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The main purpose of the present study was to investigate the relationships between running mechanics, top running speed and economy in young endurance athletes. Twenty five endurance athletes (age 19.8 +/- 1.1 years, stature 1.82 +/- 0.07 m and body mass 69.4 +/- 7.5 kg) performed two separate tests on an indoor track. The first test was 8 x 30 m with increasing speed, and the second test was incremental 5 - 6 x 1,000 m. In the first test, ground reaction forces and stride characteristics were measured from each running speed. In the second test, running economy at the speed of 3.89 m . s (-1) and maximal oxygen uptake were determined. Ground contact time was the only factor which correlated significantly with both running economy (r = 0.49, p < 0.05) and maximal running speed (r = - 0.52, p < 0.01). Furthermore, maximal running speed was correlated significantly with the mass-specific horizontal force (r = 0.56, p < 0.01) but not with the vertical effective force. It is concluded that the short contact times required in economical and high speed running suggests that fast force production is important for both economical running and high top running speed in distance runners.
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Introduction
!
Running economy is strongly related to distance
running performance [4,19], and it is typically
determined by measuring the steady-state oxy-
gen consumption at the submaximal running
speed. Taking body mass into consideration, run-
ners with good running economy use less energy
and therefore less oxygen than runners with poor
running economy at the same speed. Researchers
have reported a 20 30% range in the oxygen
consumption for a given submaximal running
speed among trained distance runners [4, 6,18].
Interindividual variability in running economy
has been explained by various physiological, bio-
mechanical, environmental, anthropometrical
and psychological factors. Biomechanists have
identified that running economy is affected by
the net vertical impulse of the ground reaction
force [9], stride length [3], change in speed dur-
ing ground contact phase [11] and vertical stiff-
ness of a leg spring [5, 9].
Running speed is the product of stride rate and
stride length. Although both stride rate and stride
length are increased with increasing running
speed, stride length is responsible for increasing
speed up to 90% of an individual maximum speed
and, thereafter, the speed is only increased by in-
creasing stride rate [15,16,23]. Cavanagh and
Williams [3] found the most economical stride
length of a group of runners was close to that
which was freely chosen. Ground contact phase
is the only phase during a running cycle in which
a runner can produce force and influence stride
length and running speed. Functional and me-
chanical requirements during stance are re-
flected in the characteristics of the ground reac-
tion force. It has been shown that vertical and
horizontal components of ground reaction forces
increase with increasing running speed [14,16,
23]. Weyand et al. [23] concluded that runners
reach faster top speeds by applying greater sup-
port forces to the ground not by more rapid leg
movements. The critical point in maximal sprint
running is the change in running speed during
the ground contact phase. The horizontal break-
ing force and braking time as well as the horizon-
tal distance between the first contact point and
the center of gravity of the body at touchdown
should be very small to avoid loss of speed during
the braking phase of ground contact [17].
Abstract
!
The main purpose of the present study was to in-
vestigate the relationships between running me-
chanics, top running speed and economy in
young endurance athletes. Twenty five endur-
ance athletes (age 19.8 ± 1.1 years, stature
1.82 ± 0.07 m and body mass 69.4 ± 7.5 kg) per-
formed two separate tests on an indoor track. The
first test was 8 × 30 m with increasing speed, and
the second test was incremental 5 6 × 1000 m.
In the first test, ground reaction forces and stride
characteristics were measured from each run-
ning speed. In the second test, running economy
at the speed of 3.89 m
s
-1
and maximal oxygen
uptake were determined. Ground contact time
was the only factor which correlated significantly
with both running economy (r = 0.49, p < 0.05)
and maximal running speed (r = 0.52, p < 0.01).
Furthermore, maximal running speed was corre-
lated significantly with the mass-specific hori-
zontal force (r = 0.56, p < 0.01) but not with the
vertical effective force. It is concluded that the
short contact times required in economical and
high speed running suggests that fast force pro-
duction is important for both economical run-
ning and high top running speed in distance run-
ners.
Factors Related to Top Running Speed and Economy
Authors A. Nummela
1
, T. Keränen
1
, L. O. Mikkelsson
2
Affiliations
1
Research Institute for Olympic Sports, Jyväskylä, Finland
2
Pajulahti Sports Institute, Nastola, Finland
Key words
l
"
running economy
l
"
distance running
l
"
ground reaction force
l
"
stride length
l
"
ground contact time
accepted after revision
July 3, 2006
Bibliography
DOI 10.1055/s-2007-964896
Published online June 1, 2007
Int J Spor ts Med 2007; 28:
655 661 © Georg Thieme
Verlag KG Stuttgart
New York
ISSN 0172-4622
Correspondence
Dr. Ari Nummela
Research Institute for Olympic
Sports
Rautpohjankatu 6
40700 Jyväsk ylä
Finland
ari.nummela@kihu.fi
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Nummela A et al. Factors Related to Int J Sports Med 2007; 28: 655 661
Training & Testing
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The amount of energy used to run a constant distance is nearly
the same whether it is run at top speed or at leisure pace. The
results of Kram and Taylor [13] suggest that, primarily, the cost
of supporting the body weight and the time course generating
this force determines the cost of running. Therefore, a long
ground contact phase and great deceleration of horizontal speed
during a braking phase of the ground contact could be consid-
ered wasteful in terms of the metabolic energy requirements. A
successful endurance runner is characterized by less vertical os-
cillation [7], longer strides [3], shorter ground contact times
[21], less change in speed during the ground contact [11], and
lower first peak in the vertical component of the ground reaction
force, associated with a tendency to have smaller anteroposte-
rior peak forces [25]. In a well controlled study, Heise and Martin
[9] showed that less economical runners exhibited greater total
and net vertical impulse, indicating wasteful vertical motion.
It is a well known fact that elite sprint runners have a higher top
running speed and a lower running economy than elite distance
runners. Although there is a discrepancy between the high neu-
romuscular capacity to produce force and running economy,
some previous studies have shown that the explosive type
strength training can be used to improve both maximal power
output and running economy [10, 20]. Therefore, the main pur-
pose of the present study was to investigate the factors of run-
ning stride, which were related to both top running speed and
running economy in young endurance athletes.
Methods
!
