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Technique and energy saving are two variables often considered as important for performance in cycling and related to each other. Theoretically, excellent pedalling technique should give high gross efficiency (GE). The purpose of the present study was to examine the relationship between pedalling technique and GE. 10 well-trained cyclists were measured for GE, force effectiveness (FE) and dead centre size (DC) at a work rate corresponding to ~75% of VO(2)max during level and inclined cycling, seat adjusted forward and backward, at three different cadences around their own freely chosen cadence (FCC) on an ergometer. Within subjects, FE, DC and GE decreased as cadence increased (p < 0.001). A strong relationship between FE and GE was found, which was to great extent explained by FCC. The relationship between cadence and both FE and GE, within and between subjects, was very similar, irrespective of FCC. There was no difference between level and inclined cycling position. The seat adjustments did not affect FE, DC and GE or the relationship between them. Energy expenditure is strongly coupled to cadence, but force effectiveness, as a measure for pedalling technique, is not likely the cause of this relationship. FE, DC and GE are not affected by body orientation or seat adjustments, indicating that these parameters and the relationship between them are robust to coordinative challenges within a range of cadence, body orientation and seat position that is used in regular cycling.
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Eur J Appl Physiol (2011) 111:2885–2893
DOI 10.1007/s00421-011-1914-3
123
ORIGINAL ARTICLE
The relationship between cadence, pedalling technique and gross
eYciency in cycling
Stig Leirdal · Gertjan Ettema
Received: 20 October 2010 / Accepted: 7 March 2011 / Published online: 25 March 2011
© The Author(s) 2011. This article is published with open access at Springerlink.com
Abstract Technique and energy saving are two variables
often considered as important for performance in cycling
and related to each other. Theoretically, excellent pedalling
technique should give high gross eYciency (GE). The pur-
pose of the present study was to examine the relationship
between pedalling technique and GE. 10 well-trained
cyclists were measured for GE, force eVectiveness (FE) and
dead centre size (DC) at a work rate corresponding to
»75% of VO2max during level and inclined cycling, seat
adjusted forward and backward, at three diVerent cadences
around their own freely chosen cadence (FCC) on an
ergometer. Within subjects, FE, DC and GE decreased as
cadence increased (p< 0.001). A strong relationship
between FE and GE was found, which was to great extent
explained by FCC. The relationship between cadence and
both FE and GE, within and between subjects, was very
similar, irrespective of FCC. There was no diVerence
between level and inclined cycling position. The seat
adjustments did not aVect FE, DC and GE or the relation-
ship between them. Energy expenditure is strongly coupled
to cadence, but force eVectiveness, as a measure for pedalling
technique, is not likely the cause of this relationship. FE,
DC and GE are not aVected by body orientation or seat
adjustments, indicating that these parameters and the
relationship between them are robust to coordinative
challenges within a range of cadence, body orientation and
seat position that is used in regular cycling.
Keywords Cadence · Inclined · Level · Pedalling ·
Technique
Introduction
In cycling, not only the work capacity but also a proper
technical execution of the propulsive movements is often
considered to be important for performance. In cycling,
force eVectiveness (FE) is often used as a parameter to indi-
cate the quality of pedalling technique (e.g., Patterson and
Pearson 1983; Ericson and Nisell 1988; Coyle et al. 1991;
Sanderson 1991; Sanderson and Black 2003; Zameziati
et al. 2006; Candotti et al. 2007; KorV et al. 2007). FE is
the ratio between the force directed 90° on the crank arm
and the total resultant force on the pedal. Furthermore, it is
generally believed that high gross eYciency (GE) is related
to good technique in general and high FE speciWcally (e.g.,
Zameziati et al. 2006; Candotti et al. 2007). In a mechani-
cally eVective pedalling technique with high FE a large
component of the generated force is directed perpendicu-
larly on the crank arm. Forces directed otherwise, i.e., radially
to the crank, do not contribute to work rate and the associ-
ated energy cost is wasted. Thus, in principle, FE aVects
GE in a direct manner. A number of studies have demon-
strated a moderate to strong relationship between FE and
GE (e.g., Zameziati et al. 2006; Candotti et al. 2007).
On the other hand, various studies have shown that for
an eVective and powerful crank cycle, one must generate
considerable radial forces. This is due to the mechanical
constraints within the rider–bicycle system (Kautz and
Hull 1993). Because of the constraints, it is not a priori so
that the most eVective force is generated with the least
muscular eVort. Furthermore, inertial and gravitational
forces add to the ineVective component of pedal forces
Communicated by Jean-René Lacour.
S. Leirdal (&) · G. Ettema
Department of Human Movement Science,
Norwegian University of Science and Technology (NTNU),
Dragvoll Idrettssenter 3 etg, 7491 Trondheim, Norway
e-mail: stig.leirdal@svt.ntnu.no
2886 Eur J Appl Physiol (2011) 111:2885–2893
123
(Kautz and Hull 1993), which are of no physiological
consequence. This raises questions on both the origin as
well as the signiWcance of the apparent relationship
between FE and GE.
