about the relationship between variability and motor adaptation in walking.…”
Section: Study Implicationsmentioning
confidence: 99%
“…This is exciting because we will be able to study gait under more realistic situations, such as when walking with variable gait speeds. It is well-accepted that motor variability can impact motor learning (Ulman et al, 2019; Wu et al, 2014), and walking on a treadmill is less variable compared to overground walking (Dingwell et al, 2001). Thus, having a device that can induce locomotor adaptation overground would help us gain more understanding about the relationship between variability and motor adaptation in a naturalistic behavior, such as walking.…”
Section: Discussionmentioning
confidence: 99%
“…Coupling angle variability (CAV), the standard deviation across all strides, was calculated for each time point using circular statistics 43 , and then pooled across the gait cycle by computing the overall root-mean-square from all time points. CAV was used as a measure of stride-to-stride coordination variability 44 .…”
Section: Methodsmentioning
confidence: 99%