Subjects
Twenty-five young male endurance athletes (ten distance run-
ners, eight orienteers and seven triathletes) volunteered as sub-
jects for the present study. All the athletes belonged to the na-
tional junior team and their mean ± SD age, height and body
mass were: 19.8 ± 1.1 years, 1.82 ± 0.07 m and 69.4 ± 7.5 kg, re-
spectively. All the subjects were fully informed of the procedures
and possible risks of the experiments, and written informed con-
sent was obtained from each subject. The informed consent was
in accordance with the guidelines of the Ethical Committee of
the University of Jyväskylä. The tests of the present study were
part of the athletes normal exercise testing and they complied
with current Finnish laws regarding the testing of human sub-
jects.
Procedure and measurements
In order to measure ground reaction forces and stride character-
istics at different running speeds and determine maximal sprint-
ing speed, running economy, distance running performance and
maximal oxygen uptake, the athletes ran two separate running
tests on a 200-m indoor track. The first test was 8 × 30 m with in-
creasing speed, and the second test was an incremental 5
6 ×1000 m.
In the first test (8 × 30 m), the athletes were able to accelerate
50 m to ensure a normal and steady running gait throughout
the 30-m measurement section. The speed of the first run was
5.0 m
s
–1
and, thereafter, the speed was increased by 0.40 m
s
–1
after each run until the sixth run (7.0 m
s
–1
). The running speed
was regulated by small lights placed on the next lane at intervals
of 4.0 m (Naakka Ltd., Lappeenranta, Finland). The athletes were
instructed to adjust their speed to coincide with the lights,
which were switched on and off along the track. The athletes
were asked to run the last two runs at maximal speed. Each run-
ning bout was separated by a two-minute recovery period dur-
ing which the runners returned to the start of the sprint course.
In order to measure running speed, stride rate and stride length,
a photocell contact mat [22] and two photocell gates were
placed on the sprint course (Ivar Ltd., Tallin, Estonia). A special
9-m long force platform system was placed in the middle of the
30-m measurement section. The system consisted of five two di-
mensional (2D) and three 3D force platforms (0.9 × 1.0 m each,
TR Test Ltd., Jyväskylä, Finland, natural frequency in the vertical
direction 170 Hz) and one Kistler 3D force platform (0.9 × 0.9 m,
400 Hz, Honeycomb, Kistler, Switzerland) connected in series
and covered with a tartan mat. Each force platform registered
both vertical and horizontal components of the ground reaction
forces. Vertical and horizontal ground reaction forces were re-
corded by a microcomputer using an AT Codas A/D converter
card (Dataq Instruments, Inc., Akron, OH, USA) with a sampling
frequency of 1000 Hz.
The incremental 5 6 × 1000-m test was performed after 15 min
recovery from the first test. The initial speed was 2.78 m
s
–1
for
the orienteers and triathletes and 3.33 m
s
–1
for the distance
runners. Thereafter, the speed was 3.89, 4.44, 5.00, and 5.56 m
s
–1
. The running speed was regulated by small lights embedded
on the inside of the 200-m indoor track at intervals of 4.0 m
(Naakka Ltd.). The athletes were instructed to adjust their speed
to coincide with the lights, which were turned on and off inside
the track. The athletes were asked to run the last 1000 m at max-
imal effort. The athletes performed five or six runs depending on
their maximal aerobic capacity. Oxygen consumption and heart
rate (Oxycon Mobile, Viasys Healthcare GmbH, Hoechberg, Ger-
many) were measured continuously during the whole test.
Running economy was measured as steady-state oxygen uptake
of submaximal running at the speed of 3.89 m
s
–1
, and maximal
oxygen uptake (V
˙
O
2max
) was defined as the highest oxygen
consumption during the test over a 60-second period. Running
economy and maximal oxygen uptake were expressed as
ml
kg
–0.75
min
–1
, since submaximal V
˙
O
2
and V
˙
O
2max
measures
during running may be better related to the 0.75 power of body
mass than [body
mass]
–1
[1].
Data analysis
Three to five contact phases of each subject at all running speeds
were selected for analysis. The horizontal force-time curve was
used to separate the ground reaction forces into the braking
and propulsion phases [16]. The integrals of both force-time
curves were calculated and divided by the respective time peri-
od to obtain the average force for the whole contact phase and
for horizontal braking and propulsion phases separately. The ef-
fective force (F
yeff
) which exceeds the body mass was determined
from (F
y
–F
BW
)
F
BW
–1
, where F
BW
= body weight.
Effective impulse values were determined from the effective
force applied to the running surface and ground contact times:
F
y
I
eff
=F
yeff
CT, where CT = ground contact time. CT was deter-
mined from the time the applied vertical force exceeded 0 N on
the force platform. Horizontal impulses (F
x
I) were calculated as
absolute impulses because horizontal force displays negative
values during breaking phase and positive values during propul-
sion phase: F
x
I=(F
x
F
BW
–1
)
CT.
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Statistics
The relationship between running speed, top running speed,
running economy and ground reaction force characteristics were
investigated using a standard Pearson product moment correla-
tion and linear regression analyses. Values are expressed as
mean ± standard deviation. All the statistical analyses were
undertaken using SPSSWIN 13.0 (SPSS, Inc., Chicago, IL, USA).
Results
!
Running economy and V
˙
O
2max
Although the subjects were all endurance athletes and belonged
to the national junior team, their V
˙
O
2max
and maximal 1000-m
speed was quite heterogeneous ranging from 152 to 240 ml
kg
–0.75
min
–1
(184±18ml
kg
–0.75
min
–1
or 63.9 ± 5.7 ml
kg
–1
min
–1
) and from 4.31 to 6.27 m
s
–1
(5.32 ± 0.55 m
s
–1
), respec-
tively. Running economy or oxygen uptake at the speed of
3.89 m
s
–1
ranged from 121 to 161 ml
kg
–0.75
min
–1
(144 ±
10 ml
kg
–0.75
min
–1
or 49.9 ± 3.3 ml
kg
–1
min
–1
), which were
typical of those which have been reported previously for similar
speeds [9,21]. The difference between the most and least eco-
nomical runners showed that the athletes were much more ho-
mogeneous in terms of running economy than they were in
V
˙
O
2max
.