GE indicates the total metabolic rate, including muscle
work rate, for a given external work rate, and FE is the
resultant outcome of all muscle activation. Thus, an FE–GE
relationship that is unaVected by other factors would indi-
cate that the total amount of muscle work done at a given
external work rate (via GE) and the net coordinative out-
come (via FE) are tightly coupled.
Cadence is shown to aVect both FE (Patterson and Pear-
son 1983; Sanderson 1991; Candotti et al. 2007; Lorås et al.
2009) and GE (Seabury et al. 1977; Coast and Welch 1985;
Belli and Hintzy 2002; Foss and Hallen 2004, 2005; Sam-
ozino et al. 2006; Hansen and Sjøgaard 2007). Body orien-
tation (e.g., inclination as in inclined cycling) and seating
position (e.g., diVerences between road cycling, time trial
and triathlon cycling, see Faria et al. 2005) are factors that
possibly aVect both FE and/or GE (e.g., Bertucci et al.
2005; Brown et al. 1996; Caldwell et al. 1998, 1999; Millet
et al. 2002; Faria et al. 2005; Heil et al. 1997; Price and
Donne 1997; Ricard et al. 2006; Umberger et al. 1998;
Welbergen and Clijsen 1990). While both FE and GE are
studied quite extensively related to these factors, relatively
little is done on the relationship between FE and GE, i.e., if
the relationship is independent of other factors. Particu-
larly, the role of cadence is of importance and may explain
any relationship between FE and GE if it aVects both in a
similar fashion.
Recently, Leirdal and Ettema (2010) introduced a new
pedalling technique parameter, which described the dead
centre (DC) and was deWned as the minimum power
divided by the average power during the pedal stroke. It
had a stronger relationship with GE than FE and it was,
unlike FE, not aVected by inertial forces that increase with
cadence. Thus, it could be hypothesised that DC is not
aVected by cadence in the way that FE and GE are. The
inXuence of cadence on DC has not been investigated
before. By studying, in detail, how the relationship between
on the one hand FE and DC (technique) and on the other
GE (energy expenditure) is aVected by cadence, more
insight may be obtained in how cycling technique and
energy expenditure are related.
In the present study, we therefore investigated the rela-
tionship between pedalling technique (FE and DC) and GE,
over three cadences, for level and inclined cycling position,
and for three seating positions. We took the freely chosen
cadence (FCC) of the cyclists as a departure point to set the
range of cadences. This increased the total range of
cadences and allowed for studying the eVect of absolute
(inter-individual diVerences) as well as relative cadence
(intra-individual diVerences).
Method
Subjects
The study was approved by the local ethics committee and
all participants signed an informed written consent before
participating in the study. Ten well-trained cyclists, at a
national and regional level, participated in the study. The
participant’s physical characteristics are presented in
Table 1.
Protocol and analysis
All participants met in the lab on two occasions. On the Wrst
occasion, they performed an incremental test at freely
chosen cadence (FCC) on a Velotron ergometer with a
computer-controlled electro-magnetic brake mechanism
(Velotron, Racermate inc., Washington). This ergometer
generates a constant power condition, independent of
cadence. The participants wore cycling shoes and the seat
and handle bar position on the ergometer was adjusted to
the preferred sitting position for each participant. During
the test, the participants did not receive any information
about their pedal rate. After a 10-min warm-up at 100 W,
the participants performed an increasing work rate protocol
that started at 100 W and had a 50 W increment every
2 min until exhaustion. Exhaustion was deWned as meeting
three of the four following criteria: (1) within 5 BPM from
the participants self-reported maximal heart rate (HRmax),
(2) above 7.5 mmol l¡1 in blood lactate concentration, (3)
the respiratory exchange ratio (RER) >1.1, and (4) a VO2
which stops increasing or starts decreasing with increased
work rate. Pedal rate, oxygen consumption, and heart rate
were measured continuously.
Gas exchange values were measured by open-circuit
indirect calorimetry using an Oxycon Pro apparatus (Jaeger
GmbH, Hoechberg, Germany). Before each measurement,
the VO2 and VCO2 gas analyzers were calibrated using
high-precision gases (16.00 §0.04% O2 and 5.00 §0.1%
CO2, Riessner-Gase GmbH & co, Lichtenfels, Germany).
The Xow meter was calibrated with a 3-L volume syringe
(Hans Rudolph Inc., Kansas City, MO). Heart rate (HR)
was measured with a heart rate monitor (Polar S610, Polar
Electro OY, Kempele, Finland), using a 5-s interval for
data storage. VO2max was deWned as the highest 1-min
Table 1 Physical characteristics of the participants in study
Age
(years)
Height
(cm)
Body
mass (kg)
VO2peak
(ml kg min¡1)
Maximal
aerobic
power (watt)
Avg 23.4 183.2 77.3 58.1 370
Std 11.7 6.3 9.5 3.3 42
Eur J Appl Physiol (2011) 111:2885–2893 2887
123
average VO2 during the test. Maximal heart rate was deW-
ned as the highest value that was attained, in average over a
5-s period at the Wnal stage of the protocol. Blood lactate
concentration was measured 2 min after completion of the
VO2max test (10.6 mmol l¡1§1.9) by taking 5 L samples
from the Wngertip by a Lactate Pro LT-1710t(ArkRay Inc,
Kyoto, Japan). This system was validated in literature
(Medbø et al. 2000; Pyne et al. 2000; Baldari et al. 2009).
