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The Foot's Arch and the Energetics of Human Locomotion

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The energy-sparing spring theory of the foot’s arch has become central to interpretations of the foot’s mechanical function and evolution. Using a novel insole technique that restricted compression of the foot’s longitudinal arch, this study provides the first direct evidence that arch compression/recoil during locomotion contributes to lowering energy cost. Restricting arch compression near maximally (~80%) during moderate-speed (2.7 ms−1) level running increased metabolic cost by + 6.0% (p < 0.001, d = 0.67; unaffected by foot strike technique). A simple model shows that the metabolic energy saved by the arch is largely explained by the passive-elastic work it supplies that would otherwise be done by active muscle. Both experimental and model data confirm that it is the end-range of arch compression that dictates the energy-saving role of the arch. Restricting arch compression had no effect on the cost of walking or incline running (3°), commensurate with the smaller role of passive-elastic mechanics in these gaits. These findings substantiate the elastic energy-saving role of the longitudinal arch during running, and suggest that arch supports used in some footwear and orthotics may increase the cost of running.
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Scientific RepoRts | 6:19403 | DOI: 10.1038/srep19403
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The Foots Arch and the Energetics
of Human Locomotion
Sarah M. Stearne1, Kirsty A. McDonald1, Jacqueline A. Alderson1, Ian North2,
Charles E. Oxnard3 & Jonas Rubenson1,4
The energy-sparing spring theory of the foot’s arch has become central to interpretations of the foot’s
mechanical function and evolution. Using a novel insole technique that restricted compression of
the foot’s longitudinal arch, this study provides the rst direct evidence that arch compression/recoil
during locomotion contributes to lowering energy cost. Restricting arch compression near maximally
(~80%) during moderate-speed (2.7 ms1) level running increased metabolic cost by + 6.0% (p < 0.001,
d = 0.67; unaected by foot strike technique). A simple model shows that the metabolic energy saved
by the arch is largely explained by the passive-elastic work it supplies that would otherwise be done by
active muscle. Both experimental and model data conrm that it is the end-range of arch compression
that dictates the energy-saving role of the arch. Restricting arch compression had no eect on the cost
of walking or incline running (3°), commensurate with the smaller role of passive-elastic mechanics in
these gaits. These ndings substantiate the elastic energy-saving role of the longitudinal arch during
running, and suggest that arch supports used in some footwear and orthotics may increase the cost of
running.
Running has classically been characterized by the spring-mass paradigm1,2. During running, gravitational poten-
tial and kinetic energy is temporarily stored as elastic strain energy, primarily in tendons, during the rst half of
stance and subsequently returned in the second half of stance, helping to propel the body forward and upward.
is form of elastic energy reduces the metabolic cost of running by sparing mechanical work otherwise required
by active muscle tissue3,4.
Ker and colleagues5, identied the longitudinal arch of the foot as an elastic storage-return mechanism. ese
authors estimated, by simulating the loads experienced during running in cadaver feet, that approximately 17% of
the mechanical work of running could be stored and returned by the foot’s arch as it undergoes compression and
recoil over the stance phase5 and that this contributes to the economy of running. is theory has subsequently
been adopted in numerous investigations ranging from analyses of running mechanics6, the evolution of human
running7, and footwear design8.
Since the initial study by Ker et al.5 the hypothesis that the foot is an energy-saving spring has never been
tested directly during locomotion and it is unknown to what extent the compression, and subsequent storage and
return of elastic energy in the foot’s longitudinal arch aects the metabolic cost of locomotion. Here we propose
that the metabolic energy saved by the arch spring is a function of the amount of positive mechanical work it
supplies passively (non-metabolically) and the cost of performing that work had it instead been done by active
muscle requiring metabolic energy.
We test this hypothesis experimentally using custom-manufactured orthotic insoles designed to restrict arch
compression and thus reduce arch elastic work. To test our predictions about the eect of arch strain on locomo-
tor cost, we used orthotic insoles to vary arch strain during walking and running at dierent inclines and foot
strike types (rearfoot strike [RFS] vs forefoot strike [FFS]).
Two separate custom insoles were designed for each participant. e rst insole was designed to restrict arch
compression near-maximally compared to that during shod running (Full Arch Insole; FAI) and the second
was designed to restrict compression by approximately 50% during stance (Half Arch Insole; HAI). Despite the
nearly two-fold dierence in arch compression between the HAI and FAI, we hypothesized that both would
result in a comparable reduction in elastic energy storage/return during running and thus a similar increase in
1School of Sport Science, Exercise and Health, The University of Western Australia, Perth, WA, 6009, Australia.
2Willetton Podiatry, Willetton, WA, 6155, Australia. 3School of Anatomy, Physiology and Human Biology, The
University of Western Australia, Perth, WA, 6009, Australia. 4Biomechanics Laboratory, Department of Kinesiology,
The Pennsylvania State University, University Park, PA, 16802, USA. Correspondence and requests for materials
should be addressed to J.R. (email: jonas@psu.edu) or S.M.S. (email: sarah.stearne@iinet.net.au)
Received: 02 June 2015
Accepted: 19 November 2015
Published: 19 January 2016
OPEN
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Scientific RepoRts | 6:19403 | DOI: 10.1038/srep19403
metabolic cost. It is expected that relatively little elastic energy will be stored in the rst 50% of arch compression
based on the non-linear nature of the arch compression-elastic energy relationship identied by Ker et al.5 (see
Online Supplementary Material Fig. S4). Given the modest arch loads at the prescribed testing speed we expected
increases in the energy cost of level running of ~10% based on the arch load vs. energy storage data of Ker et al.5
and our model for metabolic energy expenditure. In this context, the FAI and HAI were designed to test if the pre-
dicted increase in metabolic cost was associated specically with a reduction in the arch elastic energy as opposed
to a more general gait modication linked to the degree of arch restriction.
Compared to level running, we predicted that restricting arch compression during walking and incline run-
ning would not have as pronounced of an impact on metabolic cost. Walking involves lower loads9, is a pendular
as opposed to a spring-mass gait, and relies more on the arch windlass mechanism10 as opposed to an arch spring
mechanism. We consequently hypothesized the arch spring mechanism has a smaller energy-saving eect in
walking compared to running and tested this by restricting arch compression during walking using the FAI.
During incline running, the loads experienced are similar to level running and the arch is able to store and return
elastic energy11. However, the additional positive mechanical work production required to raise the center of mass
vertically during incline running cannot be generated from previously stored elastic energy11. We therefore pre-
dicted that the energetic cost associated with limiting the arch spring relative to the total cost of incline running
would be smaller than that of level running. Finally, we hypothesized that restricting arch compression would
have a greater eect on the energy cost of level running in habitual FFS runners compared with habitual RFS
strike runners, suggesting greater reliance on the arch spring for reducing running costs.
To test these questions we measured metabolic cost (oxygen consumption), arch compression using
three-dimensional (3D) motion capture, and ground reaction forces and joint kinetics on an instrumented tread-
mill. Using this data we estimated the elastic energy stored and returned by the arch, the total mechanical work of
locomotion and the metabolic cost of restricting arch elastic energy storage/return.
Results
Arch Elastic Energy and Metabolic Cost in Level Running. Arch compression (navicular displace-
ment) was signicantly reduced in the insole conditions compared with the minimal shoe-only level running. A
61.4 ± 33.4% reduction in arch compression was observed with the HAI (p < 0.001, d = 1.22) and 78.9 ± 24.7%
reduction when the FAI was worn (p < 0.001, d = 1.46; Fig.1a and Online Supplementary Fig. S2). Estimated
arch elastic energy return per step was also reduced (81.5 ± 26.4% and 97.2 ± 5.4% reductions in the HAI and
FAI, respectively; both p < 0.001, HAI d = 1.53 and FAI d = 1.72; Fig.1b) and per distance traveled (HAI and
FAI both p < 0.001, HAI d = 1.55 and FAI d = 1.72; Table1). FAI arch compression restriction was signicantly
greater than the HAI condition (p = 0.032, d = 0.60; Fig.1a; Table1) but estimated elastic energy return was not
(p = 0.121, d = 0.58; Table1).
e model-predicted increase in metabolic cost of transport (Earch) as a result of reducing arch compression
was statistically signicant in both the HAI (p = 0.001, d = 0.77) and FAI (p = 0.004, d = 0.72) conditions com-
pared with minimal shoe-only level running (Table1, Fig.2b). e metabolic cost of HAI and FAI level running
resulting from our model were not signicantly dierent from one another (p = 0.920, d = 0.01; Table1, Fig.2b).