Running mechanics as a function of speed
In pooled data across the speed range, speed increases were
achieved by increasing both stride lengths and stride frequen-
cies at the speeds below 7 m
s
–1
, and at the speeds above
7m
s
–1
, stride frequency was solely responsible for speed in-
crease (l
"
Fig. 1A). The increases in stride frequencies resulted
from the reductions in ground contact time at speeds below
6m
s
–1
, although stride frequency depends on both contact time
and flight time (l
"
Fig. 1B). As subjects approach their top speed,
both contact time and flight time decreased. These flight time
reductions coincided with the decreases in effective vertical im-
pulse and horizontal impulse (l
"
Fig. 1C, D). In pooled data, the
increase in stride length was related to the increase in effective
vertical force (r = 0.58, p < 0.001) and horizontal propulsion force
(r = 0.73, p < 0.001, l
"
Fig. 2) but not with the vertical effective
impulse or horizontal impulse.
Maximal running speed
In the present athletes, maximal 30-m running speed ranged
from 7.70 to 9.40 m
s
–1
(8.39 ± 0.45 m
s
–1
). Maximal running
speed of the athletes was significantly correlated with the
ground contact times (r = 0.52, p < 0.01, l
"
Fig. 3A) and braking
phase time (r = 0.64, p < 0.001) but not with the propulsion
phase time. The mass-specific vertical force was not related to
the maximal running speed, but a significant correlation was ob-
Fig. 1A and B Running mechanics as a function of
speed for the data of 25 endurance athletes with
eight different speeds. Each dot represents the
average value of a certain speed of an athlete. Lin-
ear or second order polynomial trend line is also
added in the figures. A Increase in stride length
(dots) and stride frequency (open circles) with in-
creasing speed. B Decrease in ground contact time
(dots) and flight time (open circles) with increasing
speed.
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Fig. 1C and D Running mechanics as a function of
speed for the data of 25 endurance athletes with
eight different speeds. Each dot represents the
average value of a certain speed of an athlete. Lin-
ear or second order polynomial trend line is also
added in the figures. C Increase in vertical effective
force (dots) and decrease in vertical effective im-
pulse (open circles) with increasing speed. D In-
crease in mass-specific horizontal force (dots) and
horizontal impulse (open circles) with increasing
running speed.
Fig. 2 Vertical effective force (open circles) and
mass-specific horizontal force (dots) during a pro-
pulsion phase as a function of stride length.
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served between the maximal running speed and the mass-spe-
cific horizontal forces of the whole ground contact (r = 0.56,
p < 0.01) and propulsion phase (r = 0.66, p < 0.001, l
"
Fig. 3B) but
not braking phase.
Running economy
In order to investigate the relationships between running econo-
my and ground reaction force and stride characteristics, the val-
ues at the running speeds of 5.4, 5.8, 6.2, and 6.6 m
s
–1
were used
in the analyses. No correlation was observed between ground re-
action force characteristics and running economy. The only sig-
nificant correlations were observed between running economy
and ground contact time at the running speeds of 5.8 m
s
–1
(r = 0.49, p < 0.05), 6.2 m
s
–1
(r = 0.44, p < 0.05) and 6.6 m
s
–1
(r = 0.41, p < 0.05). Although there were only few significant cor-
relations between running economy and ground reaction force
and stride characteristics, biomechanical factors might explain
individual differences in running economy as shown in l
"
Table 1.
Discussion
!
The present study was designed to investigate the relationships
between force production and running economy and running
speed in endurance athletes. Previous studies have shown a dis-
crepancy between running economy and top running speed,
Table 1 Ground contact time, vertical effective impulse and relative stride length (stride length
stature
–1
) of the two most economical runners (RE121
ml
kg
–0.75
min
–1
and RE123 ml
kg
–0.75
min
–1
), the two most uneconomical runners (RE158
kg
–0.75
min
–1
and RE161 ml
kg
–0.75
min
–1
) and average value of
the whole group. The ground reaction force and stride characteristics are average values from the velocity of 5.8 m
s
–1
RE121 RE123 Mean ± SD RE158 RE161
CT (ms) 165 150 175 ± 13 190 170
F
y
I
eff
(s) 0.144 0.151 0.154 ± 0.014 0.151 0.160
Rel SL 1.03 1.04 1 .03 ± 0.05 1.03 1.07
CT: ground contact time; F
y
I
eff
: vertical effective impulse; Rel SL: relative stride length; RE: running economy
Fig. 3A and B Ground contact time (A) and mass-
specific horizontal force during a propulsion phase
(B) as a function of maximal running speed for 25
endurance athletes.
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since both can be improved by strength training [20] but the
fastest runners apply greater support forces to the ground [23]
and less economical runners exhibit greater ground reaction im-
pulses [9]. In the present study, ground reaction force character-
istics were related to running speed but not to running economy.
The ground contact time was the only stride variable, which was
related to both running speed and running economy.
It is well known that ground contact time decreases linearly
with increasing running speed [15] and this was also observed
in the present study (l
"
Fig. 1B). The relationship between run-
ning economy and short contact times has also been observed
in a previous study [21]. Furthermore, Williams [24] has found
that during submaximal running, ground contact times differ
between a rearfoot and a midfoot striker. Short contact time
seems to be beneficial for both running economy and maximal
running speed. This seems to be logical since the critical point
in maximal sprint running and economical running is the speed
lost during the breaking phase [17]. The horizontal braking force
and braking time as well as the horizontal distance between the
first contact point and the center of gravity of the body at touch-
down should be very small to avoid loss of speed during the
braking phase of ground contact. Kyröläinen et al. [14] suggested
that increasing the pre-landing and braking activity of the leg
extensor muscles might prevent unnecessary yielding of the
runner during the braking phase, helping them tolerate higher
impact loads. A short and rapid stretch with a short coupling
time and a high force at the end of pre-stretch creates a good
precondition for utilizing elasticity [2,12]. Pre-activity increases
the sensitivity of the muscle spindle via enhanced alpha-gamma
coactivation potentiating stretch reflexes, and enhancing mus-
culo-tendon stiffness, with a resulting improvement in running
economy.
