A Test of the Metabolic Cost of Cushioning Hypothesis during Unshod and Shod Running

Medicine and science in sports and exercise (Impact Factor: 3.98). 02/2014; 46(2):324-329. DOI: 10.1249/MSS.0b013e3182a63b81
Source: PubMed


This study aimed to investigate the effects of surface and shoe cushioning on the metabolic cost of running. In running, the leg muscles generate force to cushion the impact with the ground. External cushioning (surfaces or shoes) may reduce the muscular effort needed for cushioning and thus reduce metabolic cost. Our primary hypothesis was that the metabolic cost of unshod running would decrease with a more cushioned running surface. We also hypothesized that because of the counteracting effects of shoe cushioning and mass, unshod running on a hard surface would have approximately the same metabolic cost as running in lightweight, cushioned shoes.
To test these hypotheses, we attached 10- and 20-mm-thick slats of the same foam cushioning used in running shoe midsoles to the belt of a treadmill that had a rigid deck. Twelve subjects who preferred a midfoot strike pattern and had substantial barefoot/minimalist running experience ran without shoes on the normal treadmill belt and on each thickness of foam. They also ran with lightweight, cushioned shoes on the normal belt. We collected V˙O2 and V˙CO2 to calculate the metabolic power demand and used a repeated-measures ANOVA to compare between conditions.
Compared to running unshod on the normal belt, running unshod on the 10-mm-thick foam required 1.63% ± 0.67% (mean ± SD) less metabolic power (P = 0.034) but running on the 20-mm-thick foam had no significant metabolic effect. Running with and without shoes on the normal belt had similar metabolic power demands, likely because the beneficial energetic effects of cushioning counterbalanced the detrimental effects of shoe mass.
On average, surface and shoe cushioning reduce the metabolic power required for submaximal running.

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Available from: Rodger Kram, Jan 24, 2014
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    • "Indirect evidence suggests that the lack of cushioning and arch support in minimalist shoes also improves running economy, independent of shoe mass, by allowing more elastic energy storage and release in the lower extremities (Perl et al., 2012). However, cushioning in shoes helps to reduce the muscular effort needed to cushion impacts with the ground; thus, reducing metabolic cost (Franz et al., 2012; Tung, Franz, & Kram, 2014). It is unclear whether "
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    ABSTRACT: The purpose of this study was to determine if minimalist shoes improve time trial performance oftrained distance runners and if changes in running economy, shoe mass, stride length, stride rate andfootfall pattern were related to any difference in performance. Twenty-six trained runners performedthree 6-min sub-maximal treadmill runs at 11, 13 and 15 km·h−1in minimalist and conventional shoeswhile running economy, stride length, stride rate and footfall pattern were assessed. They thenperformed a 5-km time trial. In the minimalist shoe, runners completed the trial in less time (effectsize 0.20 ± 0.12), were more economical during sub-maximal running (effect size 0.33 ± 0.14) anddecreased stride length (effect size 0.22 ± 0.10) and increased stride rate (effect size 0.22 ± 0.11). All butone runner ran with a rearfoot footfall in the minimalist shoe. Improvements in time trial performancewere associated with improvements in running economy at 15 km·h−1(r= 0.58), with 79% of theimproved economy accounted for by reduced shoe mass (P< 0.05). The results suggest that running inminimalist shoes improves running economy and 5-km running performance.
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    • "But our results suggest that there may be cases where external energy dissipation could actually help to reduce active energy absorption (and therefore positive work) by the human, and thus save metabolic energy or yield more subjective benefits. Indeed, some findings suggest that a cushioned surface can actually reduce the metabolic cost of running (Franz et al., 2012; Frederick et al., 1983; Tung et al., 2014). Cushioning also allows subjects to run with less knee flexion (Ferris et al., 1998; Ferris and Farley, 1997), which might reduce the mechanical work performed. "
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    ABSTRACT: Humans can perform motor tasks in a variety of ways, yet often favor a particular strategy. Some factors governing the preferred strategy may be objective and quantifiable, (e.g. metabolic energy or mechanical work) while others may be more subjective and less measurable, (e.g. discomfort, pain, or mental effort). Subjectivity can make it challenging to explain or predict preferred movement strategies. We propose that subjective factors might nevertheless be characterized indirectly by their trade-offs against more objective measures such as work. Here we investigated whether subjective costs that influence human movement during drop landings could be indirectly assessed by quantifying mechanical work performed. When landing on rigid ground, humans typically absorb much of the collision actively by bending their knees, perhaps to avoid the discomfort of stiff-legged landings. We measured how work performed by healthy adults (N=8) changed as a function of surface cushioning for drop landings (fixed at about 0.4m) onto varying amounts of foam. Landing on more foam dissipated more energy passively in the surface, thus reducing the net dissipation required of subjects, due to relatively fixed landing energy. However, subjects actually performed even less work in the dissipative collision, as well as in the subsequent active, positive work to return to upright stance (approximately linear decrease of about 1.52J per 1cm of foam thickness). As foam thickness increased, there was also a corresponding reduction in center-of-mass vertical displacement after initial impact by up to 43%. Humans appear to subjectively value cushioning, revealed by the extra work they perform landing without it. Cushioning is thus worth more than the energy it dissipates, in an amount that indicates the subjective discomfort of stiff landings. Copyright © 2015 Elsevier Ltd. All rights reserved.
    No preview · Article · Apr 2015 · Journal of Biomechanics
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    • "Many biomechanical studies have shown that individuals respond to a given intervention in a subject-dependent way with the result that the very same intervention can be beneficial for one person but not for another. Subject-dependent responses were reported with respect to footwear (Erhart et al., 2008), running surfaces (Tung et al., 2014), orthotics (Nester et al., 2003), and loading perturbations (James et al., 2014). Thus, from an analytical point of view, the task of predicting the " right " intervention is all but trivial. "
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    ABSTRACT: A functional group is a collection of individuals who react in a similar way to a specific intervention/product such as a sport shoe. Matching footwear features to a functional group can possibly enhance footwear-related comfort, improve running performance, and decrease the risk of movement-related injuries. To match footwear features to a functional group, one has to first define the different groups using their distinctive movement patterns. Therefore, the main objective of this study was to propose and apply a methodological approach to define functional groups with different movement patterns using Self-Organizing Maps and Support Vector Machines. Further study objectives were to identify differences in age, gender and footwear-related comfort preferences between the functional groups. Kinematic data and subjective comfort preferences of 88 subjects (16-76 years; 45 m/43 f) were analysed. Eight functional groups with distinctive movement patterns were defined. The findings revealed that most of the groups differed in age or gender. Certain functional groups differed in their comfort preferences and, therefore, had group-specific footwear requirements to enhance footwear-related comfort. Some of the groups, which had group-specific footwear requirements, did not show any differences in age or gender. This is important because when defining functional groups simply using common grouping criteria like age or gender, certain functional groups with group-specific movement patterns and footwear requirements might not be detected. This emphasises the power of the proposed pattern recognition approach to automatically define groups by their distinctive movement patterns in order to be able to address their group-specific product requirements. Copyright © 2015 Elsevier Ltd. All rights reserved.
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