In line with the modeled metabolic costs, both the HAI and FAI resulted in a statistically signicant increase
in the experimentally-observed metabolic cost of transport during level running (HAI p = 0.012, d = 0.53; FAI
p < 0.001, d = 0.67; Table1, Fig.2a). As with the modeled costs, there was no statistical dierence in the observed
experimental metabolic cost between the HAI and FAI conditions (p = 0.211, d = 0.18). e modeled and exper-
imental metabolic costs were not signicantly dierent from one another for either the HAI or FAI (Table1). e
insoles had a small non-signicant eect on total limb mechanical work (ANOVA main eect p = 0.121; Table1).
Arch Elastic Energy and Metabolic Cost in Walking and Incline Running. Compared to the mini-
mal shoe-only condition, the insole (FAI) reduced arch compression during walking by 82.4 ± 21.1% (p < 0.001,
d = 1.13) and during incline running by 68.5 ± 30.6% (p = 0.001, d = 1.13; Fig.1a). e estimated arch elastic
energy return per step in both conditions was signicantly reduced (96.3 ± 6.9% and 91.6 ± 15.9% reductions
per step in walking and incline running, respectively; both p < 0.001, walking d = 1.12; incline running d = 1.53;
Fig.1b). e model-predicted metabolic cost of transport in FAI walking was not statistically greater compared
to the minimal shoe-only condition (p = 0.131, d = 0.25; Fig.2b, Table1). A statistically signicant increase in the
modelled metabolic cost of transport was calculated for FAI incline running over the minimal shoe-only condi-
tion (p = 0.025, d = 0.59; Fig.2b, Table1). e experimentally observed metabolic cost of transport was likewise
not aected during walking, nor was it aected in incline running (walking p = 0.950, d = 0.01; incline running
p = 0.164, d = 0.18; Table1, Fig.2a). e insoles had a non-signicant eect on the total limb mechanical work
of locomotion in walking and incline running (walking p = 0.782, d = 0.03; incline running p = 0.074, d = 0.23;
Table1).
Arch Elastic Energy and Metabolic Cost in Rearfoot vs Forefoot Running. Arch compression in
the minimal shoe-only level running condition was signicantly greater in FFS compared with RFS runners
(FFS 12.0 mm vs RFS 9.2 mm; p = 0.022, d = 1.10; Table1). However, the estimated arch elastic energy return
(p = 0.490, d = 0.35), total limb mechanical work (p = 0.181, d = 0.43) and metabolic cost of transport (p = 0.584.
d = 0.29) did not dier between foot strike groups in minimal shoe-only level running (Table1). is was also
true for FAI conditions between RFS and FFS runners (p = 0.483, p = 0.092, p = 0.568, respectively). Both the
modelled and experimental metabolic costs were not statistically dierent between foot strike groups in any of
the HAI and FAI conditions (all conditions p > 0.05; Table1).
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Discussion
By examining the eect of restricting compression of the foot’s longitudinal arch on the metabolic cost of loco-
motion, the present study provides direct evidence supporting the energy-sparing spring theory of the arch. Our
analyses and model generally support the hypothesis that the arch spring saves metabolic energy by reducing the
mechanical work that would otherwise need to be generated by active muscle (Fig.2). Indeed, the elevated met-
abolic cost of level running aer restricting arch compression near-maximally (~80%, FAI) and by ~60% (HAI)
was predicted within 1% and 2.5%, respectively, of the measured values based on the cost of replacing lost elastic
arch work with muscular work. e agreement between the modelled and experimental eect on the metabolic
cost of level running was remarkably robust across a nearly two-fold dierence in arch compression (FAI 10 mm
reduction in compression vs HAI 6.5 mm reduction; Fig.1a), strengthening the interpretation that the elevated
metabolic cost results specically from lost arch elastic energy. We propose that energy costs do not show a clearer
dierence between FAI vs HAI because elastic energy storage increases non-linearly with arch loading5, with the
majority of the elastic energy stored in the nal 25% of arch compression (Online Supplementary Material Fig. S4).
erefore, near equal amounts of arch elastic energy storage/return was removed in both the FAI and HAI condi-
tions (Fig.1b), resulting in a non-signicant dierence in the metabolic cost of running (Fig.2, Table1).
Figure 1. (a) Maximum arch compression (mm; mean ± S.E.M.) relative to arch height at minimal shoe-only
level running initial foot contact. (b) Estimated elastic energy (J kg1, mean ± S.E.M.) returned from the arch
of the foot in one step. *indicates signicantly dierent (p < 0.05) to the minimal shoe-only trial in the same
condition, ^indicates signicant dierence between the half arch insole (HAI) and full arch insole (FAI) (level
running only).
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e estimated reduction in the elastic energy return from the arch in the FAI level running condition equaled
8.8% of the total limb mechanical work of running, similar to the 6.0% increase in the gross locomotor cost (7.4%
net
V
O2). As expected, these values are lower than Ker et al.’s5 estimate of 17% due to our slower running speed
(2.7 m s1 compared to Ker et al.s 4.5 m s1) and therefore lower arch elastic energy storage/release and
Condition
Habitual
foot strike
Arch
compression
(mm)
Estimated elastic
energy returned from
the arch (J kg1m1)
Observed metabolic
cost of transport
(J kg1 m1)
Modelled metabolic
cost of transport
(J kg1 m1)
Total limb
mechanical work
(J kg1 m1)
WALK
Minimal shoe-only
RFS 5.9 ± 2.3 0.039 ± 0.032 3.95 ± 0.46 n/a 0.37 ± 0.05
FFS 7.4 ± 5.3 0.043 ± 0.043 4.06 ± 0.33 n/a 0.42 ± 0.08
Average 6.7 ± 4.1 0.041 ± 0.037 4.01 ± 0.39 n/a 0.40 ± 0.07
Full Arch Insole (FAI)
RFS 1.1 ± 5.1 0.004 ± 0.008 3.98 ± 0.50 4.17 ± 0.56 0.39 ± 0.10
FFS 2.2 ± 4.1 0.003 ± 0.008 4.03 ± 0.42 4.09 ± 0.55 0.38 ± 0.05
Average 0.7 ± 4.8* 0.003 ± 0.007* 4.01 ± 0.44 4.13 ± 0.54 0.39 ± 0.07
LEVEL RUN
Minimal shoe-only
RFS 9.2 ± 2.1§0.110 ± 0.034 4.59 ± 0.39 n/a 1.25 ± 0.11
FFS 12.0 ± 2.4§0.126 ± 0.055 4.48 ± 0.34 n/a 1.36± 0.18
Average 10.6 ± 2.6 0.118 ± 0.045 4.53 ± 0.36 n/a 1.31± 0.15
Half Arch Insole (HAI)
RFS 2.6 ± 4.2 0.017 ± 0.023 4.79 ± 0.38 4.78 ± 0.35 1.20 ± 0.09
FFS 5.7 ± 6.1 0.021 ± 0.045 4.69 ± 0.42 4.93 ± 0.51 1.36 ± 0.15
Average 4.1 ± 5.3*^ 0.019 ± 0.035* 4.74 ± 0.39* 4.86 ± 0.43* 1.28 ± 0.15
Full Arch Insole (FAI)
RFS 1.3 ± 6.1 0.002 ± 0.004 4.87 ± 0.50 4.83 ± 0.48 1.20 ± 0.14
FFS 2.5 ± 5.8 0.005 ± 0.013 4.74 ± 0.35 4.88 ± 0.50 1.33 ± 0.15
Average 0.6 ± 6.0*^ 0.004 ± 0.009* 4.81 ± 0.42* 4.85 ± 0.48* 1.27 ± 0.15
INCLINE RUN
Minimal shoe-only
RFS 9.1 ± 3.4 0.108 ± 0.055 5.88 ± 0.41 n/a 1.46 ± 0.18
FFS 11.9 ± 4.5 0.116 ± 0.057 5.66 ± 0.26 n/a 1.56 ± 0.17
Average 10.5 ± 4.1 0.112 ± 0.054 5.77 ± 0.35 n/a 1.51 ± 0.18
Full Arch Insole (FAI)
RFS 0.3 ± 7.7 0.013 ± 0.028 5.89 ± 0.43 6.04 ± 0.46 1.41 ± 0.19
FFS 5.4 ± 4.9 0.009 ± 0.016 5.78 ± 0.31 5.93 ± 0.26 1.53 ± 0.10
Average 2.5 ± 6.8* 0.011 ± 0.022* 5.83 ± 0.37 5.99 ± 0.37* 1.47 ± 0.16
Table 1. Arch and limb mechanics and energetics. Rearfoot strike (RFS), Forefoot strike (FFS), Average
(average of RFS and FFS), Half Arch Insole (HAI), Full Arch Insole (FAI). *Signicantly dierent from minimal
shoe-only within the same condition p < 0.05, §signicant dierence between RFS and FFS p < 0.05. ^Signicant
dierence between HAI and FAI within the same condition p < 0.05.