In a well controlled study, Heise and Martin [9] observed that
less economical runners exhibited greater total and net vertical
impulse, indicating wasteful vertical motion. The influence of
the total vertical impulse was 38% of the interindividual varia-
bility in running economy. In the present study, no significant
correlation was observed between any ground reaction force
characteristics and running economy. One reason for the differ-
ence in the results might be that in the study of the Heise and
Martin [9] the ground reaction forces were measured from the
same running speed (3.35 m
s
–1
) as the running economy. In
the present study, we assumed that a runner who is economical
at a given running speed will be economical at other speeds as
well and therefore ground reaction forces were measured from
the running speeds which were close to the athletes’ speed dur-
ing a track running competition. A number of physiological and
biomechanical factors appear to influence running economy in
endurance athletes and therefore the interactions between me-
chanical and metabolic variables appear to be very complex [14,
25]. This is one reason why in some studies a relationship exists
between ground reaction force characteristics and running
economy [9] and in some other studies not (present study, [14]).
Based on the findings of the previous studies, we could hypothe-
size that short ground contact time [21], low vertical effective
impulse [9] and optimal or self-selected stride length [3] at a
given speed are associated with high running economy.
Although we did observe a significant correlation only between
contact time and running economy, vertical impulse and stride
length might also explain individual differences in running
economy. Excellent running economy of the two most economi-
cal runners in the present study can be explained, at least partly,
by short ground contact times (l
"
Table 1). Furthermore, the high
running economy of the RE121 (l
"
Table 1) could also be ex-
plained by the low vertical effective force. On the other hand,
the same biomechanical factor did not explain the poor running
economy of the two least economical runners in the present
study (l
"
Table 1). One possible reason for the poor running
economy for the RE158 (l
"
Table 1) is long ground contact times,
whereas high vertical effective impulse and long relative stride
length might explain, at least partly, why the RE161 (l
"
Table 1)
used more oxygen than the other runners in the present study.
These individual examples showed the complexity of the run-
ning economy, and that none single biomechanical factor can
fully explain the differences in running economy between the in-
dividual runners.
Stride length, stride frequency, ground contact time and flight
time as a function of running speed in the present study
(l
"
Fig. 1A, B) are well in line with previous findings [15,16, 23].
The results of the present study also showed that the increase
in stride length resulted from increasing both vertical and hori-
zontal ground reaction forces (l
"
Fig. 2). These relationships
seem obvious, since ground contact is the only phase during the
running cycle in which a runner can produce force and influence
stride length and running speed. Vertical effective force in-
creased with the increasing speed until the speed of 7 m
s
–1
,
thereafter the speed was increased without further increase in
vertical effective force (l
"
Fig. 1C) and no correlation was ob-
Fig. 4 The relationships between running econo-
my or oxygen uptake (3.89 m
s
–1
) and ground
contact time at the speeds of 5.8 m
s
–1
(dots) and
6.6 m
s
–1
(open circles).
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served between the vertical effective force and maximal running
speed in present athletes. This is contradictory to the results of
Weyand et al. [23]. They concluded that runners reach faster
top speeds by applying greater vertical support forces to the
ground. In the present study, horizontal force increased linearly
with the running speed (l
"
Fig. 1D), and a significant relationship
was observed between maximal running speed and horizontal
force (l
"
Fig. 3B). The results of the present study suggest that
maximal running speed is more dependent on horizontal than
vertical force. This seems to be logical since one can not increase
horizontal speed by increasing vertical force, but acceleration
and deceleration of running speed is produced mainly by chang-
ing horizontal force.
In conclusion, only ground contact times exhibited statistically
significant correlations with both running economy and maxi-
mal running speed. This suggests that the short braking phase
and use of elastic energy are important factors both in econom-
ical and high speed running in the group of young well-trained
endurance athletes. Although any other biomechanical factors
did not correlate with running economy, there are numerous
biomechanical factors which could be used to partially explain
differences in running economy between two runners. Another
important finding of the present study was that horizontal
ground reaction force was linearly increased with running speed
and was correlated with the maximal running speed. This sug-
gests that the horizontal component of ground reaction force is
more important in attaining high top running speed in distance
runners than the vertical component of it, since similar linear re-
lationships were not observed between vertical effective force
and running speed, and no significant correlation was observed
between vertical force and maximal running speed.
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Training & Testing
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... Another strong argument for the existence of an inaccessible region in the speed-density diagram can be put forward from independent bio-mechanical arguments if we consider that the higher the runner speed, the more available space is needed to take a step. Indeed, the relation between the runners speed and their stride length (LS) has been reported in Ref. (31)(32)(33). These studies show that the stride length increases with speed as shown in the inset of Fig. 7. ...
... The maximum local density fli at which a pedestrian can make a stride LS can be estimated as fli = 1/(LS We), with We the e ective runner width (see SI Appendix, Fig. S1). Then, using Ref. (31)(32)(33), we can obtain the minimum space (maximum density) required by runners to take a step depending on their speed (see solid lines in Fig. 7). In other words, these curves separate physically accessible from inaccessible regions in the speeddensity diagram. ...
... Theoretical limit in the speed-density diagram given by the bio-mechanical data of the stride length of runners required for a given speed (see text). Reported data correspond to Zrenner et al.(31), Nummela et al.(32) and, Yan and Jin(33). ...
Article
We characterize the dynamics of runners in the famous “Running of the Bulls” Festival by computing the individual and global velocities and densities, as well as the crowd pressure. In contrast with all previously studied pedestrian systems, we unveil a unique regime in which speed increases with density that can be understood in terms of a time-dependent desired velocity of the runners. Also, we discover the existence of an inaccessible region in the speed–density state diagram that is explained by falls of runners. With all these ingredients, we propose a generalization of the pedestrian fundamental diagram for a scenario in which people with different desired speeds coexist.
... Laufanfänger verwenden fast ausschließlich das Fersenlaufmuster (97-99 %) (Bertelsen et al. 2012 (Cavanagh und Williams 1982). Submaximale Laufgeschwindigkeiten bis 90 % der Maximalgeschwindigkeit werden vorwiegend durch Verlängerung der Schrittlänge realisiert, wohingegen die maximale Laufgeschwindigkeit durch Vergrößerung der Schrittfrequenz erreicht wird (Cavanagh und Kram 1989;Mero und Komi 1986;Nummela et al. 2007). Für eine vorgegebene Geschwindigkeit wählt der Läufer intuitiv eine Schrittlängen-und Schrittfrequenz-Kombination, die für ihn am ökonomischsten ist, d. h. ...
