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To investigate the effect of three cycling cadences on a subsequent 3000 m track running performance in well trained triathletes. Nine triathletes completed a maximal cycling test, three cycle-run succession sessions (20 minutes of cycling + a 3000 m run) in random order, and one isolated run (3000 m). During the cycling bout of the cycle-run sessions, subjects had to maintain for 20 minutes one of the three cycling cadences corresponding to 60, 80, and 100 rpm. The metabolic intensity during these cycling bouts corresponded approximately to the cycling competition intensity of our subjects during a sprint triathlon (> 80% VO(2)max). A significant effect of the prior cycling exercise was found on middle distance running performance without any cadence effect (625.7 (40.1), 630.0 (44.8), 637.7 (57.9), and 583.0 (28.3) seconds for the 60 rpm run, 80 rpm run, 100 rpm run, and isolated run respectively). However, during the first 500 m of the run, stride rate and running velocity were significantly higher after cycling at 80 or 100 rpm than at 60 rpm (p<0.05). Furthermore, the choice of 60 rpm was associated with a higher fraction of VO(2)max sustained during running compared with the other conditions (p<0.05). The results confirm the alteration in running performance completed after the cycling event compared with the isolated run. However, no significant effect of the cadence was observed within the range usually used by triathletes.
Effect of cycling cadence on subsequent 3 km running
performance in well trained triathletes
T Bernard, F Vercruyssen, F Grego, C Hausswirth, R Lepers, J-M Vallier, J Brisswalter
Br J Sports Med
Objectives: To investigate the effect of three cycling cadences on a subsequent 3000 m track running
performance in well trained triathletes.
Methods: Nine triathletes completed a maximal cycling test, three cycle-run succession sessions (20
minutes of cycling + a 3000 m run) in random order, and one isolated run (3000 m). During the cycling
bout of the cycle-run sessions, subjects had to maintain for 20 minutes one of the three cycling cadences
corresponding to 60, 80, and 100 rpm. The metabolic intensity during these cycling bouts
corresponded approximately to the cycling competition intensity of our subjects during a sprint triath-
lon (> 80% V
Results: A significant effect of the prior cycling exercise was found on middle distance running
performance without any cadence effect (625.7 (40.1), 630.0 (44.8), 637.7 (57.9), and 583.0
(28.3) seconds for the 60 rpm run, 80 rpm run, 100 rpm run, and isolated run respectively). However,
during the first 500 m of the run, stride rate and running velocity were significantly higher after cycling
at 80 or 100 rpm than at 60 rpm (p<0.05). Furthermore, the choice of 60 rpm was associated with a
higher fraction of V
MAX sustained during running compared with the other conditions (p<0.05).
Conclusions: The results confirm the alteration in running performance completed after the cycling
event compared with the isolated run. However, no significant effect of the cadence was observed
within the range usually used by triathletes.
uring the last decade, numerous studies have investi-
gated the effects of the cycle-run transition on
subsequent running adaptation in triathletes.
pared with an isolated run, the first few minutes of triathlon
running have been reported to induce an increase in oxygen
uptake (V~
) and heart rate (HR),
an alteration in
ventilatory efficiency (V~
and haemodynamic
modifications—that is, changes in muscle blood flow.
Moreover, changes in running pattern have been observed
after cycling, such as an increase in stride rate
modifications in trunk gradient, knee angle in the non-
support phase, and knee extension during the stance phase.
These changes are generally related to the appearance of leg
muscle fatigue characterised by perturbation of electromyo-
graphic activity of different muscle groups.
Recently, from a laboratory study, Vercruyssen et al
that it is possible for triathletes to improve the adaptation
from cycling to running at an intensity corresponding to
Olympic distance competition pace (80–85% maximal oxygen
uptake (<V>
MAX)). They showed a lower metabolic load
during a running session after the adoption of the energeti-
cally optimal cadence (73 rpm) calculated from the V~
cadence relation
compared with the freely chosen cadence
(81 rpm) or the theoretical mechanical optimal cadence (90
Furthermore, Lepers et al
indicated that, after cycling,
neuromuscular factors may be affected by exercise duration or
choice of pedalling cadence. They observed, on the one hand,
the appearance of neuromuscular fatigue after 30 minutes of
cycling at 80% of maximal aerobic power, and, on the other
hand, that the use of a low (69 rpm) or high (103 rpm) cycling
cadence induced a specific neuromuscular adaptation, as-
sessed by the variation in RMS/M wave ratio interpreted as the
central neural input change.
From a short distance triathlon race perspective character-
ised by high cycling or running intensities, these observations
raise a major question about the effect of neuromuscular
fatigue and/or metabolic load induced by a prior cycling event
on subsequent running performance. To the best of our
knowledge, few studies have examined the effect of cycling
task characteristics on subsequent running performance.
Hausswirth et al
15 16
indicated that riding in a continuous
drafting position, compared with the no draft modality,
significantly reduced oxygen uptake during cycling and
improved the performance of a 5000 m run in elite triathletes.
In addition, Garside and Doran
showed in recreational
triathletes an effect of cycle frame ergonomics: when the seat-
tube angle was changed from 73° to 81°, the performance of
the subsequent 10 000 m run was improved—that is, there
was a reduction in race time.
Therefore, the aim of this study was to examine in outdoor
conditions the effects of different pedalling cadences (within
the range 60–100 rpm) on the performance of a subsequent
3000 m track run, the latter depending mainly on both meta-
bolic and neuromuscular factors.
17 18
Nine well motivated male triathletes currently competing at
the national level participated in the study. They had been
training regularly and competing in triathlons for at least four
years. For all subjects, triathlon was their primary activity;
their mean (SD) times for Olympic distance and sprint
distance triathlons were 120 minutes 37 seconds (3.2) and 59
minutes 52 seconds (3.4) respectively. Mean (SD) training
distances a week were 9.1 (1.9) km for swimming, 220.5
(57.1) km for cycling, and 51.1 (8.9) km for running. The
mean (SD) age of the subjects was 24.9 (4.0) years.Their mean
Abbreviations: V
, oxygen uptake; HR, heart rate; V
E, ventilatory
efficiency; V
MAX, maximal oxygen uptake
See end of article for
authors’ affiliations
Correspondence to:
Professor Brisswalter, Unité
Ergonomie Sportive et
Performance, Université de
Toulon-Var, BP 132 83957
La Garde, France;
Accepted 13 June 2002
(SD) body weight and height were 70.8 (3.8) kg and 179 (3.9)
cm respectively. The subjects were asked to abstain from
exhaustive training throughout the experiment. Finally, they
were fully informed of the content of the experiment, and
written consent was obtained before all testing, according to
local ethical committee guidelines.
