Running injury and stride time variability over a prolonged run

Meardon, Stacey A.; Hamill, Joseph; Derrick, Timothy R.

doi:10.1016/j.gaitpost.2010.09.020

Cited by 110 publications

(106 citation statements)

References 24 publications

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“…Overall findings revealed that 73% (n = 16/22) of studies reported a statistically significant difference in at least one dependent variable used to examine movement variability between injured subjects and uninjured controls. Injured subject groups demonstrated greater variability in 64% (n = 14/22) of the studies, reduced variability in 27% (n = 6/22), and no difference between groups was evident in 27% (n = 6/22) . Table presents the percentage of studies reporting greater, less, or no difference in variability when comparing injured subjects to uninjured controls.…”

Section: Resultsmentioning

confidence: 99%

Does the amount of lower extremity movement variability differ between injured and uninjured populations? A systematic review

Baida

Gore

Franklyn-Miller

et al. 2018

Scandinavian Med Sci Sports

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Movement variability during repetitive performance of a dynamic activity (eg, running, jumping, kicking) is considered an integral characteristic of optimal movement execution; however, its relationship with musculo-skeletal injury is not known. The primary aim of this study was to review published comparison trials to determine whether movement variability differs between uninjured controls and subjects with a lower limb musculo-skeletal injury. A systematic search of online databases; MEDLINE, Sports Discus, Scopus, and Web of Science was conducted from July to November 2016. Studies were selected if they (a) included participants with a lower limb injury, (b) compared injured participants to uninjured controls, (c) examined movement variability for at least one dependent variable, and (d) provided a statistical between-group comparison when comparing measures of movement variability. Studies were excluded if they (a) investigated neurological disorders, (b) examined musculo-skeletal injury in the upper extremity or spine, and (c) used nonlinear measures to examine variability (ie, complexity). A significant difference between injured and uninjured populations was reported in 73% of the included studies, and of these, 64% reported greater movement variability in the injured group. This is the first systematic review with a best-evidence synthesis investigating the association between movement variability and musculo-skeletal injury. Findings suggest that movement variability in those with a musculo-skeletal injury differs from uninjured individuals. Interestingly, there was an overall trend toward greater movement variability being associated with the injured groups, although it should be noted that this trend was not consistent across all subcategories (eg, injury type). For a clearer insight into the clinical application of variability, greater methodological homogeneity is required and prospective research is recommended.

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Section: Resultsmentioning

confidence: 99%

Does the amount of lower extremity movement variability differ between injured and uninjured populations? A systematic review

Baida

Gore

Franklyn-Miller

et al. 2018

Scandinavian Med Sci Sports

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“…To this aim, subjects need to adequately explore the immediate environment, and correct the cycling time to appropriate target values. It is taught that, in other movement types such as walking, stride-to-stride variability emerges as a consequence of system's need to continuously correct movement errors (Jordan et al 2007;Meardon et al 2011). The study of walking variability has received great attention because it is interesting parameter for pathological conditions such as aging, neuropsychiatric diseases, Parkinson's disease, cruciate ligament deficit (Hausdorff 2009).…”

Section: Introductionmentioning

confidence: 99%

Pedaling time variability is increased in dropped riding position

2011

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Variability of cycle-to-cycle duration during a pedaling task is probably related to the rhythmic control of the lower limb muscles as in gait. Although walking variability has been extensively studied for its clinical and physiological implications, pedaling variability has received little attention. The present contribution determines the variability of the cycling time during a 10-min exercise as a function of upper body position. Nine healthy males were required to pedal on cycle-ergometer at a self-selected speed for 10 min in two different upper body positions [hands on upper handlebars (UP) or lower handlebars (DP)]. Time domain measures of cycling variability [total standard deviation (SDtot), mean standard deviation cycle-to-cycle intervals over 100 cycles (SD100), standard deviation of the average cycle-to-cycle intervals over 100 cycles (SDA100)] were measured. Moreover, the same time domain measures were also calculated for heart rate in order to discriminate possible involvements of autonomic regulation. Finally, the structure of the cycle variations has been analyzed in the framework of deterministic chaos calculating the maximum Lyapunov exponents. Significant increases in cycle-to-cycle variability were found for SDtot, SD100 in DP compared to UP, whereas cardiac parameters and other cycling parameters were not changed in the two positions. Moreover, the maximum Lyapunov exponent was significantly more negative in DP. The results suggest that small perturbations of upper body position can influence the control of cycling rhythmicity by increasing the variability in a dissipative deterministic regimen.