... Die Beschleunigungskraft wirkt in der zweiten Hälfte der Standphase vom Mittelstütz bis zur Abdruckphase. Die Bremskraft und die Bremszeit sollten möglichst kurz sein, um den Geschwindigkeitsverlust des Läufers in der Bremsphase möglichst gering zu halten (Nummela et al. 2007). Chang und Kram (1999) vermuten, dass sich dies vorteilhaft auf die Laufökonomie auswirken könnte. ...
... In einer Studie von Pollock (1977) konnte gezeigt werden, dass professionelle Marathonläufer geringere _ VO 2 max Werte und eine bessere Laufökonomie aufweisen als diejenigen Läufer, die sich auf kürzere Laufdistanzen spezialisiert haben. Aus biomechanischer Sicht wird Laufökonomie durch eine Vielzahl von Einflussgrößen, wie der Schrittlänge und -frequenz (Cavanagh und Williams 1982), der Bodenreaktionszeit (Nummela et al. 2007), den Bodenreaktionskräften (Nummela et al. 2007), der Muskelaktivität (Kyrolainen et al. 2001;Tartaruga et al. 2012) der vertikalen Oszillation des Körperschwerpunktes (Heise et al. 2011;Tartaruga et al. 2012;Williams und Cavanagh 1987) und der Eigenschaft elastischer Elemente zur Speicherung und Rückgabe von Energie (Gleim et al. 1990) bestimmt. Jedoch können deskriptive kinematische und dynamische Parameter alleine nicht die Komplexität von Laufökonomie beschreiben (Kyrolainen et al. 2001;Williams und Cavanagh 1987 (Butler et al. 2007;Hardin et al. 2004;Nigg et al. 1998), die Kraftverteilung (Hamill et al. 2011;Ly et al. 2010;Nigg et al. 2003b), die Gelenkbelastung und Gelenkenergie (Nigg et al. 2003a;Roy und Stefanyshyn 2006;Stefanyshyn und Nigg 1997), die Muskelaktivität (Nigg, Stefanyshyn et al. 2003;Wakeling et al. 2002), den Energyreturn (Nigg 2010;Stefanyshyn und Nigg 2000), den Laufkomfort Miller et al. 2000;Mundermann et al. 2002;Nigg et al. 2015), und das Bewegungsmuster (Eskofier et al. 2012). ...
... The faster speed may not be attainable due to increased shock absorption and stride length requirements of downhill running. [12][13][14] Furthermore, previous research indicates that runners are unable to reach their VO 2 max during downhill running. 15 All the above points to simultaneous benefits for increased energy expenditure on uphill and downhill segments, which is aspirational for all runners, but akin to attaining a personal record for a half-marathon en route to a personal record for a full marathon. ...
... The reasoning could be rooted in biomechanical limitations on downhill running speed such as maintaining adequate shock attenuation, stride length, and ground reaction forces. [12][13][14] Another hypothesis is that varied pacing strategies are observed on hilly courses due to diminished aerobic capabilities during downhill running. Lemire et al 15 demonstrated that runners increase their v VO 2 max and achieve the same maximum heart rate during downhill running but are unable to match their VO 2 max from uphill and level running. ...
Article
Purpose: To investigate the relationship between pacing strategy and performance during uphill and downhill running-specifically, what distribution of energy corresponds to faster race finish times between and among participants. Methods: Eighteen years of race data from a 10.2-mile running race with an uphill first half and a downhill second half were analyzed to identify relationships between pacing and performance. A pacing coefficient (PC), equal to a participant's ascent time divided by finishing time (FT), was used to define each participant's pacing strategy. The American College of Sports Medicine metabolic running equation was used to estimate energy expenditure during the ascent, descent, and total race. Statistical analyses compared participants' PC to their FT and finishing place within their age and gender category. Additionally, FT and finishing place were compared between groups of participants who exhibited similar pacing strategies. Results: PCs were positively associated with faster FTs (r2 = .120, P < .001) and better finishing positions (r2 = .104, P < .001). PCs above .600 were associated with the fastest average FTs and best average finishing position within age and gender categories (all P ≤ .047). Conclusions: Participants performed the best when energy expenditure increased no more than 10.4% during the uphill portion compared to their overall average. It is not possible to state that overly aggressive uphill efforts resulted in premature fatigue and thus slower decent times and worse race performance. However, participants should still avoid overly aggressive uphill pacing, as performance was associated with larger PCs.
... Human running has been studied extensively from the viewpoint of how its temporal (cadence) and spatial (step length) components contribute to velocity [1][2][3][4][5][6][7][8][9][10]. Velocity equals the product of cadence and step length, and the relative contribution of each component to a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 changing velocity differs across the velocity range. ...
... Velocity changes below the inflection point occurred mainly by modulating step length and velocity changes above the inflection point occurred mainly via cadence modulation. These characteristics were demonstrated in preceding studies conducted on sprinters and distance runners [7,9], and are particularly prominent in sprinters. ...
Article
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The effect of the different training regimes and histories on the spatiotemporal characteristics of human running was evaluated in four groups of subjects who had different histories of engagement in running-specific training; sprinters, distance runners, active athletes, and sedentary individuals. Subjects ran at a variety of velocities, ranging from slowest to fastest, over 30 trials in a random order. Group averages of maximal running velocities, ranked from fastest to slowest, were: sprinters, distance runners, active athletes, and sedentary individuals. The velocity-cadence-step length (V-C-S) relationship, made by plotting step length against cadence at each velocity tested, was analyzed with the segmented regression method, utilizing two regression lines. In all subject groups, there was a critical velocity, defined as the inflection point, in the relationship. In the velocity ranges below and above the inflection point (slower and faster velocity ranges), velocity was modulated primarily by altering step length and by altering cadence, respectively. This pattern was commonly observed in all four groups, not only in sprinters and distance runners, as has already been reported, but also in active athletes and sedentary individuals. This pattern may reflect an energy saving strategy. When the data from all groups were combined, there were significant correlations between maximal running velocity and both running velocity and step length at the inflection point. In spite of the wide variety of athletic experience of the subjects, as well as their maximum running velocities, the inflection point appeared at a similar cadence (3.0 ± 0.2 steps/s) and at a similar relative velocity (65–70%Vmax). These results imply that the influence of running-specific training on the inflection point is minimal.