Maximal cycling test
Subjects first performed a maximal test to determine V~
and ventilatory threshold. This test was carried out on an
electromagnetically braked ergocycle (SRM; Jülich, Welldorf,
19 20
on which the handle bars and racing seat are
fully adjustable both vertically and horizontally to reproduce
the positions of each subject’s bicycle. No incremental running
test was performed in this study, as previous investigations
indicated similar V~
MAX values whatever the locomotion
mode in triathletes who began the triathlon as their first
[22 ]
This incremental session began with a warm up of 100 W
for six minutes, after which the power output was increased
by 30 W a minute until volitional exhaustion. During this pro-
tocol, V~
,V~E, respiratory exchange ratio, and HR were
continuously recorded every 15 seconds using a telemetric
system collecting gas exchanges (Cosmed K4
, Rome, Italy)
previously validated by Hausswirth et al.
V~ O
MAX was
determined according to criteria described by Howley et al
that is, a plateau in V~
despite an increase in power output, a
respiratory exchange ratio value of 1.15, or an HR over 90% of
the predicted maximal HR (table 1). The maximal power out-
put reached during this test was the mean value of the last
minute. Moreover, the ventilatory threshold was calculated
during the cycling test using the criterion of an increase in
E/V~ O
with no concomitant increase in V~ E/V~ CO
Cycle-run performance sessions
All experiments took place in April on an outdoor track. Out-
side temperature ranged from 22 to 25°C, and there was no
appreciable wind during the experimental period. Each
athlete completed in random order three cycle-run sessions
(20 minutes of cycling and a 3000 m run) and one isolated run
(3000 m). These tests were separated by a 48 hour rest period.
Before the cycle-run sessions, subjects performed a 10 minute
warm up at 33% of maximal power.
During the cycling bout
of the cycle-run sessions, subjects had to maintain one of
three pedalling cadences corresponding to 60, 80, or 100 rpm.
These cycling cadences were representative of the range of
cadences selected by triathletes in competition.
15 26
Indeed, it
was recently reported that, on a flat road at 40 km/h, cycling
cadences could range from 67 rpm with a 53:11 gear ratio to
103 rpm with a 53:17 gear ratio.
However, 60 rpm is close to
the range of energetically optimal cadence values,
80 rpm is
near the freely chosen cadence,
and 100 rpm is close to the
cadence used in a drafting situation.
15 16
According to previous studies of the effect of a cycling event
on running adaptation,
the cycling bouts were performed at
an intensity above the ventilatory threshold corresponding to
70% of maximal power output (80% V~
MAX) and were
representative of a sprint distance simulation.
15 16
The three cycling bouts of the cycle-run sessions were con-
ducted on the SRM system next to the running track. The
SRM system allowed athletes to maintain constant power
output independent of cycling cadence. In addition, feedback
on selected cadence was available to the subjects via a screen
placed directly in front of them.
After cycling, the subjects immediately performed the 3000
m run on a 400 m track. The mean (SD) transition time
between the cycling and running events (40.4 (8.1) seconds)
was the same as that within actual competition.
During the
running bouts, race strategies were free, the only instruction
given to the triathlete being to run as fast as possible over the
whole 3000 m.
Measurement of physiological variables during the
cycle-run sessions
,V~E, and HR were recorded every 15 seconds with a K4
The physiological data were analysed during the cycling bouts
at the following intervals: 5th–7th minute (5–7), 9th–11th
minute (9–11), 13th–15th minute (13–15), 17th–19th minute
(17–19), and every 500 m during the 3000 m run (fig 1).
Measurement of biomechanical variables during the
cycle-run sessions
Power output and pedalling cadence were continuously
recorded during cycling bout. During the run, kinematic data
were analysed every 500 m using a 10 m optojump system
Table 1 Physiological characteristics of the subjects obtained during a maximal
cycling test
Parameters V~O
VT (% V~ O
68.1 (6.5) 179.1 (14.7) 185.4 (4.9) 67.0 (3.6) 398.1 (24.5)
Values are expressed as mean (SD).
MAX, maximal oxygen uptake (ml/min/kg); V
EMAX, maximal ventilation (litres/min); HR
, maximal heart
rate (beats/min); VT, ventilatory threshold; MAP, maximal power output (W).
Figure 1 Representation of the three cycle-run sessions. TR, Cycle-run transition; BS, blood samples taken; M
, measurement intervals
during cycling at 5–7, 9–11, 13–15, and 17–19 minutes; M
, measurement intervals during running at 500, 1000, 1500, 2500, and
3000 m; WU, warm up for each condition.
Cycling cadence and running performance 155
(MicroGate, Timing and Sport, Bolzano, Italy). From this sys-
tem, speed, contact, and fly time attained were recorded every
500 m over the whole 3000 m. The stride rate-stride length
combination was calculated directly from these values. Thus
the act of measuring the kinematic variables had no effect on
the subjects’ running patterns within each of the above 10 m
optical bands.
Blood sampling
Capillary blood samples were collected from ear lobes. Blood
lactate was analysed using the Lactate Pro system previously
validated by Pyne et al.
Four blood samples were collected:
before the cycle-run sessions (at rest), at 10 and 20 minutes
during the cycling bouts, and at the end of the 3000 m run.
Statistical analysis
All data are expressed as mean (SD). The stability of the run-
ning pattern was described using the coefficient of variation
((SD/mean) × 100) for each athlete.
A two way analysis of
variance (cadence × period time) for repeated measures was
performed to analyse the effects of time and cycling cadence
using V~
,V~E, HR, speed velocity, stride variability, speed vari-
ability, stride length, and stride rate as dependent variables.
For this analysis, the stride and speed variability (in %) were
analysed by an arcsine transformation. A Newmann-Keuls
post hoc test was used to determine differences among all
cycling cadences and periods during exercise. In all statistical
tests, the level of significance was set at p<0.05.
3000 m performances
In this study, the performance of the isolated run was signifi-
cantly better than the run performed after cycling (583.0
(28.3) and 631.1 (47.6) seconds for the isolated run and mean
cycle-run sessions respectively). No significant effect of
cycling cadence was observed on subsequent 3000 m running
performance. Running times were 625.7 (40.1), 630.0 (44.8),
and 637.7 (57.9) seconds for the 60, 80, and 100 rpm run ses-
sions respectively (table 2). The mean running speed during
the first 500 m (fig 2) was significantly lower after the 60 rpm
ride than after the 80 and 100 rpm cycling bouts (17.5 (1.1),
18.3 (1.1), and 18.3 (1.2) km/h respectively). In addition, the
speed variability (from 500 to 2500 m) was significantly lower
during the 60 rpm run session than for the other cycle-run
conditions (2.18 (1.2)%, 4.12 (2.0)%, and 3.80 (1.8)% for the
60, 80, and 100 rpm run respectively).
Cycling bouts of cycle-run sessions
During the 20 minutes at 60, 80, and 100 rpm cycling bouts,
average cadences were 61.6 (2.6), 82.7 (4.3) and 98.2 (1.7)
rpm respectively. Mean HR and V~
E recorded during the 100
rpm cycling bout were significantly higher than in other
cycling conditions. Furthermore, blood lactate concentrations
were significantly higher at the end of the 100 rpm bout than
after the 60 and 80 rpm cycling bouts (7.0 (2.0), 4.6 (2.1) and
5.1 (2.1) mmol/l respectively, p<0.05). Conversely, no effect of
either pedalling rate or exercise duration was found on V~
(table 2, p>0.05).