Figure 2. (a) Experimentally observed and (b) model-predicted percent change in the gross metabolic cost
of locomotion (mean ± S.E.M.) from the minimal shoe-only to insole trial across walking, level running and
incline running conditions. FAI = full arch insole, HAI = half arch insole. * indicates signicant (p < 0.05)
increase in metabolic energy cost [(a) experimental, (b) modeled] between the minimal shoe-only and insole
trial within the same condition.
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subsequent smaller arch compressive loads. If the contribution of the arch spring to the total mechanical cost of
running increases with speed, as the data from Ker et al.5 suggest, the arch may have an even more pronounced
role in reducing locomotor costs at faster running speeds. What makes the arch-spring such an effective
energy-saving mechanism? It is notable that the arch spring, unlike tendon structures (e.g. the Achilles ten-
don;12,13), achieves elastic energy recycling largely in absence of muscle activity. e distinction between this
passive and other primary active spring mechanisms (e.g. triceps surae/Achilles muscle-tendon-unit) is impor-
tant since the later requires metabolic energy to maintain tension in the spring (cost of force). In this regard, the
arch spring may be the most eective energy saving structure in the lower limb.
Despite conrming that arch compression is greater in FFS compared with RFS runners in the minimal shoe
only level run (p = 0.022; Table1), our hypothesis that forefoot runners would be more aected by restricting
arch compression was not supported. e lack of dierence in the metabolic cost resulting from the FAI between
foot strike groups was, however, predicted by our model. e similar model-predicted metabolic costs between
FAI running in RFS and FFS arose because of a non-signicant dierence in the reduction of arch elastic energy
storage/return between groups. ese ndings raise questions regarding dierences in arch compliance between
RFS and FFS runners, although additional analyses in these groups are required to assess arch material properties
in detail.
Our hypotheses that the arch-spring mechanism has a smaller eect on the energy cost of walking and incline
running were supported. For walking, the small energetic eect can be explained to a large extent by the smaller
role of arch elastic energy storage/return in normal gait (Fig.1b). It is also possible that the FAI increased midfoot
rigidity and thus may have improved the eectiveness of the plantar-exion torque,14,15 saving metabolic energy.
e percent increase in metabolic cost of FAI incline running computed from our model was smaller than that
of FAI level running but was nevertheless signicantly greater than the observed experimental eect. We do not
have a denite answer to explain the poorer agreement between the increase in metabolic cost and the predicted
increase in muscle work during incline FAI running. When running uphill the primary function of muscle is to
generate the positive mechanical work of raising the body vertically. erefore, it remains possible that replacing
lost passive-elastic energy recycling may be less important in incline running compared to level running, which
follows spring-mass mechanics.
Orthotic insoles and arch-support footwear are occasionally prescribed to runners to alter foot and lower
limb biomechanics and tissue loading. e ndings of this study suggest that certain arch supports may hin-
der the arch’s elastic energy storage and subsequently lead to an increase in running energy cost. A number of
studies have reported an increase in the energy cost of running when wearing orthotic insoles16–18, although this
eect may in part be due to added weight19. Perl et al.6 found a statistically signicant 3% increase in metabolic
cost when participants ran in traditional arch supporting running shoes compared with minimalist shoes, even
aer controlling for strike technique, shoe mass and stride frequency. e benets of using corrective orthotics
or footwear designed with signicant arch support should therefore be weighed against their possible eect on
running energetics. In contrast to running, our ndings suggest that using rigid supportive shoes or insoles that
prevent arch collapse are likely to have little energetic consequence during walking given the smaller reliance on,
and reductions in, arch elastic energy storage/return.
Finally, the evolution of the longitudinal foot arch is regarded as a key adaptation for obligate hominin biped-
alism20–24. Although the evolution of the arch is debated, recent fossil evidence suggest that Australopithecus
afarensis (~3.2 million years) possessed at least a partial longitudinal arch22. e functional signicance of the
longitudinal arch in the evolution of human bipedal gait has oen been attributed to the rigid mid-tarsal lever
system allowing eective plantar-exion during toe-o25,26. A complementary theory surrounding the evolution
of the longitudinal arch is that its spring like properties lower the energetic cost of endurance running5,7. Our
study provides support for the arch functioning as both a rigid lever in walking and an energy-sparing spring in
running. e insoles had no eect on the metabolic cost of walking despite restricting ~80% of arch compression.
e absence of any energetic dierence might result, in part, because the insoles enhanced the eect of midfoot
rigidity in walking. On the other hand, restricting the arch’s spring function in level running resulted in a clear
increase in metabolic cost. Further, that we only observed an energetic consequence of arch restriction during
level running and not incline running may oer added insight into the movement behavior and environment of
early Homo. e landscape inhabited by early Homo was invariably not limited to horizontal ground, although
given that the arch only provided an energetic advantage during level and not incline running begs questions of
how landscape inuenced the evolution of the human foot and bipedal gait and how early Homo navigated this
landscape.
Methods
Participants. Eight habitual RFS and nine habitual FFS male runners were included in the study. e par-
ticipants had not experienced any lower limb injuries in the six months prior to testing nor presented with any
pre-existing gait abnormalities. No signicant dierences in measured physiological variables, as determined by
a series of independent t-tests, existed between foot strike groups (age- RFS 25.5 ± 4.4 years, FFS 27.6 ± 3.4 years;
height- RFS 185.3 ± 6.9 cm, FFS 181.8 ± 4.8 cm; weight- RFS 79.4 ± 6.8 kg, FFS 75.7 ± 5.9 kg; weekly running
distance- RFS 39.4 ± 21.1 km, FFS 42.2 ± 36.0 km; mean ± SD). Participants did not regularly wear prescriptive
orthotic insoles. Included participants were deemed to have normal foot structure as determined by the Foot
Posture Index27 (FPI) (RFS 1.4 ± 1.4, FFS 1.0 ± 2.8). Measured foot variables did not dier between RFS and FFS
groups; foot length- RFS 277.0 ± 11.4 mm, FFS 272.4 ± 6.1 mm; resting arch height (from sole to navicular tuber-
osity)- RFS 50.3 ± 7.3 mm, FFS 49.5 ± 9.5 mm; and Achilles tendon moment arm (perpendicular distance from
lateral malleolus to Achilles)- RFS 45.3 ± 4.1 mm, FFS 46.8 ± 5.4 mm. All FPI and foot anthropometric measure-
ments were taken by a single experienced clinician (I.N.). Participants provided written, informed consent prior
to inclusion in the study. All procedures were approved by e University of Western Australia Human Research
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Ethics Committee (Approval ID: RA/4/1/4541) and the study was carried out in accordance with the approved
guidelines.