... Typically, the running economy is measured during submaximal running at a speed below the ventilatory-lactate threshold [1]. Moreover, step characteristics, including SF and SL, change depending on the running speed [8][9][10]. Taken together, it is necessary to analyze step characteristics while running at a speed near the race pace to clarify the relationship of SF and SL with running performance. ...
... Sports 2021,9, 131 ...
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This study examined the relationship between step characteristics and race time in a 5000-m race. Twenty-one male Japanese endurance runners performed a 5000-m race. Step length, step frequency, contact time, and flight time of two gait cycles (i.e., four consecutive ground contacts) were measured every 400-m by using high-speed video image. Moreover, step length was normalized to body height to minimize the effect of body size. In addition to step characteristics on each lap, the averages of all laps and the per cent change from the first half to the second half were calculated. The average step frequency and step length normalized to body height correlated significantly with the 5000-m race time (r = −0.611, r = −0.575, respectively, p < 0.05 for both). Per cent changes in contact time and step length correlated significantly with the 5000-m race time (r = 0.514, r = −0.486, respectively, p < 0.05 for both). These findings suggest that, in addition to higher step frequency and step length normalized to body height, smaller changes in step length during a given race may be an important step characteristic to achieving superior race performance in endurance runners.
... The faster subjects run, the shorter ( Figure 3). This is due to the fact, that longer ground contacts decelerate runners to a higher extent, which causes lower running speeds [41]. Both ground contact and swing phase can be further segmented into sub-phases. ...
Thesis
Full-text available
Body-worn sensors, so-called wearables, are getting more and more popular in the sports domain. Wearables offer real-time feedback to athletes on technique and performance, while researchers can generate insights into the biomechanics and sports physiology of the athletes in real-world sports environments outside of laboratories. One of the first sports disciplines, where many athletes have been using wearable devices, is endurance running. With the rising popularity of smartphones, smartwatches and inertial measurement units (IMUs), many runners started to track their performance and keep a digital training diary. Due to the high number of runners worldwide, which transferred their data of wearables to online fitness platforms, large databases were created, which enable Big Data analysis of running data. This kind of analysis offers the potential to conduct longitudinal sports science studies on a larger number of participants than ever before. In this dissertation, both studies showing how to extract endurance running-related parameters from raw data of foot-mounted IMUs as well as a Big Data study with running data from a fitness platform are presented.
... In addition, vertical and/or horizontal GRFs are positively correlated with running economy [53,54]. However, not all research is in agreement on the influence of GRF/displacement on economy [55]. Future research is required to examine the influence of altering vertical displacement and stride rate/length in persons with ASD. ...
Article
Background Neuromuscular training (NMT) has demonstrated efficacy as an intervention to decrease the risk of anterior cruciate ligament injuries and improve sports performance. The effect of this training on the mechanisms that contribute to improved physical performance has not been well defined. Hypothesis Athletes in the NMT group will have better mechanisms of fundamental movements and agility tests that may contribute to improved sports performance. Study Design Prospective cohort study Level of Evidence Level 2 Methods Eight high school teams (111 athletes, 53% male, mean age 16 years) participated, with half performing NMT. Physical performance was measured using the dorsaVi ViPerform system, a US Food and Drug Administration-cleared wireless sensor system. Agility was assessed using a timed 3-cone test. Independent sample t tests were used to compare differences between the intervention and control groups. Results Matched pre- and postseason data were collected from 74 athletes after excluding athletes with injury and those lost to follow-up. Significant improvements were observed in the NMT group for loading/landing speed ratios during a single-leg hop test (right lower extremity = −0.19 [–0.37, 0.03], P = 0.03 and left lower extremity = −0.27 [–0.50, −0.03], P = 0.03). The control group had lower ground reaction forces compared with the NMT group ( P < 0.02), while significant improvements were found in the NMT group for initial peak acceleration ( P < 0.02) and cadence ( P = 0.01) during a straight-line acceleration/deceleration test. For the 3-cone agility test, the postseason time decreased compared with preseason in the NMT group, whereas the time for the control group increased (–0.37 s vs 0.14 s, P < 0.00). Conclusion The results demonstrate that NMT administered by sports medicine clinicians can significantly improve some physical performance of fundamental movements in high school athletes. Clinical Relevance Coaches should be trained to effectively deliver NMT in order to improve sports performance.
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Running biomechanics and ethnicity can influence running economy (RE), which is a critical factor of running performance. Our aim was to compare RE of South East Asian (SEA) and non-South East Asian (non-SEA) runners at several endurance running speeds (10–14 km/h) matched for on-road racing performance and sex. Secondly, we explored anthropometric characteristics and relationships between RE and anthropometric and biomechanical variables. SEA were 6% less economical (p = 0.04) than non-SEA. SEA were lighter and shorter than non-SEA, and had lower body mass indexes and leg lengths (p ≤ 0.01). In terms of biomechanics, a higher prevalence of forefoot strikers in SEA than non-SEA was seen at each speed tested (p ≤ 0.04). Furthermore, SEA had a significantly higher step frequency (p = 0.02), shorter contact time (p = 0.04), smaller footstrike angle (p < 0.001), and less knee extension at toe-off (p = 0.03) than non-SEA. Amongst these variables, only mass was positively correlated to RE for both SEA (12 km/h) and non-SEA (all speeds); step frequency, negatively correlated to RE for both SEA (10 km/h) and non-SEA (12 km/h); and contact time, positively correlated to RE for SEA (12 km/h). Despite the observed anthropometric and biomechanical differences between cohorts, these data were limited in underpinning the observed RE differences at a group level. This exploratory study provides preliminary indications of potential differences between SEA and non-SEA runners warranting further consideration. Altogether, these findings suggest caution when generalizing from non-SEA running studies to SEA runners.