Table 2 Mean values for power output and speed, oxygen uptake, expiratory flow, heart rate, blood lactate, and
running performance obtained during the cycle-run sessions
(60 rpm)_ Run
(80 rpm) Run
(100 rpm) Run
Power output (W)/speed (km/h) 275.4 (19.4) 17.3 (1.1) 277.1 (18.6) 17.2 (1.20 277.2 (17.2) 17.1 (1.5)
Oxygen uptake (ml/min/kg) 55.6 (4.6) 62.8 (7.3)* 55.3 (4.0) 57.9 (4.1) 56.5 (4.3) 59.7 (5.6)
Expiratory flow (litres/min) 94.8 (12.2) 141.9 (15.9) 98.2 (9.2) 140.5 (14.6) 107.2 (13.0)* 140. 5 (21.8)
Heart rate (beats/min) 163.5 (9.5) 184.2 (4.6) 166.1 (10.4) 185.8 (3.1) 170.7 (4.7)* 182. 6 (5.0)
Lactataemia (mmol/l) 4.6 (2.1) 9.0 (1.9) 5.1 (2.1) 9.2 (1.2) 7.0 (2.0)* 9.9 (1.8)
Stride rate (Hz) 1.48 (0.01) 1.49 (0.01) 1.48 (0.02)
Running performance (s) 625.7 (40.1) 630.0 (44.8) 637.6 (57.9)
*Significantly different from the other cycle-run sessions, p<0.05.
Figure 2 Race strategies expressed as the evolution in running
velocity during the run bouts (60, 80, 100 rpm). *Significantly
different from the running velocity during the 60 rpm run session,
Figure 3 Changes in fraction of V
MAX) sustained by
subjects during the running bouts (60, 80, and 100 rpm).
*Significantly different from the initial period, p<0.05; †significantly
different from the other conditions, p<0.05.
156 Bernard, Vercruyssen, Grego, et al
Running bouts of cycle-run sessions
Table 2 gives mean values for V~
,V~E, and HR for the running
bouts. The statistical analysis indicated a significant interac-
tion effect (period time + cycling cadence) on V~
during sub-
sequent running (p<0.05). V~
values recorded during the run
section of the 60 rpm session were significantly higher than
during the 80 rpm or the 100 rpm sessions (p<0.05, table 2).
These values represent respectively 92.3 (3.0)% (60 rpm run),
85.1 (0.6)% (80 rpm run), and 87.6 (1.2)% (100 rpm run) of
cycle V~
MAX, indicating a significantly higher fraction of
MAX sustained by subjects during the 60 rpm run session
from 1000 to 3000 m than under the other conditions
(p<0.05, fig 3). Changes in stride rate within the first 500 m of
the 3000 m run were significantly greater during the 80 and
100 rpm run sessions than during the 60 rpm run session
(1.52 (0.05), 1.51 (0.05), and 1.48 (0.03) Hz respectively). No
significant effect of cycling cadence was found on either stride
variability during the run or blood lactate concentration at the
end of the cycle-run sessions (table 2).
The main observations of this study confirm the negative
effect of a cycling event on running performance when com-
pared with an isolated run. However, we observed no effect of
the particular choice of cycling cadence on the performance of
a subsequent 3000 m run. However, our results highlight an
effect of the characteristics of the prior cycling event on meta-
bolic responses and running pattern during the subsequent
Cycle-run sessions v isolated run and running
To our knowledge only one study has analysed the effect of
cycling events on subsequent running performance when
compared with an isolated run.
The study showed, during a
sprint distance triathlon (0.75 km swim, 20 km bike ride, 5 km
run), a significant difference betweena5kmrunafter cycling
(alone and in a sheltered position) and the run performed
without a prior cycling event (isolated run). The cycling event
caused an increase in mean 5 km race time (1014 seconds)
and a decrease in mean running velocity (17.4 km/h)
compared with the isolated run (980 seconds and 18.2 km/h).
Our results are in agreement, showing an impairment in run-
ning performance after the cycling event whatever the choice
of pedalling cadence. There was an increase in mean running
time (631 seconds) and a decrease in mean running velocity
(17.2 km/h) compared with the performance in the isolated
run (583 seconds and 18.5 km/h). Therefore, one finding of
our study is that a prior cycling event can affect running per-
formance over the 3 km as well as the 5 km and 10 km
One hypothesis to explain the alteration in running
performance after cycling could be the high metabolic load
sustained by subjects at the end of cycling characterised by an
increase in blood lactate concentration (4–6 mmol/l) associ-
ated with a high V~
MAX (81–83%) and HR
(88–92%). On the
other hand, Lepers et al
have recently shown in well trained
triathletes a reduction in muscular force relating to both cen-
tral and peripheral factors—that is, changes in M wave and
EMG RMS—after 30 minutes of cycling performed at different
pedalling cadences (69–103 rpm). We hypothesise that these
modifications of neuromuscular factors associated with
increasing metabolic load during cycling could increase the
development of fatigue just before running, whatever the
choice of pedalling cadence.
Cycling cadences and physiological and biomechanical
characteristics of running
Our results show no effect of different cycling cadences
(60–100 rpm) commonly used by triathletes on subsequent
running performance. A classical view is that performance in
triathlon running depends on the characteristics of the
preceding cycling event, such as power output, pedalling
cadence, and metabolic load.
Previous investigations have
shown a systematic improvement in running performance
when the metabolic load of the cycling event was reduced
either by drafting position
or racing on a bicycle with a steep
seat-tube angle (81°).
Unlike a 3000 m run which is charac-
terised by neuromuscular and anaerobic factors,
17 18
improvement in running performance in these previous stud-
ies was observed over a variety of long distances (5–10 km)
where the performance depends mainly on the capacity of the
subject to minimise energy expenditure over the whole
Therefore one explanation for our results is that
minimisation of metabolic load through cadence choice
during cycling has a significant effect on the running time
mainly during events of long duration. Further research is
needed into the effect of cadence choice on total performance
for running distances close to those of Olympic and Iron man
triathlon events.
However, despite the lack of cadence effect on 3000 m race
time, our results indicate an effect of cadence choice (60–100
rpm) on the stride pattern or running technique during a 3000
m run. This difference was mainly related to the higher veloc-
ity preferred by subjects immediately after cycling at 80 and
100 rpm and to the lower velocity from 1500 to 2500 m after
cycling at high cadences. These results may suggest that the
use of a low pedalling cadence (close to 60 rpm) reduces vari-
ability in running velocity—that is, one of the factors of run-
ning technique—during a subsequent run.
For running speeds above 5 m/s (> 18 km/h) and close to
maximum values, the change in stride rate is one of the most
important factors in increasing running velocity.
