Biomechanical Comparison of Male and Female Distance Runners*

Nelson, Richard C.; Brooks, Christine; Pike, Nancy L.

doi:10.1111/j.1749-6632.1977.tb38247.x

Cited by 23 publications

(16 citation statements)

References 2 publications

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“…In particular, the different filtering techniques used for the two data sets may have affected the magnitudes of the angular velocities of the lower extremity segments. The longer relative stride lengths used by the elite female runners compared with elite males is similar to the results presented by Nelson et al (16) or collegiate runners. It would be interesting to have a group of male runners of similar size to the females so that it could be determined whether these differences are due to differences in size of the two groups or are in fact gender differences.…”

Section: Kinematic Datasupporting

confidence: 88%

“…Differences between male and female runners in stride length (SL) were reported by Nelson et a!. (16) for speeds ranging from 4.8 to 6.7 ms'. A group of 21 elite women used shorter absolute stride lengths at a given velocity when compared with a control group of 10 college-level male runners, but when SL was expressed relative to body height the women ran with relative strides significantly greater than the males.…”

Section: Review Of Literaturementioning

confidence: 88%

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Biomechanical Studies of Elite Female Distance Runners*

1987

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Section: Kinematic Datasupporting

confidence: 88%

Section: Review Of Literaturementioning

confidence: 88%

Biomechanical Studies of Elite Female Distance Runners*

1987

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“…Figure 10 compares video footage of a human child with images of a simulated child, and figure 12 compares biomechanical data from the literature [22,10] with measurements of the simulated runners. We found that our simulation results were very similar to the quantitative data from the human runners.…”

Section: Discussionmentioning

confidence: 99%

Adapting simulated behaviors for new characters

Hodgins

Pollard

1997

Proceedings of the 24th Annual Conference on Computer Graphics and Interactive Techniques - SIGGRAPH '97

187

109

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This paper describes an algorithm for automatically adapting existing simulated behaviors to new characters. Animating a new character is difficult because a control system tuned for one character will not, in general, work on a character with different limb lengths, masses, or moments of inertia. The algorithm presented here adapts the control system to a new character in two stages. First, the control system parameters are scaled based on the sizes, masses, and moments of inertia of the new and the original characters. Then a subset of the parameters is fine-tuned using a search process based on simulated annealing. To demonstrate the effectiveness of this approach, we animate the running motion of a woman, child, and imaginary character by modifying the control system for a man. We also animate the bicycling motion of a second imaginary character by modifying the control system for a man. We evaluate the results of this approach by comparing the motion of the simulated human runners with video of an actual child and with data for men, women, and children in the literature. In addition to adapting a control system for a new model, this approach can also be used to adapt the control system in an on-line fashion to produce a physically realistic metamorphosis from the original to the new model while the morphing character is performing the behavior. We demonstrate this on-line adaptation with a morph from a man to a woman over a period of twenty seconds.

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“…Notably, many studies on human running showed a significant positive correlation between tc and RE (Nummela et al, 2007;Barnes et al, 2014;Di Michele and Merni, 2014;Mooses et al, 2021). This was likely due to less time required for braking to decelerate the body's forward motion (Nummela et al, 2007;Kong and de Heer, 2008;Mooses et al, 2021). Meanwhile, a negative correlation between leg stiffness and tc was demonstrated in other studies (Morin et al, 2007;Hayes and Caplan, 2014;Santos-Concejero et al, 2014;Man et al, 2016).…”

Section: Leg Stiffness and Running Economymentioning

confidence: 89%

“…Because the longer tc allows the lower-extremities to generate propulsive force over a longer period of time when in contact with the ground, reducing energy costs (Kram and Taylor, 1990). Notably, many studies on human running showed a significant positive correlation between tc and RE (Nummela et al, 2007;Barnes et al, 2014;Di Michele and Merni, 2014;Mooses et al, 2021). This was likely due to less time required for braking to decelerate the body's forward motion (Nummela et al, 2007;Kong and de Heer, 2008;Mooses et al, 2021).…”

Section: Leg Stiffness and Running Economymentioning

confidence: 99%

Running economy and lower extremity stiffness in endurance runners: A systematic review and meta-analysis

Liu

Wu²,

Shi³

et al. 2022

Front. Physiol.

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Background: Lower extremity stiffness simulates the response of the lower extremity to landing in running. However, its relationship with running economy (RE) remains unclear. This study aims to explore the relationship between lower extremity stiffness and RE.Methods: This study utilized articles from the Web of Science, PubMed, and Scopus discussing the relationships between RE and indicators of lower extremity stiffness, namely vertical stiffness, leg stiffness, and joint stiffness. Methodological quality was assessed using the Joanna Australian Centre for Evidence-Based Care (JBI). Pearson correlation coefficients were utilized to summarize effect sizes, and meta-regression analysis was used to assess the extent of this association between speed and participant level.Result: In total, thirteen studies involving 272 runners met the inclusion criteria and were included in this review. The quality of the thirteen studies ranged from moderate to high. The meta-analysis results showed a negative correlation between vertical stiffness (r = −0.520, 95% CI, −0.635 to −0.384, p < 0.001) and leg stiffness (r = −0.568, 95% CI, −0.723 to −0.357, p < 0.001) and RE. Additional, there was a small negative correlation between knee stiffness and RE (r = −0.290, 95% CI, −0.508 to −0.037, p = 0.025). Meta-regression results showed that the extent to which leg stiffness was negatively correlated with RE was influenced by speed (coefficient = −0.409, p = 0.020, r2 = 0.79) and participant maximal oxygen uptake (coefficient = −0.068, p = 0.010, r2 = 0.92).Conclusion: The results of this study suggest that vertical, leg and knee stiffness were negatively correlated with RE. In addition, maximum oxygen uptake and speed will determine whether the runner can take full advantage of leg stiffness to minimize energy expenditure.

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Biomechanical Comparison of Male and Female Distance Runners*

Cited by 23 publications

References 2 publications

Biomechanical Studies of Elite Female Distance Runners*

Biomechanical Studies of Elite Female Distance Runners*

Adapting simulated behaviors for new characters

Running economy and lower extremity stiffness in endurance runners: A systematic review and meta-analysis

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