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The aim of this study was to compare the effects of two 10-week non-laboratory based running retraining programs on foot kinematics and spatiotemporal parameters in recreational runners. One hundred and three recreational runners (30 ± 7.2 years old, 39% females) were randomly assigned to either: a barefoot retraining group (BAR) with 3 sessions/week over 10 weeks, a cadence retraining group (CAD) who increased cadence by 10% again with 3 sessions/week over 10 weeks and a control group (CON) who did not perform any retraining. The footstrike pattern, footstrike angle (FSA) and spatial-temporal variables at comfortable and high speeds were measured using 2D/3D photogrammetry and a floor-based photocell system. A 3x2 ANOVA was used to compare between the groups and 2 time points. The FSA significantly reduced at the comfortable speed by 5.81° for BAR (p < 0.001; Cohen’s d = 0.749) and 4.81° for CAD (p = 0.002; Cohen’s d = 0.638), and at high speed by 6.54° for BAR (p < 0.001; Cohen’s d = 0.753) and by 4.71° for CAD (p = 0.001; Cohen’s d = 0.623). The cadence significantly increased by 2% in the CAD group (p = 0.015; Cohen’s d = 0.344) at comfortable speed and the BAR group showed a 1.7% increase at high speed. BAR and CAD retraining programs showed a moderate effect for reducing FSA and rearfoot prevalence, and a small effect for increasing cadence. Both offer low-cost and feasible tools for gait modification within recreational runners in clinical scenarios.
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This study determined the effects of a 10-week strength training program on running economy in 12 female distance runners who were randomly assigned to either an endurance and strength training program (ES) or endurance training only (E). Training for both groups consisted of steady-state endurance running 4 to 5 days a week, 20 to 30 miles each week. The ES undertook additional weight training 3 days a week. Subjects were tested pre and post for [latin capital V with dot above]O2, max, treadmill running economy, body composition, and strength. A repeated-measures ANOVA was used to determine significant differences between and within groups. The endurance and strength training program resulted in significant increases in strength (p < 0.05) for the ES in both upper (24.4%) and lower body (33.8%) lifts. There were no differences in treadmill [latin capital V with dot above]O2, max and body composition in either group. Running economy improved significantly in the ES group, but no significant changes were observed in the E group. The findings suggest that strength training, when added to an endurance training program, improves running economy and has little or no impact on [latin capital V with dot above]O2, max or body composition in trained female distance runners. (C) 1997 National Strength and Conditioning Association
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During running, the behaviour of the support leg was studied by modelling the runner using an oscillating system composed of a spring (the leg) and of a mass (the body mass). This model was applied to eight middle-distance runners running on a level treadmill at a velocity corresponding to 90% of their maximal aerobic velocity [mean 5.10 (SD 0.33) m · s−1]. Their energy cost of running (C r ), was determined from the measurement of O2 consumption. The work, the stiffness and the resonant frequency of both legs were computed from measurements performed with a kinematic arm. The C r was significantly related to the stiffness (P < 0.05, r = −0.80) and the absolute difference between the resonant frequency and the step frequency (P < 0.05, r = 0.79) computed for the leg producing the highest positive work. Neither of these significant relationships were obtained when analysing data from the other leg probably because of the work asymmetry observed between legs. It was concluded that the spring-mass model is a good approach further to understand mechanisms underlying the interindividual differences in C r .
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Understanding of biomechanical factors in sprint running is useful because of their critical value to performance. Some variables measured in distance running are also important in sprint running. Significant factors include: reaction time, technique, electromyographic (EMG) activity, force production, neural factors and muscle structure. Although various methodologies have been used, results are clear and conclusions can be made. The reaction time of good athletes is short, but it does not correlate with performance levels. Sprint technique has been well analysed during acceleration, constant velocity and deceleration of the velocity curve. At the beginning of the sprint run, it is important to produce great force/ power and generate high velocity in the block and acceleration phases. During the constant-speed phase, the events immediately before and during the braking phase are important in increasing explosive force/power and efficiency of movement in the propulsion phase. There are no research results available regarding force production in the sprint-deceleration phase. The EMG activity pattern of the main sprint muscles is described in the literature, but there is a need for research with highly skilled sprinters to better understand the simultaneous operation of many muscles. Skeletal muscle fibre characteristics are related to the selection of talent and the training-induced effects in sprint running. Efficient sprint running requires an optimal combination between the examined biomechanical variables and external factors such as footwear, ground and air resistance. Further research work is needed especially in the area of nervous system, muscles and force and power production during sprint running. Combining these with the measurements of sprinting economy and efficiency more knowledge can be achieved in the near future.
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Oxygen uptake during treadmill running was measured at submaximal and maximal intensities in six different groups of endurance athletes (N = 134) and in seven endurance-trained men. The relationship between body mass (M) and oxygen uptake (VO2) was evaluated by deriving the exponent b in the equation VO2 = a.Mb. Thus, if b = 1, the oxygen uptake increases in proportion to body mass and oxygen uptake per kg is independent of body mass; if b less than 1, than the oxygen uptake per kg is inversely related to body mass. The exponent b was found to be less than unity for all groups for both submaximal (b = 0.76, s = 0.06) and maximal oxygen uptake (b = 0.71, s = 0.05). These results indicate that neither submaximal nor maximal oxygen uptake increases in proportion to body mass during running. The relationship between submaximal oxygen uptake and body mass observed in this study may explain why the oxygen uptake per kg of body mass has been found to be higher for children than for adults.
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The amount of energy used to run a mile is nearly the same whether it is run at top speed or at a leisurely pace (although it is used more rapidly at the higher speed). This puzzling independence of energy cost and speed is found generally among running animals, although, on a per gram basis, cost is much higher for smaller animals. Running involves little work against the environment; work is done by muscles and tendons to lift and accelerate the body and limbs. Some of the work is recovered from muscle-tendon springs without metabolic cost and work rate does not parallel metabolic rate with either speed or size. Regardless of the amount of work muscles do, they must be activated and develop force to support the weight of the body. Load-carrying experiments have shown that the cost of supporting an extra newton of load is the same as the weight-specific cost of running. Size differences in cost are proportional to stride frequency at equivalent speeds, suggesting that the time available for developing force is important in determining cost. We report a simple inverse relationship between the rate of energy used for running and the time the foot applies force to the ground during each stride. These results support the hypothesis that it is primarily the cost of supporting the animal's weight and the time course of generating this force that determines the cost of running.