In our
study, the significant increase in running speed observed dur-
ing the first 500 m of the 80 and 100 rpm run sessions was
associated with a significantly higher stride rate (1.51–1.52
Hz) than in the 60 rpm run session (1.48 Hz). The relation
between stride rate and cycling cadence has been reported by
Hausswirth et al
in elite subjects participating in a sprint dis-
tance triathlon, indicating a significantly higher stride rate
after cycling at 102 rpm (1.52 Hz) than after cycling at 85 rpm
(1.42 Hz) for the first 500 m of the run.
These observations suggest that immediately after the cycle
stage, triathletes spontaneously choose a race strategy directly
related to the pedalling cadence, but this effect seems to be
transitory, as no significant differences between conditions
were reported after the first 500 m of running. This is in
agreement with previous studies in which changes in stride
pattern and running velocity were found to occur only during
the first few minutes of the subsequent run.
the fact that triathletes prefer to run at a high pace after
cycling at 80 and 100 rpm seems to confirm different anecdo-
tal reports of triathletes. Most triathletes prefer to adopt a
high pedalling cadence during the last few minutes of the
cycle section of actual competition. Three strategies may be
evoked to characterise the choice of cycling cadence: speeding
up in the last part of the cycle stage in order to get out quickly
on the run (when elite triathletes compete in draft legal
; reducing power output and spin to minimise the
effects of the bike-run transition; maintaining power output
while increasing cadence. However, our results show that such
a strategy is associated with higher metabolic cost during the
cycling stage and greater instability in running pattern,
suggesting that it is not physiologically beneficial for the ath-
lete to adopt high pedalling cadences in triathlon competition.
During our study, cycling at 100 rpm was associated with an
increase in metabolic cost as classically observed in previous
studies for a high cadence such as an increase in V~
, HR,
and blood lactate concentration.
At the end of the 100
rpm cycling task, mean blood lactate concentration was 7.0
(2.0) mmol/l, suggesting a high contribution of anaerobic
Cycling cadence and running performance 157
whereas it was 4.6 (2.1) mmol/l after cycling at
60 rpm. The effect of pedalling rate on physiological
adaptation during prolonged cycling has recently been
Brisswalter et al
indicated that cycling at a
cadence higher than 95 rpm induces a significant increase in
,V~E, and lactate concentration after 30 minutes of exercise
in triathletes.
Moreover, our results show an effect of cycling cadence on
aerobic contribution during maximal running performance.
The subjects were able to sustain a higher fraction of V~
during the 60 rpm run session—that is, 92%—than during
the 80 and 100 rpm run sessions—84% and 87% of V~
respectively—(fig 3). These results suggest that the contribu-
tion of the anaerobic pathway
is more important after the
higher cycling rates (80 and 100 rpm) than after the 60 rpm
ride and could lead during a prolonged running exercise to
earlier appearance of fatigue caused by metabolic
33 34
In conclusion, our results confirm the alteration in running
performance after a cycling event compared with an isolated
run. The principal aim of our investigation was to evaluate the
impact of different pedalling rates on subsequent running
performance. No significant effect of cycling cadence was
found on 3000 m running performance, despite some
changes in running strategies, stride rate, and metabolic con-
tributions. We chose a running distance of 3000 m to analyse
the possible effect of neuromuscular fatigue—previously
reported after a 30 minute cycling exercise at the same
—on running performance when neuromuscular
and anaerobic factors make important contributions.
17 18
the effect observed was not significant, the choice of cadence
within the usual range does not seem to influence the
performance of a middle distance run. One limiting factor of
this study may be the choice of a short exercise duration
because an effect of metabolic load reduction during the
cycling stage on running performance was previously
observed for a run longer than 5000 m. For multidisciplinary
activities such as triathlon and duathlon, further applied
research on the relation between cycling cadence and
performance of the subsequent run is required to evaluate the
influence of the practical conditions and constraints of actual
Authors’ affiliations
T Bernard, F Vercruyssen, F Grego, J-M Vallier, J Brisswalter,
Ergonomie et performance sportive, UFR STAPS, Université de
Toulon-Var, France
C Hausswirth, Laboratoire de physiologie et biomécanique, INSEP,
Paris, France
R Lepers, Groupe analyse du mouvement, UFR STAPS, Université de
Bourgogne, France
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22 Vercruyssen F, Bernard T, Vallier JM. Evaluation of aerobic fitness in
triathletes: effect of locomotion mode.
Science of Motion
23 Hausswirth C, Bigard AX, Le Chevalier JM. The cosmed K4 telemetry
system as an accurate device for oxygen uptake measurements during
Int J Sports Med
24 Howley ET, Basset DR, Welch HG. Criteria for maximal oxygen uptake:
review and commentary.
Med Sci Sports Exerc
25 Wasserman K, Whipp BJ, Koyal SN,
et al.
Anaerobic threshold and
respiratory gas exchange during exercise.
J Appl Physiol
26 Lepers R., Millet GY, Maffiuletti NA,
et al.
Effect of pedalling rates on
physiological response during an endurance cycling exercise.
Eur J Appl
27 Pyne DB, Boston T, Martin DT,
et al.
Evaluation of the lactate pro blood
lactate analyser.
Eur J Appl Physiol
28 Maruyama H, Nagasaki H. Temporal variability in the phase durations
during treadmill walking.
Hum Mov Sci
29 Hausswirth C, Lehénaff D. Physiological demands of running during
long distance runs and triathlons.
Sports Med
30 Fukunaga T, Matsuo A, Yuasa K,
et al.
Mechanical power output in
International Series on Biomechanics; Biomechanics VI-B
31 Hagan RD, Weiss SE, Raven BR. Effect of pedal rate on
cardiorespiratory responses during continuous exercise.
Med Sci Sports
32 Vercruyssen F, Hausswirth C, Smith D,
et al.
Effect of exercise duration
on optimal pedaling rate choice in triathletes.
Can J Appl Physiol
33 Bigland-Ritchie B, Woods JJ. Changes in muscle contractile properties
and neural control during human muscular fatigue.
Muscle Nerve
34 Fitts RH. Cellular mechanisms of muscle fatigue.
Physiol Rev
Take home message
Compared with an isolated run, completion of a cycling
event impairs the performance of a subsequent run
independently of the pedalling cadence. However,
running strategy, stride rate, and metabolic contribution
seem to be improved by the use of a low pedalling
cadence (60 rpm). The choice of cycling cadence may
have an effect on the running adaptation during a sprint or
short distance triathlon.
158 Bernard, Vercruyssen, Grego, et al
Much research has been conducted on the effects of cycling on
physiological variables measured during subsequent running
in triathletes. Few authors, however, have examined the effect
of variation in cycling task characteristics on either such vari-
ables or overall run performance. This study, examining the
effect of different pedalling cadences during a cycle at about
80% V~
MAX on performance within a succeeding 3 km run by
well trained male triathletes, adds to the published work in
this area.