Custom Arch-restricting Insoles. Two pairs of custom-made foot insoles were manufactured for each par-
ticipant from 3D scans of the participants’ feet in a non-weight bearing neutral sub-talar joint position (ScanAny,
Orthotech laboratories, Blackburn, Melbourne). Both insoles were made with the following specication; four
millimeter polypropylene, high density arch ll (shore value ~350–400), four degree intrinsic rear foot grind, a
balanced fore foot, maximum arch congruency and the heel ground to less than one millimeter such that heel-toe
drop was deemed negligible. One insole was designed to ll the participants arch when the foot was positioned in
a neutral non-weight bearing position, theoretically allowing minimal arch compression during locomotion (full
arch insole; FAI). e second insole had a peak arch height ve millimeters lower than the FAI, with the aim of
allowing ~50% arch compression (half arch insole; HAI). e ve millimeter reduction was chosen based on pilot
work and arch compression data from Perl et al.6 and Ker et al.5. Participants were provided the insoles two weeks
prior to testing to become familiar with wearing them.
Testing Conditions. New Balance Minimus road MR00 shoes were provided to all participants to wear for
testing (approx. weight 180 grams, zero heel-toe drop, no medial arch support and a uniform EVA midsole).
Pockets lled with lead weights were axed to the laces of both shoes in order to standardize foot weight across
all shoe and insole conditions. We chose a minimal shoe as a control condition in order to standardize non-insole
eects as much as possible (e.g. eect of shoe sole cushioning28). Prior to testing, participants completed a ve
minute warm-up on a force-plate instrumented split belt treadmill (Bertec Corporation, Columbus OH, USA)
at a slow run.
Testing comprised of the following conditions; i) shoe-only walk, ii) FAI walk, iii) minimal shoe-only level
run, iv) HAI run, v) FAI run, vi) minimal shoe-only incline run, and vii) FAI incline run. All trials were com-
pleted on the force-plate instrumented treadmill and the order of conditions randomized to prevent any fatigue
or order eects. To further ensure fatigue and trial order were not inuencing results, the rst condition was
repeated at the end of the testing session. Participants reported minimal discomfort and no conscious change in
their running technique whilst wearing the insoles (see Online Supplementary Table S3 for questionnaire results).
All running conditions were performed using the runner’s habitual foot strike technique as conrmed by a
sagittal high speed video camera (Casio EXILIM EX-F1, Casio Computer Co. LTD., Shibuya-ku, Tokyo; 300 Hz).
In accordance with the literature, a RFS was dened when the heel of the shoe made initial contact with the
ground and a FFS dened when the ball of the foot made rst contact29,30. A standardized walking speed of
1.1 ms1 (representing a comfortable speed on the treadmill and within the range of the participants’ pilot tested
preferred walking speeds) was selected to minimize arch compression and subsequently elastic energy contribu-
tion. To ensure our results were not aected by walking speed, a sub-set of participants (n = 8) also performed the
minimal shoe-only and FAI walk at their individually preferred walking speed (average 1.3 ± 0.1 ms1). Similar
metabolic cost results were found in the preferred walking speed and the 1.1 ms1 walking trials (13.6 ± 1.3 vs
13.1 ± 1.5 ml kg1 min1, respectively; p = 0.190), including a similar minimal eect of the FAI on the metabolic
cost of walking. All running trials were performed at 2.7 ms1 (level and incline trials were performed at the same
velocity to control for any speed eects). Pilot testing on a sub-set of participants (n = 8) revealed that running at
faster speeds (3.5 ms1) caused the insoles to compress and thus limited the eect of the insole on arch compres-
sion, likely due to the higher joint loading at this speed. During incline trials the treadmill was set at three degrees
(although not specically instructed to do so, all runners maintained their level habitual foot strike technique).
is inclination was selected to increase the mechanical work and metabolic cost but within aerobic levels as
faster speed/incline combinations risked reliance on anaerobic metabolic pathways31. e chosen running speed
thus represents an optimized speed to test the eect of the insoles in both level and incline conditions.
Metabolic Cost. Participants were asked to abstain from caeine on the day of the testing and to not eat in
the two hours prior to arriving at the laboratory. Expired gasses were collected during rest (standing) and walk-
ing/running trials. Participants were required to breathe into a two-valve mouthpiece connected via two light-
weight exible tubes to a computerized oxygen and carbon dioxide gas analysis system [Morgan ventilation
monitor (Morgan, Reinham, Kent, UK); oxygen and carbon dioxide analyzers (Ametek SOV S-3A11/Ametek
COV CD-3 A, Applied Electrochemistry, Ametek, Pittsburgh, PA)]. e ventilometer and gas analyzers were
calibrated before and immediately aer each test using a one liter syringe pump and reference gas mixtures,
respectively (BOC Gases, Chatswood, Australia). Each treadmill condition was performed until the participant
reached a steady state of oxygen consumption (
V
O2) aer which a further minute of data was collected for anal-
ysis.
V
O2 data was collected for a minimum period of four minutes as per the Australian Institute of Sport
national testing battery for runners32. During the incline conditions, blood lactate concentration levels were
determined (Lactate-Pro, Arkray, LT-1710, Kyoto, Japan) aer steady state was reached to ensure participants
were exercising aerobically (below their previously determined lactate threshold and the
V
O2 at which this
threshold occurred [see Online Supplementary Material]).
In order to compare metabolic and mechanical energy measures,
V
O2 was converted to a metabolic energy cost
of transport (J kg1 m1) by using an energy equivalent of 20.1 J ml1 O2 and dividing by locomotor speed (m s1)
and body mass (kg).
Arch Compression and 3D Joint Kinematics and Kinetics. We used a custom 3D kinematic foot
model to estimate arch compression, outlined briey here, and in detail in the Online Supplementary Material.
First, a previously established lower body model was used to dene a rearfoot segment and ankle kinematics33.
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Retro-reective markers were axed to the lower limbs in accordance with Besier et al.33, with additional markers
placed on the navicular tuberosity and distal phalanx of the rst metatarsal (Fig.3). e shoe upper was modied
with ve marker ‘windows’ coinciding with the marker positions, allowing markers to be placed directly on the
foot and remain visible. To ensure marker positions remained unchanged aer removing shoes, all foot markers
were detachable by a magnetic base that did not change location. is resulted in the markers being slightly
oset from the anatomical landmark. e frame-to-frame location of the marker relative to the anatomical land-
mark deviated minimally (< 1 mm) within their respective rigid segments during running. e location of the
functionally relevant anatomical landmarks were identied using a six marker wand in static pointer trials and
expressed in the rearfoot or forefoot anatomical coordinate systems (see Online Supplementary Material). A
small marker was also placed on the medial aspect of the insole in line with the maximum insole height and hence
the maximum arch height.
Motion of the retro-reective markers were tracked using a ten-camera near infrared Vicon T-series 3D
motion capture system (T40S, 250 Hz; Oxford Metrics, Oxford, UK) and sagittal plane high-speed video (300 Hz).
Six consecutive right leg strides from the nal minute of data collection were selected for analysis. Arch height
was dened as the distance of the navicular marker relative to the base of the foot and tracked continuously
throughout the stride (see Online Supplementary Material). Arch height at initial foot contact during the mini-
mal shoe-only level run was used as a reference height for each condition. Arch compression was dened as the
dierence between the reference height and the minimum arch height during stance in each condition.
