A dynamical systems approach to lower extremity running injuries

Hamill, Joseph; Emmerik, Richard E.A. van; Heiderscheit, Bryan C.; Li, Li

doi:10.1016/s0268-0033(98)90092-4

Cited by 579 publications

(531 citation statements)

References 28 publications

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“…Human movement variability has been described as having a functional role (Hamill, van Emmerick, Heiderscheit and Li, 1999;van Emmerick, Hamill, and McDermott, 2005;Bartlett et al, 2007), but it has also been described as having a component of "noise" (Wolpert, 2007;Cohen and Sternad, 2009) and as being due to redundancy in the sensorimotor system (Newell and Corcos, 1993). As variability will always be present in human movement (Bartlett et al, 2007) it will have an important influence on the success of a given task and therefore the technique adopted by athletes.…”

Section: Resultsmentioning

confidence: 99%

Investigating optimal technique in a noisy environment: Application to the upstart on uneven bars

Hiley

Yeadon

2013

Human Movement Science

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Additional Information:• NOTICE: this is the author's version of a work that was accepted for publication in Human Movement Science.Changes ABSTRACTThe upstart is a fundamental skill in gymnastics which is used to transfer a gymnast from a swing beneath the bar to a position above the bar. The aim of this study was to optimise the technique in the upstart on the uneven bars in order to determine the underlying control strategy used by gymnasts. A previous attempt based on minimising joint torque had failed to find a satisfactory solution without forcing the joint angle histories to pass through a "via-point" (Yamasaki et al., 2010). Using a computer simulation model of a gymnast and bar, the technique (joint angle histories) used in the upstart was optimised under three different criteria: minimising joint torque, minimising joint torque change and maximising success in the presence of movement variability. The third optimisation introduced "noise" into the joint angle time histories based on measurements of kinematic variability. All three optimisations were started from the technique used by a gymnast competing in an Olympic Games uneven bars final. Root mean squared (RMS) differences between the recorded and optimal joint angle time histories were computed. The two optimisations based on minimising joint torque diverged from the gymnast's technique. However, the technique based on maximising the number of successful performances in a noisy environment remained close to the gymnast's technique. It is concluded that the underlying strategy used in the upstart is not based on minimisation of joint torque; rather, it is based on ensuring success in the task despite the inherent variability in technique. Gymnasts develop techniques that are able to cope with the level of kinematic variability present in their movements.

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Section: Resultsmentioning

confidence: 99%

Investigating optimal technique in a noisy environment: Application to the upstart on uneven bars

Hiley

Yeadon

2013

Human Movement Science

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“…Potentially, these results provide support for the hypothesised link between variability and overuse injury. Follow-up studies (Heiderschiet, 2000;Heiderschiet et al, 2002) reported similar results to Hamill et al (1999). However, with the retrospective research designs used in these studies, it is impossible to determine whether the decreased variability was the cause or the effect of the patellofemoral pain.…”

Section: Variability In Basketball Shootingmentioning

confidence: 92%

“…This approach challenges traditional views of movement variability, which assume variability to be system noise or error that must be eliminated: non-linear dynamical systems theory, in contrast, proposes that variability is functional. Hamill et al (1999) stated that a central message of the work in motor control from a dynamical systems perspective (e.g. Schöner et al, 1986) is that variability in movement is necessary for changes in the coordination of movement, for example from walking to running or vice versa (Diedrich and Warren, 1995).…”

Section: Variability In Basketball Shootingmentioning

confidence: 99%

“…Schöner et al, 1986) is that variability in movement is necessary for changes in the coordination of movement, for example from walking to running or vice versa (Diedrich and Warren, 1995). As well as assisting in coordination changes, various authors have postulated recently that another function of movement variability might be to attenuate impact shocks when runners are subjected to large forces (Holt et al, 1995;Hamill et al, 1999;Heiderscheit et al, 1999;James et al, 2000;Heiderscheit et al, 2002;James, 2004). These authors suggested that variability in movement might provide a broader distribution of stresses among different tissues, potentially reducing the cumulative load on internal structures of the body.…”

Section: Variability In Basketball Shootingmentioning

confidence: 99%

“…McClay and Manal, 1997;Stergiou and Bates, 1997;Stergiou et al, 1999;DeLeo et al, 2004). With this in mind, investigating the actions of the Hamill et al (1999) were among the first to use the dynamical systems approach to investigate overuse running injuries. These authors recognised the two important tenets of dynamical systems theory outlined previously in this section -the importance of movement variability and inter-segment coordination.…”

Section: Variability In Basketball Shootingmentioning

confidence: 99%

See 2 more Smart Citations

Is movement variability important for sports biomechanists?

Bartlett

Wheat

Robins

2007

Sports Biomechanics

369

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Quantifying coordinative patterns in steady‐state running: The impact of footwear and foot strike on joint coupling variability

Garofolini,

Mickle,

McLaughlin

et al. 2024

European Journal of Sport Science

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In this study, we aimed to compare and contrast the intralimb coordinative patterns of habitual forefoot strikers (FFS) and rearfoot strikers (RFS) during steady‐state running across three different shoe types: minimalist, neutral and cushioned shoes. To describe these coordinative patterns, we implemented the concept of the ‘preferred movement path’ which represents the movement path that runners naturally select in response to their physical capacity and external environment. We quantified cycle‐to‐cycle consistency (ACC) and within‐trial variance in coordination patterns (SoV) using joint angle data from the ankle and knee for ankle‐knee coupling and from the knee and hip for knee‐hip coupling. Additionally, we calculated the measure of shape difference in joint coupling as the sum of squared distances (SSD) between/within conditions and groups. The percentage of runners who displayed shape differences below certain SSD thresholds was also evaluated. Our findings revealed no significant group or shoe type effect on any of the variability measures (ACC: p = 0.460 for ankle‐knee and p = 0.832 for knee‐hip; SoV: p = 0.345 for ankle‐knee and p = 0.755 for knee‐hip). However, there was a significant (p < 0.001) shape difference observed between the most extreme shoe conditions. Despite this, when runners switched shoes, 70%–90% of them maintained their original coordinative pattern across both joint couplings, indicating a strong adherence to their preferred movement path. This suggests that while shoe type can influence the shape of the coordinative pattern, the inherent movement tendencies of the runners remain largely consistent.

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A dynamical systems approach to lower extremity running injuries

Cited by 579 publications

References 28 publications

Investigating optimal technique in a noisy environment: Application to the upstart on uneven bars

Investigating optimal technique in a noisy environment: Application to the upstart on uneven bars

Is movement variability important for sports biomechanists?

Quantifying coordinative patterns in steady‐state running: The impact of footwear and foot strike on joint coupling variability

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