V Vleck
Chair, Medical and Research Committee of the European
Triathlon Union and Senior Lecturer, School of Chemical and
Life Sciences, University of Greenwich, London, UK
Cycling cadence and running performance 159
... Therefore, the detrimental effects of cycling before running are verified. Our results are supported by previous findings in studies that were performed in laboratory conditions [7,35,36] or in outdoor conditions with cycling and running distances that are similar to those in our investigation [37]. The damaging effects of cycling prior to running might be due to accumulated muscular fatigue in the bike segment and could be attributed to an increase in neural fatigue, causing alterations in the neuromotor pattern [10,38], as has been argued in previous studies. ...
... Some running kinematic variables, such as ground contact time, step cadence, or vertical oscillation, do not appear to be affected by previous biking under the conditions of this study, which supports the findings of previous researches, and suggesting that bike-run transitioning will affect physiological parameters more than biomechanical parameters [7,37]. However, the running kinematics after cycling might be impaired when compared to isolated run kinematics, with a significant decrease in terms of stride length, which significantly reduces after cycling transition. ...
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Running performance is a determinant factor for victory in Sprint and Olympic distance triathlon. Previous cycling may impair running performance in triathlons, so brick training becomes an important part of training. Wearable technology that is used by triathletes can offer several metrics for optimising training in real-time. The aim of this study was to analyse the effect of previous cycling on subsequent running performance in a field test, while using kinematics metrics and SmO2 provided by wearable devices that are potentially used by triathletes. Ten trained triathletes participated in a randomised crossover study, performing two trial sessions that were separated by seven days: the isolated run trial (IRT) and the bike-run trial (BRT). Running kinematics, physiological outcomes, and perceptual parameters were assessed before and after each running test. The running distance was significantly lower in the BRT when compared to the IRT, with a decrease in stride length of 0.1 m (p = 0.00) and higher %SmO2 (p = 0.00) in spite of the maximal intensity of exercise. No effects were reported in vertical oscillation, ground contact time, running cadence, and average heart rate. These findings may only be relevant to ‘moderate level’ triathletes, but not to ‘elite’ ones. Triathletes might monitor their %SmO2 and stride length during brick training and then compare it with isolated running to evaluate performance changes. Using wearable technology (near-infrared spectroscopy, accelerometry) for specific brick training may be a good option for triathletes.
... As a result, these findings may lack practical and training specificity for triathletes competing in draft-legal short-course and Olympic distance triathlon where cycling is highly variable with respect to both power output and cadence ranges [3] that would therefore, have a substantially different impact on running performance [2]. Subsequent studies have aimed to replicate the metabolic demand of cycling experienced during short-course triathlon, by prescribing constant cycling intensities based on a percentage of maximal aerobic power (~72% MAP) [12] or above the ventilatory threshold (~80% VO 2max ) [13]. Exercising at such intensities may reflect the average metabolic cost of the cycle leg of short-course and Olympic distance triathlon however, considering the variable nature of cycling during these formats of triathlon such testing protocols lack specificity, at least concerning elite draft-legal short-course and Olympic distance triathlon. ...
... Despite the reported energy saving benefits of drafting during elite short-course and Olympic distance triathlon [50], it is suggested that variability of power output and cadence increases as a by-product of drafting [53]. In particular, pedalling frequency (PF) influences the physiological cost and running performance during the C-R [13,[54][55][56]. It has been reported that higher PF (cadence range 80-120 rpm) increases the oxygen cost and negatively affects subsequent running performance [55,56]. ...
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Transitioning efficiently between cycling and running is considered an indication of overall performance, and as a result the cycle–run (C–R) transition is one of the most researched areas of triathlon. Previous studies have thoroughly investigated the impact of prior cycling on running performance. However, with the increasing number of short-course events and the inclusion of the mixed relay at the 2020 Tokyo Olympics, efficiently transitioning from cycle–run has been re-emphasised and with it, any potential limitations to running performance among elite triathletes. This short communication provides coaches and sports scientists a review of the literature detailing the negative effects of prior variable-cycling on running performance experienced among elite, short-course and Olympic distance triathletes; as well as discussing practical methods to minimise any negative impact of cycling on running performance. The current literature suggests that variable-cycling negatively effects running ability in at least some elite triathletes and that improving swimming performance, drafting during cycling and C–R training at race intensity could improve an athlete’s triathlon running performance. It is recommended that future research clearly define the performance level, competitive format of the experimental population and use protocols that are specific to the experimental population in order to improve the training and practical application of the research findings.
... Moreover, increases in mean oxygen uptake (V _ O 2 ), and heart rate (HR) ( 18), paired with increases to the overall cost of running (C r ) 2 0 ) rang-ing between 1.6 and 11.6% ( 31) have been reported during TR bouts, compared with control or isolated running (control run, CR) after high-intensity cycling. Similarly, prior variable cadence cycling, at 80% V _ O 2 max, has been shown to elevate the metabolic cost of subsequent running in comparison with isolated running among national-level triathletes, slowing mean 5 km race times and decreasing velocity of subsequent running ( 3). ...
... The significant decrease in mean SL during the TR is consistent with previous findings ( 27). However, mean SF increased during the TR, in contrast to results previously stated ( 3,27). Despite the variation in the findings between the current study and those of previous studies, the evidence suggests that prior variable cadence cycling may induce perturbations to an individual's stride patterns during subsequent moderate intensity running. ...
Full-text available
This study sought to determine whether prior moderate intensity cycling is sufficient to influence the cardiorespiratory and biomechanical responses during subsequent running. Cardiorespiratory and biomechanical variables measured after moderate intensity cycling were compared with control running at the same intensity. Eight highly trained, competitive triathletes completed two separate exercise tests; 1) a 10-min control run (no prior cycling) and, 2) a 30-min transition run (preceded by 20-min of variable cadence cycling; i.e., run versus cycle- run). Respiratory, breathing frequency (fb), heart rate (HR), cost of running (Cr), rate constant, stride length and stride frequency variables were recorded, normalised and quantified at the mean response time (MRT), 3 min, 10 min (steady-state) and overall for the control (CR) and transition (TR) runs. Cr increased (p<0.05) at all respective times during the TR. V[Combining Dot Above]E/V[Combining Dot Above]CO2 and RER were significantly (p<0.01) elevated at the MRT and 10 min of the TR. Furthermore, overall mean increases were recorded for Cr, V[Combining Dot Above]E, V[Combining Dot Above]E/V[Combining Dot Above]CO2, RER, fb (p<0.01) and HR (p<0.05) during the TR. Rate constant values for oxygen uptake were significantly different between CR and TR (0.48 ± 0.04 vs. 0.89 ± 0.15; p < 0.01). Stride length decreased across all recorded points during the TR (p<0.05) and stride frequency increased at the MRT and 3 min (p<0.01). The findings suggest that at moderate intensity, prior cycling influences the cardiorespiratory response during subsequent running. Furthermore, prior cycling appears to have a sustained effect on the Cr during subsequent running.