Inverse dynamics (net joint moments and joint reaction forces) were computed for the ankle in accord-
ance with Besier et al.33, as well as for the MTP joint (sagittal plane only), using Vicon BodyBuilder soware
(Oxford Metrics, Oxford, UK). Ground reaction forces (GRFs) from the instrumented treadmill were recorded at
Figure 3. Right foot medial view illustrating (a) foot marker positions used to compute foot and arch kinematics.
e white markers are physical reective markers, the large red circles are pointed landmarks and the small red
circles represent the computed joint centers. e inset illustrates the virtual landmarks relative to the skeleton, the
sole axis and the navicular displacement measure. e inset gure was generated using OpenSim 3.0 (https://simtk.
org/home/opensim), freely available open source musculoskeletal modeling soware42. (b) example of the arch
compression-restricting insole; image displayed is the Full Arch Insole (FAI); photograph by S.M.S. (c) Footwear
illustrating marker ‘windows, the insole marker and weight pouch used for matching total shoe and insole weight;
photograph by S.M.S. MP1 = rst metatarsophalangeal joint, MP5 = h metatarsophalangeal joint.
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2,000 Hz, and synchronized with the kinematic data using a Vicon MX-Net control box (Oxford Metrics, Oxford,
UK). All marker trajectories were ltered using a zero-lag 4th order low pass Butterworth lter with cut-o fre-
quencies typically at 14 Hz, determined by a custom residual analysis algorithm for each participant (MATLAB,
e MathWorks Inc., USA). GRFs were ltered at the same cut-o frequency as the kinematic data to mitigate any
artefacts in joint moments arising due to un-accounted segment acceleration34,35.
Arch Elastic Energy and Total Mechanical Work of Locomotion. Our hypotheses are based on the
premise that the insoles impede the storage of elastic energy in the arch and its subsequent ability to contribute to
total mechanical work. How these variables changed between conditions was estimated using a simple model to
predict arch elastic energy storage (Fig.4) and a force plate approach to measure total mechanical limb work of
locomotion36. e arch energy storage model was based on the compressive load-energy storage function estab-
lished by Ker et al.5 and calculations of the participants’ individual ankle compressive loads (inverse dynamics)
and arch compression (high-speed motion capture) (Fig.4; see Online Supplementary Material). Using these
data, we developed subject-specic arch load-displacement curves that permitted an estimate of the arch elastic
energy storage during each trial from their arch compression values (Figs1a and 4). Arch elastic energy return
(Warch
+) was predicted based on a hysteresis value of 22% from Ker et al.5. e force plate approach followed the
individual limb work (Wlimb
+) calculations described by Donelan et al.36, whereby limb powers were computed as
the dot product of the force acting on the limb and the body center of mass velocity, and subsequently integrated
with respect to time. Center of mass velocities were computed by time integrating the center of mass accelera-
tions, which were determined from the sum of the ground reaction forces. Both the arch elastic energy and limb
work calculations are described in detail in the Online Supplementary Material.
Modelled Arch Metabolic Energy Saving. e eect of arch elastic energy on the metabolic cost of loco-
motion was predicted by estimating the amount of positive arch elastic work (energy return) that was eliminated
aer restricting arch compression, and the cost of replacing lost mechanical work were it to be performed by
active muscle. is was computed as:
=(∆−∆)
()
+++
EWW1
arch arch limb
where Earch is the modelled additional metabolic energy (expressed as a cost of transport; J kg1 m1) after
restricting arch compression, ∆Warch+ is the dierence in the amount of returned arch elastic energy between
the minimal shoe-only trial and the corresponding insole trial for level running, incline running and walking (as
computed from our model; J kg1 m1). Although they were found to be small (Table1), we incorporated any
dierences in positive limb mechanical work between shoe-only and insole conditions (∆Wlimb+) as these could
aect metabolic cost. Finally, η
+ is the muscular eciency of performing positive work. A constant theoretical
muscle eciency of 0.25 was used for all trials. is assumed that all the lost arch elastic energy was replaced
Figure 4. (a) Arch elastic strain energy – ankle compressive load relationship adapted from Ker et al.5 used
to estimate arch strain energy from the participant’s maximum ankle joint compressive load (see Online
Supplementary Material). (b) Subject specic load-displacement curve used to predict stored arch elastic energy
during dierent conditions from measured arch compression. e subject-specic load-displacement curve
was established using the maximum arch compression from the participant’s trials and the corresponding ankle
compressive load, and by adjusting the optimized control point so that the area under the curve (elastic energy
storage) matched the estimated energy storage from (a).
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solely by positive muscle ber work functioning at a high eciency37. For comparison, (presented in the Online
Supplementary Material Table S2) we also made predictions using the locomotor mechanical eciency computed
from the minimal shoe-only trial for each condition (walking, level running and incline running).
Statistics. General linear model two-way repeated measures split-plot ANOVAs were performed to deter-
mine the eect of the custom insoles and foot strike technique on the following variables; arch compression,
estimated arch elastic energy storage, modeled and experimental metabolic cost, and total limb mechanical work
of locomotion. e between subject factors were habitual foot strike technique (RFS and FFS) and the within
subjects factors were minimal shoe-only, HAI (level running only) and FAI. e signicance level was p < 0.05
for ANOVA analyses. 3 × 2 ANOVAs were conducted for level running and 2 × 2 ANOVAs for walking and
incline running. In the 3 × 2 ANOVAs the location of the signicant main eect was determined using a post-hoc
pairwise comparison with a Bonferroni adjustment for multiple comparisons. Cohens d eect sizes38 were cal-
culated and interpreted using the eect scale; small (0.2); moderate (0.5); large (0.8). A series of paired samples
t-tests were conducted between RFS and FFS groups in the minimal shoe-only and FAI conditions to determine
if foot strike had an eect. Paired samples t-tests were also conducted to compare modelled versus experimentally
observed increases in metabolic cost of transport.
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Acknowledgements
The authors would like to acknowledge Orthotech laboratories (Blackburn, Melbourne, Australia) for the
manufacture and supply of the insoles used in this study, Robert Day for his assistance testing the insole material
properties, and Tony Roby for constructing the magnetic marker set and the insole material testing piece. e
authors would like to thank Rodger Kram, Daniel Lieberman and Nicholas Brown for their helpful suggestions
and critique of this work, and Robert Eckhardt and Owen Lovejoy for information pertaining to the evolution of
the human foot.
Author Contributions
S.M.S. contributed to the conception and design of the experiment, was the primary author involved in
the collection and analysis of data and contributed critically to data interpretation, draing and editing the
manuscript and figure preparation. K.A.M. contributed to the design of the experiment, data collection,
processing and interpretation, and editing the manuscript. J.A.A. contributed to the conception and design of the
experiment, the analysis and interpretation of data and editing the manuscript. I.N. contributed to the design of
the experiment, data collection and editing the manuscript. C.E.O. contributed to data interpretation and editing
the manuscript. J.R. contributed to the conception and design of the experiment, the collection, analysis and
interpretation of data, draing and editing the manuscript and gure preparation.
Additional Information
Supplementary information accompanies this paper at http://www.nature.com/srep
Competing nancial interests: e authors declare no competing nancial interests.
How to cite this article: Stearne, S. M. et al. e Foots Arch and the Energetics of Human Locomotion. Sci. Rep.
6, 19403; doi: 10.1038/srep19403 (2016).
is work is licensed under a Creative Commons Attribution 4.0 International License. e images
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unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license,
users will need to obtain permission from the license holder to reproduce the material. To view a copy of this
license, visit http://creativecommons.org/licenses/by/4.0/

Supplementary resources (2)

Data
January 2016
Sarah Michelle Stearne · Kirsty A McDonald · Jacqueline A. Alderson · Ian North · Jonas Rubenson
Data
January 2016
Sarah Michelle Stearne · Kirsty A McDonald · Jacqueline A. Alderson · Ian North · Jonas Rubenson
... The plantar fascia also plays an important role in the energetics of the foot during running. With deflection of the foot arch, the plantar fascia and associated deep ligaments of the foot are strained and subsequently return around 6% to 17% of the total mechanical work of running (Ker et al., 1987;Stearne et al., 2016). There is emerging evidence that a FFS pattern may induce greater deflection of the arch than RFS (Ker et al., 1987;Chao et al., 2011;Stearne et al., 2016), thus further increasing the peak strain within these structures. ...