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Running economy, defined as the steady-state V̇O2 for a given running velocity, has been shown to account for a large and significant proportion of variation in distance-running performance among runners roughly comparable in V̇O2 max. Despite this recognition, relatively little is known regarding the potpourri of physiological, environmental, structural and mechanical factors potentially associated with a lower aerobic demand of running. Early attempts at quantifying the energy expenditure of exhaustive runs incorporated measurements of oxygen consumption before, during, and after exercise. The validity of this approach has been questioned, however, since recent evidence has demonstrated that only a moderate relationship exists between postexercise V̇O2 and anaerobic metabolism. The energy demands for submaximal running (i.e. running economy) can be quantified by calculating the steady-state V̇O2, expressed with respect to body mass and time, for a standardised, submaximal running speed. Since this variable represents the aerobic demand of running, the generation of energy must derive wholly from cell respiration and not from substantial protein catabolism. Research has indicated that at low to moderate work rates, the steady-state energy condition is attained in about 3 minutes. Trained individuals reach steady-state sooner that unfit subjects. While limited by methodological constraints, the existence of a steady-state has also been verified by the lack of blood lactate accumulation and the presence of a respiratory exchange ratio of less than 1.00. The ability of economy, either singly or in combination with V̇O2 max, to account for a substantial portion of performance variation among trained distance runners and untrained subjects of comparable ability and fitness level has been demonstrated in recent cross-sectional studies. Limited data from short and long term longitudinal research also suggests that endurance running success is linked to training and growth-related improvements in economy. Intraindividual variation in economy has been shown to vary between 2% and 11% for a given speed. Most of this variation can probably be attributed to biological error. While the majority of evidence does not support a gender difference in running economy, data from some studies suggest that males may be more economical than women. Prepubescent children are less economical than older children and adults, whereas older adults exhibit the same trend when compared to younger counterparts. Because of air and wind resistance, the aerobic demands of indoor treadmill running significantly underestimate the cost of overground running, especially at higher speeds. As body temperature rises during exercise, V̇O2 increases as a result of the ‘Q10 effect.’ While conflicting data exist with respect to the effect of fatigue on the aerobic demand of running, recent work incorporating physiological and biomechanical measures demonstrated that a 30-minute maximal run produced little or no change in the metabolic and biomechanical profiles of trained runners. No consensus exists regarding the effects of different types and intensities of training on running economy. Substantial variation in economy among long distance runners who compete in the same event suggests non-training factors may also influence economy. A number of anthropometric and biomechanical factors have been considered for their ability to account for some of the interindividual variability in running economy commonly observed. Despite assumptions to the contrary, it seems appropriate to conclude that when the confounding influence of speed is negated, few biomechanical variables have been shown consistently to account for a substantial portion of variation in economy. It has been suggested that at present it is not possible to distinguish whether mechanical variables describing the running pattern of an uneconomical runner contribute to making the runner uneconomical, or whether the pattern reflects the means by which the individual has optimised his or her own anatomical and physiological features.
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Man-shoe-surface interaction in running is a complex phenomenon, and its investigation gives specific requirements for the measuring system. This study was designed to make an effort to develop a methodology for measuring the interaction between the first two components (man and shoe) under normal heel running conditions both on the force plate and on an asphalt road. The force plate system consisted of a series of 1.5-m long plates with a total length of 12 m. This allowed recordings of several natural ground contact phases in one run. By repeating the runs several times at constant velocity (3 m X s-1 and 5 m X s-1), altogether 10-30 Fz and Fx force curves could be obtained for further computerized averaging. The running shoes were equipped with special heel and toe contact sensors, which were used for recordings of even more cycles at constant velocity on the road running conditions. Telemetered EMG technique was employed to examine the response of the selected lower extremity muscles on the varying shoe and running velocity conditions. The results indicated preliminarily that the changes in ground reaction forces were more velocity than shoe (hard/soft) dependent and that EMG activation patterns were muscle specific with regard to preinnervation and impact and push-off phases for the gastrocnemius, rectus femoris, vastus lateralis, and tibialis anterior muscles. Although the actual measurements were not yet designed for comprehensive recording of each parameter, the results obtained suggest that the major leg extensor muscles change their activation patterns with the varying impact load conditions.(ABSTRACT TRUNCATED AT 250 WORDS)
Article
A new instrument, the photocell contact mat (PCM), was developed to measure ground contact time and flight time as well as step and stride frequency as a function of running time or running distance. The purpose of this study was to evaluate the validity and accuracy of PCM measurements against simultaneous force platform measurements, Effects of striking pattern (sprinter or long-distance), running velocity, and height of the PCM from ground level on the contact parameters were analyzed. One male sprint runner and one male distance (marathon) runner volunteered as subjects. The time difference between the PCM and force platform determinations linearly increased as a function of the PCM height and decreased as a function of running velocity (except for the lowest 10 mm PCM height). The low coefficients of variation found between corrected PCM contact times and force platform contact times suggested that the PCM is an accurate instrument to measure ground contact times.
The relationships between ground reaction forces, electromyographic activity (EMG), elasticity and running velocity were investigated at five speeds from submaximal to supramaximal levels in 11 male and 8 female sprinters. Supramaximal running was performed by a towing system. Reaction forces were measured on a force platform. EMGs were recorded telemetrically with surface electrodes from the vastus lateralis and gastrocnemius muscles, and elasticity of the contact leg was evaluated with spring constant values measured by film analysis. Data showed increases in most of the parameters studied with increasing running speed. At supramaximal velocity (10.36±0.31 m×s−1; 108.4±3.8%) the relative increase in running velocity correlated significantly (P<0.01) with the relative increase in stride rate of all subjects. In male subjects the relative change in stride rate correlated with the relative change of IEMG in the eccentric phase (P<0.05) between maximal and supramaximal runs. Running with the towing system caused a decrease in elasticity during the impact phase but this was significant (P<0.05) only in the female sprinters. The average net resultant force in the eccentric and concentric phases correlated significantly (P<0.05−0.001) with running velocity and stride length in the maximal run. It is concluded that (1) increased neural activation in supramaximal effort positively affects stride rate and that (2) average net resultant force as a specific force indicator is primarily related to stride length and that (3) the values in this indicator may explain the difference in running velocity between men and women.
Article
The study of running economy has important performance implications for the long-distance runner and may provide insight into mechanisms underlying economical human locomotion. Physiological aspects of running economy discussed in this paper include intraindividual variability, body temperature, heart rate, ventilation, muscle fiber type, gender, air and wind resistance, altitude, fatigue, and training. The lack of consensus evident in the literature regarding many of these variables and their influence on economy supports the use of expanded sample sizes featuring both genders, standard testing conditions, and cross- and interdisciplinary approaches to help explain group economy differences observed in descriptive and experimental paradigms and to extend the generalizability of research findings.