... Load of a person sitting on a machine = 100 Kg = 100 x 9.81 = 980 = 1000 N Normal paddling RPM = 60-100 rpm Force applied at paddling = 50kg = 5 x 9.81 = 49.05 = 50 N A normal person applies 60-100 rpm in normal working conditions [9]. As per this assumption, we design the transmission of a system based on washing, rinsing and drying mechanisms, in order to calculate the speed of sprocket pinion we use maximum rpm. ...
Pedal-operated washing and drying machine (POWDM) is an inexpensive/ cut rate washing and drying machine buildup of simple and reliable available scrap parts in our everyday life and it is looking like a commercially available horizontal axis washer. It is a machine designed in the way that produces power over human pedaling and the drive mechanism; alters that motion into essential rotary motion of the internal drum. The modernization of this machine is revealed in the design simplicity. Its affordable parts, low cost of maintenance, most of all it is cheap so that everyone should afford it and it can have no impact on the environment. We proposed this to solve the issue of washing clothes and design a new generation for everyone in washing and drying clothes. POWDM is a new idea, which should do wash clothes like the automatic washing machine available in the market, with the specification of drying immediately after washing. Current techniques for washing clothes do not function well in underdeveloped rural areas. Lack of electricity makes electrical washing machines unfeasible. The proposed and designed pedal operated washing and drying machine is a leader because it solves the clothes washing and drying problems in an effective, inexpensive and practical way.
... By analyzing the performance of elite male and female triathletes in international Olympic distance triathlons from 2009 to 2012, Rüst et al. (2012b) found that the sex difference in running (14.3%) was greater than that which was evidenced for swimming (9.1%) and cycling (9.5%). In light of this observation, the relatively lower gender difference in cycling versus running may be associated with drafting, pacing and/or cadence on the bike (Bernard et al., 2003;Le Meur et al., 2009). However, the relative effects of these factors on the cycling and subsequent running performance of males as compared to females remain to be fully explored, and certainly warrant further study. ...
Full-text available
This brief review investigates how sex influences triathlon performance. Performance time for both Olympic distance and Ironman distance triathlons, and physiological considerations are discussed for both elite and non-elite male and female triathletes. The relative participation of female athletes in triathlon has increased over the last three decades, and currently represents 25–40% of the total field. Overall, the sex difference in both Olympic and Ironman distance triathlon performance has narrowed across the years. Sex difference differed with exercise mode and exercise duration. For non-elite Ironman triathletes, the sex difference in swimming time (≈12%) is lower than that which was evidenced for cycling (≈15%) and running (≈18%). For elite triathletes, sex difference in running performance is greater for Olympic triathlon (≈14%) than it is for Ironman distance triathlon (≈7%). Elite Ironman female triathletes have reduced the gap to their male counterparts to less than 10% for the marathon. The sex difference in triathlon performance is likely to be due to physiological (e.g., VO2max) and morphological (e.g., % body fat) factors but hormonal, psychological and societal (e.g., lower participation rate) differences should also be considered. Future studies should address the limited evidence relating sex difference in physiological characteristics such as lactate threshold, exercise economy or peak fat oxidation.
... A fundamental aspect that differentiates between Olympic and sprint distance triathlons and an ultra-triathlon is drafting in cycling; in contrast to shorter distances, drafting is not allowed in Half-Ironman and longer distances. It is well known that cycling before running leads to an alteration in running performance ( Bernard et al., 2003). Nevertheless, Ofoghi et al. (2016) demonstrated that triathletes, who were the fastest in swimming and cycling, were also the fastest in overall race time at the Olympic distance. ...
Full-text available
The aim of the present study was to examine the effects of the performance level and race distance on pacing in ultra-triathlons (Double, Triple, Quintuple and Deca), where pacing was defined as the relative time (%) spent in each discipline (swimming, cycling and running). All finishers (n = 3,622) in Double, Triple, Quintuple and Deca Iron ultra-triathlons between 1985 and 2016, classified into quartile groups (Q1, Q2, Q3 and Q4) with Q1 being the fastest and Q4 the slowest, were analyzed. Performance of all non-finishers (n = 1,000) during the same period was also examined. The highest rate of non-finishers was shown in Triple and Quintuple (24.4%) and the lowest in Deca (18.0%) Iron ultra-triathlons (χ2 = 12.1, p = 0.007, φC = 0.05). In swimming and cycling’s relative times (%), Deca (6.7 ± 1.5% and 48.8 ± 4.9%, respectively) was the fastest and Double (9.2 ± 1.6% and 49.6 ± 3.6%) Iron ultra-triathlon the slowest (p < 0.008) with Q4 being the fastest (8.3 ± 1.6% and 48.8 ± 4.3%) and Q1 the slowest (9.5 ± 1.5% and 50.9 ± 3.0%) (p < 0.001). In running, Double was relatively the fastest (41.2 ± 4.0%) and Deca (44.5 ± 5.4%) Iron ultra-triathlon the slowest (p < 0.001) with Q1 being the fastest (39.6 ± 3.3%) and Q4 the slowest (42.9 ± 4.7%) (p < 0.001). Based on these findings, it was concluded that the fastest ultra-triathletes spent relatively more time swimming and cycling, but less running highlighting the role of the latter discipline for the overall ultra-triathlon performance. Furthermore, coaches and ultra-triathletes should be aware of differences in pacing among Double, Triple, Quintuple and Deca Iron triathlons.
... While triathlon and duathlon events have some similar charac- teristics, the physiological consequences associated with the transition phases may invoke different physiological responses. Few studies have investigated the effects of cycling on a subsequent running bout ( Bernard et al., 2003;Gottschall and Palmer, 2000;Hue et al., 2000;Suriano et al., 2007) or running on subsequent cycling performance (Chapman et al., 2008;Gottschall and Palmer, 2000;Suriano et al., 2007;Vercruyssen et al., 2002). The compounding effects of a duathlon event on running performance have been minimally investigated (Moncada- Jiménez et al., 2009;Sparks et al., 2005;2013;Vallier et al., 2003). ...
Multisport events continue to grow in popularity among recreational, amateur, and professional athletes around the world. This study aimed to determine the compounding effects of the initial run and cycling legs of an International Triathlon Union (ITU) Duathlon simulation on maximal oxygen uptake (VO2max), ventilatory threshold (VT) and running economy (RE) within a thermoneutral, laboratory controlled setting. Seven highly trained multisport athletes completed three trials; Trial-1 consisted of a speed only VO2max treadmill protocol (SOVO2max) to determine VO2max, VT, and RE during a single-bout run; Trial-2 consisted of a 10 km run at 98% of VT followed by an incre-mental VO2max test on the cycle ergometer; Trial-3 consisted of a 10 km run and 30 km cycling bout at 98% of VT followed by a speed only treadmill test to determine the compounding effects of the initial legs of a duathlon on VO2max, VT, and RE. A repeated measures ANOVA was performed to determine differ-ences between variables across trials. No difference in VO2max, VT (%VO2max), maximal HR, or maximal RPE was observed across trials. Oxygen consumption at VT was significantly lower during Trial-3 compared to Trial-1 (p = 0.01). This decrease was coupled with a significant reduction in running speed at VT (p = 0.015). A significant interaction between trial and running speed indicate that RE was significantly altered during Trial-3 compared to Trial-1 (p < 0.001). The first two legs of a laboratory based duathlon simulation negatively impact VT and RE. Our findings may provide a useful method to evaluate multisport athletes since a single-bout incremental treadmill test fails to reveal important alterations in physiological thresholds.