... With deflection of the foot arch, the plantar fascia and associated deep ligaments of the foot are strained and subsequently return around 6% to 17% of the total mechanical work of running (Ker et al., 1987;Stearne et al., 2016). There is emerging evidence that a FFS pattern may induce greater deflection of the arch than RFS (Ker et al., 1987;Chao et al., 2011;Stearne et al., 2016), thus further increasing the peak strain within these structures. As such, a FFS pattern has greater potential to store and return elastic strain energy via the passive components of the arch than a RFS pattern, although this has yet to be determined. ...
Article
Full-text available
Recent studies have suggested that 95% of modern runners land with a rearfoot strike (RFS) pattern. However, we hypothesize that running with an RFS pattern is indicative of an evolutionary mismatch that can lead to musculoskeletal injury. This perspective is predicated on the notion that our ancestors evolved to run barefoot and primarily with a forefoot strike (FFS) pattern. We contend that structures of the foot and ankle are optimized for forefoot striking which likely led to this pattern in our barefoot state. We propose that the evolutionary mismatch today has been driven by modern footwear that has altered our footstrike pattern. In this paper, we review the differences in foot and ankle function during both a RFS and FFS running pattern. This is followed by a discussion of the interaction of footstrike and footwear on running mechanics. We present evidence supporting the benefits of forefoot striking with respect to common running injuries such as anterior compartment syndrome and patellofemoral pain syndrome. We review the importance of a gradual shift to FFS running to reduce transition-related injuries. In sum, we will make an evidence-based argument for the use of minimal footwear with a FFS pattern to optimize foot strength and function, minimize ground reaction force impacts and reduce injury risk.
... By contrast, the hallux of the human foot is aligned in parallel with the other four digits; as such, the prehensile function is not afforded. In addition, the human foot exhibits unique morphological features, such as a longitudinal arch with an enlarged, robust calcaneus, and a well-developed plantar aponeurosis, which allows mechanical energy to be stored in the form of elastic energy and successively released during the contact of each foot (Ker et al., 1987;Bramble and Lieberman, 2004;Stearne et al., 2016). Additionally, a curved transverse arch, which can increase the stiffness of the human foot, has been suggested recently (Venkadesan et al., 2020). ...
... The evolution of the longitudinal arch is generally regarded as an adaptation for efficient bipedal locomotion in humans; the flattening of the arch and the elongation of the well- Frontiers in Bioengineering and Biotechnology | www.frontiersin.org January 2022 | Volume 9 | Article 760486 developed plantar aponeurosis in humans allow mechanical energy to be stored in the form of elastic energy, which is successively released during locomotion (Ker et al., 1987;Stearne et al., 2016). Additionally, the present study confirmed that the human foot was more capable of storing more elastic energy during axial loading compared with the chimpanzee foot. ...
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To comparatively investigate the morphological adaptation of the human foot for achieving robust and efficient bipedal locomotion, we develop three-dimensional finite element models of the human and chimpanzee feet. Foot bones and the outer surface of the foot are extracted from computer tomography images and meshed with tetrahedral elements. The ligaments and plantar fascia are represented by tension-only spring elements. The contacts between the bones and between the foot and ground are solved using frictionless and Coulomb friction contact algorithms, respectively. Physiologically realistic loading conditions of the feet during quiet bipedal standing are simulated. Our results indicate that the center of pressure (COP) is located more anteriorly in the human foot than in the chimpanzee foot, indicating a larger stability margin in bipedal posture in humans. Furthermore, the vertical free moment generated by the coupling motion of the calcaneus and tibia during axial loading is larger in the human foot, which can facilitate the compensation of the net yaw moment of the body around the COP during bipedal locomotion. Furthermore, the human foot can store elastic energy more effectively during axial loading for the effective generation of propulsive force in the late stance phase. This computational framework for a comparative investigation of the causal relationship among the morphology, kinematics, and kinetics of the foot may provide a better understanding regarding the functional significance of the morphological features of the human foot.
... This might be because the PA springs contributed toward transfer of the energy absorbed at the MTP joint to generate positive work at the midtarsal joint during walking. The human foot possesses a longitudinal arch with the PA spanning its plantar side, allowing stretch and recoil of the PA springs to store and release mechanical energy for generation of efficient locomotion (Ker et al., 1987;Kim and Voloshin, 1995;Stearne et al., 2016). Our study, which was based on inverse dynamics using the proposed multi-segment foot model, clarified the detailed energy recovery mechanism embedded in the human foot that possibly contributes to the reduced energy cost in human bipedal walking. ...
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Kinetic multi-segment foot models have been proposed to evaluate the forces and moments generated in the foot during walking based on inverse dynamics calculations. However, these models did not consider the plantar aponeurosis (PA) despite its potential importance in generation of the ground reaction forces and storage and release of mechanical energy. This study aimed to develop a novel multi-segment foot model incorporating the PA to better elucidate foot kinetics. The foot model comprised three segments: the phalanx, forefoot, and hindfoot. The PA was modeled using five linear springs connecting the origins and the insertions via intermediate points. To demonstrate the efficacy of the foot model, an inverse dynamic analysis of human gait was performed and how the inclusion of the PA model altered the estimated joint moments was examined. Ten healthy men walked along a walkway with two force plates placed in series close together. The attempts in which the participant placed his fore- and hindfoot on the front and rear force plates, respectively, were selected for inverse dynamic analysis. The stiffness and the natural length of each PA spring remain largely uncertain. Therefore, a sensitivity analysis was conducted to evaluate how the estimated joint moments were altered by the changes in the two parameters within a range reported by previous studies. The present model incorporating the PA predicted that 13%–45% of plantarflexion in the metatarsophalangeal (MTP) joint and 8%–29% of plantarflexion in the midtarsal joints were generated by the PA at the time of push-off during walking. The midtarsal joint generated positive work, whereas the MTP joint generated negative work in the late stance phase. The positive and negative work done by the two joints decreased, indicating that the PA contributed towards transfer of the energy absorbed at the MTP joint to generate positive work at the midtarsal joint during walking. Although validation is limited due to the difficulty associated with direct measurement of the PA force in vivo, the proposed novel foot model may serve as a useful tool to clarify the function and mechanical effects of the PA and the foot during dynamic movements.
... This is due to the arch-like structure of the human foot in which the midfoot bones are elevated by the well-developed plantar aponeurosis connecting from the calcaneal tuber to the bases of the proximal phalanges. Therefore, the human foot has a larger capacity to be flattened due to axial loading, and the plantar aponeurosis is stretched to store elastic energy [35,36]. On the other hand, the structure of chimpanzee and gorilla feet is more flattened in an unloaded neutral condition. ...
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The human foot is considered to be morphologically adapted for habitual bipedal locomotion. However, how the mobility and mechanical interaction of the human foot with the ground under a weight-bearing condition differ from those of African great apes is not well understood. We compared three-dimensional (3D) bone kinematics of cadaver feet under axial loading of humans and African great apes using a biplanar X-ray fluoroscopy system. The calcaneus was everted and the talus and tibia were internally rotated in the human foot, but such coupling motion was much smaller in the feet of African great apes, possibly due to the difference in morphology of the foot bones and articular surfaces. This study also found that the changes in the length of the longitudinal arch were larger in the human foot than in the feet of chimpanzees and gorillas, indicating that the human foot is more deformable, possibly to allow storage and release of the elastic energy during locomotion. The coupling motion of the calcaneus and the tibia, and the larger capacity to be flattened due to axial loading observed in the human foot are possibly morphological adaptations for habitual bipedal locomotion that has evolved in the human lineage.