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“…Instead on-going stride variations are meaningfully related—in a decaying Power law fashion—to past variations stretching back over thousands of strides (Meardon et al, 2011; Hamill et al, 2012). This pervasive fractal variation ensures the mechanical stress of running is distributed in ever varying, yet non-randomly organized, patterns: patterns tuned, through practice, to the runner’s unique architectural and experiential peculiarities.…”

Section: Running Variability: Sharing the Running Work-burdenmentioning

confidence: 99%

“…This structured variability enables the well-trained runner to disperse the running ‘work burden’ amongst expanded networks of biological tissues, whilst simultaneously retaining the agility to spontaneously respond to emerging challenge ( Figure 2 ). Healthy running, accordingly, is characterized by an optimal bandwidth of movement variability: neither too much, nor too little (Meardon et al, 2011; Hamill et al, 2012). …”

Section: Running Variability: Sharing the Running Work-burdenmentioning

confidence: 99%

The Robust Running Ape: Unraveling the Deep Underpinnings of Coordinated Human Running Proficiency

Kiely

2017

Front. Psychol.

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In comparison to other mammals, humans are not especially strong, swift or supple. Nevertheless, despite these apparent physical limitations, we are among Natures most superbly well-adapted endurance runners. Paradoxically, however, notwithstanding this evolutionary-bestowed proficiency, running-related injuries, and Overuse syndromes in particular, are widely pervasive. The term ‘coordination’ is similarly ubiquitous within contemporary coaching, conditioning, and rehabilitation cultures. Various theoretical models of coordination exist within the academic literature. However, the specific neural and biological underpinnings of ‘running coordination,’ and the nature of their integration, remain poorly elaborated. Conventionally running is considered a mundane, readily mastered coordination skill. This illusion of coordinative simplicity, however, is founded upon a platform of immense neural and biological complexities. This extensive complexity presents extreme organizational difficulties yet, simultaneously, provides a multiplicity of viable pathways through which the computational and mechanical burden of running can be proficiently dispersed amongst expanded networks of conditioned neural and peripheral tissue collaborators. Learning to adequately harness this available complexity, however, is a painstakingly slowly emerging, practice-driven process, greatly facilitated by innate evolutionary organizing principles serving to constrain otherwise overwhelming complexity to manageable proportions. As we accumulate running experiences persistent plastic remodeling customizes networked neural connectivity and biological tissue properties to best fit our unique neural and architectural idiosyncrasies, and personal histories: thus neural and peripheral tissue plasticity embeds coordination habits. When, however, coordinative processes are compromised—under the integrated influence of fatigue and/or accumulative cycles of injury, overuse, misuse, and disuse—this spectrum of available ‘choice’ dysfunctionally contracts, and our capacity to safely disperse the mechanical ‘stress’ of running progressively diminishes. Now the running work burden falls increasingly on reduced populations of collaborating components. Accordingly our capacity to effectively manage, dissipate and accommodate running-imposed stress diminishes, and vulnerability to Overuse syndromes escalates. Awareness of the deep underpinnings of running coordination enhances conceptual clarity, thereby informing training and rehabilitation insights designed to offset the legacy of excessive or progressively accumulating exposure to running-imposed mechanical stress.

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Running injury and stride time variability over a prolonged run

Cited by 110 publications

References 24 publications

Does the amount of lower extremity movement variability differ between injured and uninjured populations? A systematic review

Does the amount of lower extremity movement variability differ between injured and uninjured populations? A systematic review

Pedaling time variability is increased in dropped riding position

The Robust Running Ape: Unraveling the Deep Underpinnings of Coordinated Human Running Proficiency

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