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ABSTRACT: The aim of this study was to analyze the effect of a simulated Duathlon (5-20-5 km) on both energy cost and technique during running and pedaling. Four tests were performed in the laboratory: a-Maximal running; b-Maximal pedaling; c-Submaximal pedaling; d-Simulated Duathlon (5-20-5 km). Physiological (VO2, RER, EC and GE) and biomechanical variables (spatial-temporal during running; kinetics and kinematics during pedaling) were recorded. The main finding of this pilot study was to observe an impairment of physiological variables, but not for the biomechanical ones during the Duathlon. Energy cost of running and pedaling during the Duatlon increased by 7% compared to submaximal fatigue tests. Besides, during the submaximal tests, a progressive increase of the energy cost was observed. In conclusion, energy cost of running and pedaling during a Duathlon increase by comparing to cycling and running alone. However, no changes in running technique and pedaling kinetics were observed, and only pedaling kinematics was altered. Future studies should monitoring the electromyographic variables which would justify the increase of energy cost during running and pedaling observed in this study.
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Las carreras de fondo (comprendidas entre los 5 km hasta la maratón) han crecido en España tanto en número como en participación. Esto ha suscitado un gran interés en entrenadores y deportistas, que solicitan información y formación sobre los diferentes factores que afectan al rendimiento. Ante esta demanda, el número de investigaciones ha aumentado notablemente. El objetivo de esta revisión bibliográfica ha sido analizar los factores que afectan al rendimiento en carreras de fondo desde sus diferentes perspectivas. Para ello, se ha realizado una revisión bibliográfica en 3 bases de datos (Medline, SportDiscus y Google Scholar) y los factores han sido clasificados en 5 grandes grupos, subdivididos a su vez en diferentes apartados: 1- ambientales (aire/viento, temperatura, humedad, altura y pendiente del terreno), 2- ligados al entrenamiento (entrenamiento de resistencia, fuerza, en ambientes calurosos y en altura), 3- fisiológicos (VO2max, umbrales ventilatorios, economía de carrera, edad, género, tipos de fibras musculares, fatiga y raza), 4- biomecánicos (antropometría, leg-stiffness, flexibilidad, patrón de pisada, calzado, ortesis plantares y parámetros espacio-temporales) y 5- psicológicos (estrategias de intervención, dirección de la atención y música). La influencia de algunos de éstos sobre el rendimiento es ampliamente conocida; sin embargo, en el caso de algunos factores psicológicos (dirección de la atención y música) y biomecánicos (patrón de pisada y parámetros espacio-temporales) el número de estudios es escaso o los resultados poco concluyentes. La realización de más estudios, conjuntamente con el avance de las nuevas tecnologías y sistemas de medición, permitirá un mejor conocimiento sobre la temática. Abstract The number of competitions and participation on long-distance races (from 5 km to the marathon) in Spain has grown significantly during the last few years. Due to this popularity, both coaches and runners are interested on learning about the factors that affect long-distance running performance. Facing this new reality, scientific literature has been concerned about the aforementioned factors, and the amount of studies has considerably grown. Therefore, the purpose of this review is to analyse factors affecting long-distance running performance from different points of view. Literature review was performed through 3 different databases (Medline, SportDiscus and Google Scholar) and the factors were classified into 5 main groups, subdivided into different sections: 1- environmental (air/wind, temperature, humidity, altitude and slope of the ground), 2- training-related (endurance, resistance, training in hot environments and in altitude), 3- physiological (VO2max, thersholds, running economy, age, gender, muscle fibre type, fatigue and race), 4- biomechanical (anthropometry, leg-stiffness, flexibility, foot strike pattern, footwear, foot orthoses and spatio-temporal parameters) and 5- psychological (intervention strategies, direction of attention and music). Even though the influence of some of these factors on running performance in quite well-known, the influence of some psychological (direction of attention and music) and biomechanical factors (foot strike pattern and spatio-temporal parameters) is still unclear. There are few studies or the results cannot be generalized. Future studies and the progress of new technologies and measurement tools will provide a better understanding.
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The aim of the present study was to determine the effects of 40 km of cycling on the biomechanical and cardiorespiratory responses measured during the running segment of a classic triathlon, with particular emphasis on the time course of these responses. Seven male triathletes underwent four successive laboratory trials: (1) 40 km of cycling followed by a 10-km triathlon run (TR), (2) a 10-km control run (CR) at the same speed as TR, (3) an incremental treadmill test, and (4) an incremental cycle test. The following ventilatory data were collected every minute using an automated breath-by-breath system: pulmonary ventilation (V˙ E, l · min−1), oxygen uptake (V˙O2, ml · min−1 · kg−1), carbon dioxide output (ml · min−1), respiratory equivalents for oxygen (V˙ E/V˙O2) and carbon dioxide (V˙ E/V˙CO2), respiratory exchange ratio (R) respiratory frequency (f, breaths · min−1), and tidal volume (ml). Heart rate (HR, beats · min−1) was monitored using a telemetric system. Biomechanical variables included stride length (SL) and stride frequency (SF) recorded on a video tape. The results showed that the following variables were significantly higher (analysis of variance, P < 0.05) for TR than for CR: V˙O2 [51.7 (3.4) vs 48.3 (3.9) ml · kg−1 · min−1, respectively], V˙ E [100.4 (1.4) l · min−1 vs 84.4 (7.0) l · min−1], V˙ E/V˙O2 [24.2 (2.6) vs 21.5 (2.7)] V˙ E/V˙CO2 [25.2 (2.6) vs 22.4 (2.6)], f [55.8 (11.6) vs 49.0 (12.4) breaths · min−1] and HR [175 (7) vs 168 (9) beats · min−1]. Moreover, the time needed to reach steady-state was shorter for HR and V˙O2 (1 min and 2 min, respectively) and longer for V˙ E (7 min). In contrast, the biomechanical parameters, i.e. SL and SF, remained unchanged throughout TR versus CR. We conclude that the first minutes of the run segment after cycling in an experimental triathlon were specific in terms of V˙O2 and cardiorespiratory variables, and nonspecific in terms of biomechanical variables.