... According to the study a higher foot arch results in a higher vertical jump [21] . Foot arch height may help utilize the elastic energy stored by the MTP joint during the stance phase while sprinting [22,23,24] . A player with high arch is able to store more elastic energy in the tendons during the squatting portion of a jump in order to use that energy to achieve a greater velocity at takeoff, thus resulting in higher jump. ...
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Introduction: Basketball is a game of speed and vertical jump which involves the rebound, dribble, blocks and jump shots. The players improve their game performance by repeated practicing of jumping and shooting during the practice sessions. Jumping is the most prevalent action performed by basketball players. To perform the action of jump coordination from several muscles in arm, trunk and legs are required. The vertical jump height plays a vital role in positioning of the players in basketball. The foot anthropometry and other morphological factors affect vertical jump height. Therefore, the study was done to identify the relationship between foot variables and jump performance in collegiate basketball players. Materials/Methods: 30 basketball players were selected using convenient sampling method. Body Mass Index, Foot length, Toe length and Arch height were measured for each player using inch tape and weighing machine. Each player was asked to perform vertical jump test thrice and mean value was noted. Results: Greater jump performance can be achieved with taller stature, lower body weight, minimal foot length, longer toes and greater arch height. The correlation between body weight and jumping height shows p value 0.45 states that weight has negative correlation with vertical jump, whereas body height has a positive correlation with vertical jump with p value 0.73 states that taller stature results in greater jump performance. Foot length and jumping height has a negative correlation with p value 0.74 states that high cost of energy required to raise heels during jump cause a lesser jump performance. However, toe length has a positive correlation with vertical jump height with p value 0.07 stating that longer toes allows more time of contact with the ground creating a greater acceleration due to ground reaction force. Arch height also has a strong positive relation with jumping height with p value 0.00001 states that a high arch is able to store more elastic energy in the tendons during squatting position of jump enabling to use that energy at the takeoff, resulting in a higher jump. Conclusions: The result of the study showed that these foot variables contribute in selection of position of players in game strategy for better performance in the game.
... The resulting trajectory is characterized by a marked clearance and an emphasized heel-strike to comply with requirement #3. In fact, in humans, the heel-strike to toe-off movement has an important role, widely studied in literature: the foot arches compliance reduces metabolic energy consumption during locomotion, help balance and, consequently, improve stability (Stearne et al., 2016). Most importantly, this approach is also beneficial to the safety of the patient because it is meant to avoid the potential hazard caused by accidental stumbling (requirements #3 and #7). ...
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For decades, powered exoskeletons have been considered for possible employment in rehabilitation and personal use. Yet, these devices are still far from addressing the needs of users. Here, we introduce TWIN, a novel modular lower limb exoskeleton for personal use of spinal-cord injury (SCI) subjects. This system was designed according to a set of user requirements (lightweight and autonomous portability, quick and autonomous donning and setup, stability when standing/walking, cost effectiveness, long battery life, comfort, safety) which emerged during participatory investigations that organically involved patients, engineers, designers, physiatrists, and physical therapists from two major rehabilitation centers in Italy. As a result of this user-centered process, TWIN's design is based on a variety of small mechatronic modules which are meant to be easily assembled and donned on or off by the user in full autonomy. This paper presents the development of TWIN, an exoskeleton for personal use of SCI users, and the application of user-centered design methods that are typically adopted in medical device industry, for its development. We can state that this approach revealed to be extremely effective and insightful to direct and continuously adapt design goals and activities toward the addressment of user needs, which led to the development of an exoskeleton with modular mechatronics and novel lateral quick release systems. Additionally, this work includes the preliminary assessment of this exoskeleton, which involved healthy volunteers and a complete SCI patient. Tests validated the mechatronics of TWIN and emphasized its high potential in terms of system usability for its intended use. These tests followed procedures defined in existing standards in usability engineering and were part of the formative evaluation of TWIN as a premise to the summative evaluation of its usability as medical device.
... These adaptations help reduce midfoot motion, the latter shown as a pronounced "midtarsal break" in apes 3,4 but present to some degree in humans 5 . The springy plantar aponeurosis present in modern day humans (Homo sapiens) reduces the cost of transport by cyclically storing and releasing energy during locomotion 6,7 . It is also considered a key component of the windlass mechanism 8 which contributes to the foot's ability to regulate stiffness 9,10 but muscle action also contributes especially during push-off 11 . ...
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The human foot is uniquely adapted to bipedal locomotion and has a deformable arch of variable stiffness. Intrinsic foot muscles regulate arch deformation, making them important for foot function. In this study we explore the hypothesis that normal daily activity in minimal footwear, which provides little or no support, increases foot muscle strength. Western adults wore minimal footwear for a six-month period (the “intervention” group). Foot strength, i.e., maximum isometric plantarflexion strength at the metatarsophalangeal joints, and foot biometrics were measured before and after the intervention. An additional group was investigated to add further insight on the long-term effects of footwear, consisting of Western adults with an average 2.5 years of experience in minimal footwear (the “experienced” group). This study shows that foot strength increases by, on average, 57.4% (p < 0.001) after six months of daily activity in minimal footwear. The experienced group had similar foot strength as the post intervention group, suggesting that six months of regular minimal footwear use is sufficient to gain full strength, which may aid healthy balance and gait.
... The MLA is supported by the intrinsic and extrinsic foot muscles, by strong ligaments such as the calcaneo-navicular ligament, and by the plantar aponeurosis. The MLA allows the foot to sustain body weight and to act as a spring, storing elastic energy that can be recovered during dynamic tasks (Caravaggi et al., 2009;Hicks, 1954;Stearne et al., 2016). ...
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Static and dynamic measurements of the medial longitudinal arch (MLA) in the foot are critical across different clinical and biomechanical research fields. While MLA deformation can be estimated using skin-markers for gait analysis, the current understanding of the correlates between skin-marker based models and radiographic measures of the MLA is limited. This study aimed at assessing the correlation and accuracy of skin-marker based measures of MLA deformation with respect to standard clinical X-ray based measures, used as reference. 20 asymptomatic subjects without morphological alterations of the foot volunteered in the study. A lateral X-ray of the right foot of each subject was taken in monopodalic upright posture with and without a metatarsophalangeal-joint dorsiflexing wedge. MLA angle was estimated in the two foot postures and during gait using 16 skin-marker based models, which were established according to the marker set of a validated multi-segment foot kinematic protocol. The error of each model in tracking MLA deformation was assessed and correlated with respect to standard radiographic measurements. Estimation of MLA deformation was highly affected by the skin-marker models. Skin-marker models using the marker on the navicular tuberosity as apex of the MLA angle showed the smallest errors (about 2 deg) and the largest correlations (R = 0.64–0.65; p < 0.05) with respect to the radiographic measurements. According to the outcome of this study, skin-marker based definitions of the MLA angle using the navicular tuberosity as apex of the arch may provide a more accurate estimation of MLA deformation with respect to that from radiographic measures.
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Shoes are generally designed protect the feet against repetitive collisions with the ground, often using thick viscoelastic midsoles to add in-series compliance under the human. Recent footwear design developments have shown that this approach may also produce metabolic energy savings. Here we test an alternative approach to modify the foot–ground interface by adding additional stiffness in parallel to the plantar aponeurosis, targeting the windlass mechanism. Stiffening the windlass mechanism by about 9% led to decreases in peak activation of the ankle plantarflexors soleus (~ 5%, p < 0.001) and medial gastrocnemius (~ 4%, p < 0.001), as well as a ~ 6% decrease in positive ankle work (p < 0.001) during fixed-frequency bilateral hopping (2.33 Hz). These results suggest that stiffening the foot may reduce cost in dynamic tasks primarily by reducing the effort required to plantarflex the ankle, since peak activation of the intrinsic foot muscle abductor hallucis was unchanged (p = 0.31). Because the novel exotendon design does not operate via the compression or bending of a bulky midsole, the device is light (55 g) and its profile is low enough that it can be worn within an existing shoe.