In order to find speed- and step-dependencies of temporal variability in gait, treadmill walking was examined in a speed range from 2 to 6 km/h and step rate from 60 to 160 steps/min. The duration of walking phases, i.e., stride cycle, step, stance, swing and double stance, were measured by using foot switches. Intrasubject variable error (VE) and coefficient of variation (CV) in each duration was regarded as an index of stability of gait within subjects. VE and CV decreased with walking speed in every phase, thereby supporting the hypothesis that faster movement is more stable than slower movement. CV in every phase was the least at the specific step rates which were linearly dependent on walking speed. The relationship between walking speed and step rate with the least CV was invariant among the different walking phases, and was close to that found in ‘free’ walk. There results suggest that the stability of gait in terms of CV in the duration of the walking phases is optimal for walking with freely chosen step rate at any given speed. The relevance of these findings to the optimality of the energy expenditure in walking is discussed.
The role of cycle ergometer pedal rate on the gradual increase in ventilation (VE), heart rate (HR), and oxygen uptake (VO2) accompanying continuous submaximal exercise is unknown. To examine this problem, five trained males (VO2peak = 4.00 +/- 0.27 l.min-1) performed 45 min of moderate intensity (MI, 127 W) and high-moderate intensity (HMI, 166 W) cycle ergometry both at pedal rates of 60 rpm and 90 rpm. Power output and pedal rate had an additive effect on the overall mean responses for VE, HR, and VO2, producing significantly higher values as power output and pedal rate increased. During continuous exercise, VE, HR, and VO2 increased progressively from the 10th to the 45th minute for all tests. However, the rates of increase and factors modifying the VE, HR, and VO2 responses were different. HR increased during all exercise tests an average of 10.8% independent of power output and pedal rate. VE increased 7.4% during MI exercise and 10% during HMI exercise independent of pedal rate. Similar power output dependent responses were observed for rectal temperature (Tr) and blood lactate. VO2 increased 4.4% for MI and HMI exercise at 60 rpm, and 8.2% for the same power outputs at 90 rpm, respectively. Increases in Tr, the oxygen cost of pulmonary ventilation and fat oxidation, and lactate removal were estimated to account for only 31-36% of the slow rise in VO2 for any single test. This suggests that 64-69% of the rise in VO2 was due to factors related to muscle use.(ABSTRACT TRUNCATED AT 250 WORDS)
Triathletes typically train each triathlon event separately. Therefore, to determine the cardiovascular and thermal differences between training and triathlon performance, nine male triathletes performed a simulated 75-min (40 km) control bike and a 40-min (10 km) control run at 70% of maximal oxygen uptake. Control data were compared to data derived from a simulated triathlon (0.8-km swim, 75-min bike, and 40-min run). Results demonstrated that prior swimming significantly decreased (P less than 0.05) triathlon cycling work output (191 +/- 4.2 to 159 +/- 7.6 W) producing mean differences (P less than 0.05) in oxygen uptake (3.18 +/- 0.1 to 3.01 +/- 0.11.min-1), ventilation (84.7 +/- 4 to 80.4 +/- 4.21.min-1), stroke volume (128 +/- 7.1 to 118 +/- 3.5 ml.min-1), cardiac output (20.7 +/- 1.2 to 18.9 +/- 0.8 l.min-1), mean arterial pressure (105 +/- 3.8 to 96 +/- 7.9 mm Hg) and rectal temperature (38.2 +/- 0.2 to 38.4 +/- 0.3 degrees C). Triathlon running, while performing identical control work output, elicited significant increases (P less than 0.05) in oxygen uptake (3.41 +/- 0.1 to 3.85 +/- 0.1 l.min-1), ventilation (91.3 +/- 3.3 to 104.2 +/- 2.8 l.min-1), heart rate (161 +/- 3.1 to 174 +/- 3.6 beats.min-1), arteriovenous oxygen difference (15.3 +/- 0.2 to 17.2 +/- 0.3 ml.100 ml-1) and rectal temperature (38.3 +/- 0.2 and 39.2 +/- 0.3 degrees C) with significantly lower (P less than 0.05) stroke volume (138 +/- 2.4 to 129 +/- 3.6 ml.min-1) and mean arterial pressure (102 +/- 11.2 to 89 +/- 5.5 mm Hg).(ABSTRACT TRUNCATED AT 250 WORDS)
This experiment was designed to estimate the optimum pedal rates at various power outputs on the cycle ergometer. Five trained bicycle racers performed five progressive maximal tests on the ergometer. Each rode at pedal rates of 40, 60, 80, 100, and 120 rev X min-1. Oxygen uptake and heart rate were determined from each test and plotted against pedal rate for power outputs of 100, 150, 200, 250, and 300 W. Both VO2 and heart rate differed significantly among pedal rates at equivalent power outputs, the variation following a parabolic curve. The low point in the curve was taken as the optimal pedal rate; i.e., the pedal rate which elicited the lowest heart rate or VO2 for a given power output. When the optimum was plotted against power output the variation was linear. These results indicate that an optimum pedal rate exists in this group of cyclists. This optimum pedal rate increases with power output, and when our study is compared to studies in which elite racers, or non-racers were used, the optimum seems to increase with the skill of the rider.
Alterations in gas exchange were studied in man during exercise increasing in increments of 5 w each minute, to determine the noninvasive indicators of the onset of metabolic acidosis (anaerobic metabolism). Expired airflow and CO2 and O2 tensions at the mouth during the breath were continuously monitored with rapidly responding gas analyzers. These measurements were recorded directly as well as processed by a minicomputer, on line, to give minute ventilation (VE), CO2 production (VCO2), O2 consumption (VO2), and the gas exchange ratio (R), breath by breath. The anaerobic threshold (AT) could be identified by the point of nonlinear increase in VE, nonlinear increase in VCO2, an increase in end tidal O2 without a corresponding decrease in end tidal CO2, and an increase in R, as work rate was increased during an incremental exercise test. Of these measurements, R was found least sensitive. The AT was determined in 85 normal subjects between 7 and 91 yr of age, by these techniques. The lower limit of normal was 45 w (VO2 = 1 liter/min) while values for very fit normal adults were as high as 180 w. The patients studied with cardiac disease above functional class I have lower anaerobic thresholds than the least fit normal subjects. The 1 min incremental work rate test is associated with changes in gas exchange which can be used as sensitive on line indicators of the AT, thus bypassing the need for measuring arterial lactate or acid base parameters to indicate anaerobiosis.
The factors limiting force production and exercise endurance time have been briefly described, together with some of the changes occurring at various sites within the muscle and central nervous system. Evidence is presented that, in fatigue of sustained maximal voluntary contractions (MVC) executed by well-motivated subjects, the reduction in force generating capacity need not be due to a decline in central nervous system (CNS) motor drive or to failing neuromuscular transmission, but can be attributed solely to contractile failure of the muscles involved. However, despite this conclusion, both the integrated electromyogram (EMG) and the mean firing rate of individual motor units do decline progressively during sustained MVC. This, however, does not necessarily result in loss of force since the parallel slowing of muscle contractile speed reduces tetanic fusion frequency. It is suggested that the range of motoneuron firing rates elicited by voluntary effort is regulated and limited for each muscle to the minimum required for maximum force generation, thus preventing neuromuscular transmission failure and optimizing motor control. Such a CNS regulating mechanism would probably require some reflex feedback from the muscle.