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Objective: The medial longitudinal arch is the main structure of load bearing and shock absorption of the foot. The evaluation of medial longitudinal arch, such as the navicular height, the medial longitudinal arch angle and the Feiss line should be performed with the subtalar joint in the neutral and relaxed position. Our study analyzed the correlation between the measurements of the subtalar joint in neutral and relaxed positions during the evaluation tests of the medial longitudinal arch. Methods: This is a cross-sectional study, in which 51 healthy volunteers (102 feet; 36 women; 28 ± 5 years, 1.66 ± 0.10 m; 24.5 ± 4.5 kg/m2) had their navicular height, medial longitudinal arch angle and Feiss line measured in the neutral and relaxed positions. The correlation between the measures was evaluated using Pearson's test. Results: A strong correlation of the 102 feet Feiss line measurements between neutral and relaxed positions (r = 0.81) was observed, and a moderate correlation between the medial longitudinal arch angle (r = 0.78) and between navicular height in neutral and relaxed positions (r = 0.76). Conclusion: The measurements of the longitudinal medial arch between the neutral and relaxed positions are strongly correlated. Therefore, it is not necessary to measure the medial longitudinal arch in both neutral and relaxed positions. Level of Evidence II, Diagnostic Studies - Investigating a diagnostic test.
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The return of tendon strain energy is thought to contribute to reducing the energy cost of running (Erun). However, this may not be consistent with the notion that increased Achilles tendon (AT) stiffness is associated with a lower Erun. Therefore, the purpose of this study was to quantify the potential for AT strain energy return relative to Erun for male and female runners of different abilities. A total of 46 long distance runners (18 elite male (EM), 12 trained male (TM) and 16 trained female, (TF) participated in this study. Erun was determined by indirect calorimetry at 75, 85 and 95% of the speed at lactate threshold (sLT) and energy cost per stride at each speed was estimated from previously reported stride length (SL)-speed relationships. AT force during running was estimated from reported vertical ground reaction force (Fz)-speed relationships, assuming an AT:GRF moment arm ratio of 1.5. AT elongation was quantified during a maximal voluntary isometric contraction using ultrasound. Muscle energy cost was conservatively estimated on the basis of AT force and estimated crossbridge mechanics and energetics. Significant group differences existed in sLT (EM>TM>TF, p<0.001). A significant group x speed interaction was found in the energy storage/release per stride (TM>TF>EM, p<0.001), the latter ranging from 10-70 J ∙ stride-1. At all speeds and in all groups, estimated muscle energy cost exceeded energy return (p<0.001). These results show that during distance running, the muscle energy cost is substantially higher than the strain energy release from the AT.
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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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Background: The human foot contains one of the most variable structures of the body, which is the medial longitudinal arch. Decrease in the height of this arch results in a flat foot. Although there is some evidence regarding the influence of flat foot on gait performance of flat-footed individuals, there is no strong evidence to support the theory that being flat-footed has an effect on energy consumption. Therefore, the aim of this study was to find the relationship between flat foot and energy consumption. Method: Two groups of normal and flat-footed participants were recruited in this research project. They were selected from the staff and students of Isfahan University of Medical Sciences. The foot indexes of both groups were obtained using the footprint method with help of Solid worker software. The physiological cost index (PCI) of the participants was measured by the use of a heart rate monitoring system (Polar Electro, Finland). The differences between the PCIs of both groups of participants was determined using a t test. In addition, the influence of using an insole was evaluated using a paired t test. Result: The energy consumption of flat-footed individuals differed significantly from that of normal individuals (the PCIs of normal and flat-footed individuals were 0.357 and 0.368 beats/m, respectively). Using a foot insole improved the performance of the flat-footed individuals during walking. Conclusion: The PCI of flat-footed individuals is more than that of normal participants as a result of misalignment of foot structure. Moreover, using a foot insole improved foot alignment and decreased energy consumption.
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The aims of this study were to examine ground contact characteristics, their relationship with race performance, and the time course of any changes in ground contact time during competitive 800 m and 1500 m races. Twenty-two seeded, single-sex middle-distance races totalling 181 runners were filmed at a competitive athletics meeting. Races were filmed at 100 Hz. Ground contact time was recorded one step for each athlete, on each lap of their race. Forefoot and midfoot strikers had significantly shorter ground contact times than heel strikers. Forefoot and midfoot strikers had significantly faster average race speed than heel strikers. There were strong large correlations between ground contact time and average race speed for the women's events and men's 1500 m (r = -0.521 to -0.623; P < 0.05), whereas the men's 800 m displayed only a moderate relationship (r = -0.361; P = 0.002). For each event, ground contact time for the first lap was significantly shorter than for the last lap, which might reflect runners becoming fatigued.
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The use of Sorbothane shoe inserts did not significantly alter the oxygen cost of running although the cost increased at both speeds (241 and 268 m · min-1). Catlin and Dressendorfer (1979) compared the oxygen cost of running in training flats (435 g each) and racing flats (260 g each). Subjects were seven marathoners who ran at their own best marathon race pace (201 to 303 m · min-1). V̇O2 (m1 · kg1 · min-1) was increased 3.3% (p<.05) while wearing the training flats, which was equivalent to an extra 2.14 kJ · min-1. At the submaximal running speeds selected, 241 and 268 m · min-1, no significant increase in absolute (l · min-1) or relative (ml · kg-1 · min-1) V̇O2 was found. This was true whether comparing V̇O2 as an average over the 6 minutes or the sum of the 6 minutes. These data are summarized in Table 3. The differences observed were slight. The increased oxygen uptake (l · min-1) was 0.4% greater while wearing the inserts at 241 · ̇ min-1, and 1.1% greater at 268 m · min-1. This yielded an increase in kJ expended of only .25 and .80 per minute at the two speeds, respectively. Over a 1 hour duration, this would amount to an increased energy expenditure of only 15.12 kJ at 241 · min-1, and 47.0 kJ at 268 m · min-1. When expressed relative to body weight, the increase in V̇O2 was 0.9% at 241 m · min-1 and 1.5% at 268 m · min-1.
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LEEN, BURKETT, WENDY M. KOHRT, and RICHARD BUCHBINDER. Effects of shoes and foot orthotics on [latin capital V with dot above]O2 and selected frontal plane knee kinematics. Med. Sci. Sports Exerc., Vol. 17, No. 1, pp. 158-163, 1985. The objective of this study was to investigate the effects of shoes and foot orthotics on running economy and selected frontal plane knee kinematics during the support phase of running. Twenty-one male runners who had been fitted with orthotics served as subjects. Subjects participated in three submaximal runs on a treadmill under the following conditions: (1) barefoot, (2) shoes, and (3) shoes plus orthotics. A run consisted of 1 min at 161 m[middle dot] min-1, 2 min at 180 m[middle dot]min-1, and 4 min at 201 m[middle dot]min-1. [latin capital V with dot above]O2 was calculated for the last 3 min of each test. Frontal plane motion was filmed during the sixth min of each submaximal run, and linear and angular displacement of the knee were then calculated from film data. Results from the mechanical aspect of this study indicate that there were no significant differences among the means for linear displacement of the knee. Angular displacement of the knee during barefoot running was significantly (P < 0.05) less than shoe and shoe-plus-orthotic conditions. There was no difference, however, between shoes and shoes plus orthotics. The economy results revealed that the aerobic cost of running increased as the amount of mass added to the foot increased. In absolute terms (1min-1), running in shoes plus orthotics was significantly (P < 0.05) more costly than running barefoot. It appears that if orthotics do, in fact, improve running economy by improving running mechanics, the amount of improvement is negated by the additional cost of running associated with the mass of the orthotics. (C)1985The American College of Sports Medicine