The second occasion, 3 days after the incremental test,
all participants performed a protocol consisting of eight
repetitions of 5 min cycling at a work rate that was esti-
mated to elicit »80% of their VO2max as was determined in
the Wrst test. Also during this test, the participants wore
cycling shoes. The eVorts were done at level and in tilted
(11%, i.e., 6.3° inclined) position (Fig. 1b), all at preferred
seat position. In the tilted position, the entire ergometer was
tilted by elevating the front. Both positions (level and
tilted) were performed at three cadences (FCC, FCC ¡10
and FCC + 10 rpm), giving six conditions. In addition, the
level position was also performed with the seat moved for-
ward and backward from the preferred position, giving two
additional conditions. Corresponding seat adjustments were
made in height as well, such that the angle of the line
between crank centre and (rock point of the) seat was
rotated by approximately 3° in both directions. This led to a
similar total angle change of about 6° as in levels versus
inclined position. For all forward and backward positions
the distance between hip (major trochanter) and crank cen-
tre was unaltered in comparison with preferred seat position
(Fig. 1c). This was done using a tape measure. The handle-
bars were moved in the same manner. Thus, in these condi-
tions, the orientation of the upper body was not altered.
During all tests on the second occasion, the participants
received continuous feedback about their cadence and were
asked to keep it at a preset level. The FCC was set as the
average cadence that was used the last minute during the
incremental test at the work rate increment nearest 80% of
VO2max. To avoid any eVect of fatigue, learning eVect, or
drift of energy expenditure in the statistical analysis, all
conditions were done in a diVerent order for each partici-
pant. Oxygen consumption and heart rate were measured
continuously. GE was calculated as the ratio of work rate
over metabolic cost rate as calculated from VO2 and RER.
All measurements on »80% VO2max showed RER values
below 1.0 (RER was 0.89 §0.03) indicating no signiWcant
anaerobic contribution. Kinetics was sampled for 5 times
for 10 s at the end of each minute during the 5-min work
periods.
Crank and pedal kinematics were recorded using a Pro-
ReXex (Qualisys, Sweden) 3D motion capture system with
Fig. 1 Conditions in present
study. aNormal condition.
bInclined condition. cSeat
preferred backward and forward
position
= α11%
AB
C
2888 Eur J Appl Physiol (2011) 111:2885–2893
123
8 cameras in the same way as described by Ettema et al.
(2009). Two spherical reXective markers were placed on
extensions of both pedals in the sagittal plane of cyclist and
bicycle. The positions of these markers were used to deter-
mine pedal orientation and crank angle. Both pedals were
equipped with two force cells (Model 9363, Revere, capacity
250 kg per cell, The Netherlands), detecting pedal normal
and shear forces (Ettema et al. 2009). The pedals were
calibrated by applying full normal forces and full shear
forces of known magnitude. A constant proportional cross-
talk between the normal and shear forces of a single pedal
was detected (<3%) and taken into account by building a
gain matrix.
All data were recorded using the QTM software (Quali-
sys, Sweden) at a sample rate of 500 Hz and further
processed in Matlab (Mathworks, US). All data were low-
pass Wltered (10 Hz, 8th order, zero lag Butterworth). After
correction for acceleration artefacts (Ettema and Huijing
1994), pedal normal and shear forces were transformed to
crank shear and normal forces by rotation of the coordina-
tion system from pedal to crank using the angle between
pedal and crank as calculated from the kinematical data.
The vector sum of right and left pedal forces (in the crank
coordinate system) was used for further analysis (Lorås
et al. 2009). This leads to higher FE values than consider-
ing the pedals separately, mainly because of the elimination
of the negative eVect of gravity during the up-stroke.
Normal crank force was considered to be the eVective
force component. Thus, the ratio of normal force over
total force was deWned as FE. FE was calculated as aver-
age of the 5 £10 s measurements from each 5-min work
period.
DC was deWned as the lowest work rate (average of
top and bottom dead centre) divided by the average work
rate (Leirdal and Ettema 2010). Thus, this is a parameter
describing the evenness of work rate generation; 100%
indicates a perfect circular work rate generation,
whereas 0% indicates that the work rate at the DC equals
zero.
Power was calculated as the product of crank moment
(i.e., eVective (normal) crank force £crank arm) and crank
angular velocity. Continuous crank angular velocity was
calculated from crank angles using a 5-point diVerentiating
Wlter. The average crank cycle (for all variables) was calcu-
lated by interpolation of the crank angle—variable data to
360 samples, i.e., 1 sample per degree crank angle (Ettema
et al. 2009).
To investigate how technique (FE, DC) and eYciency of
energy consumption (GE) relate to each other, and how
cadence may aVect this relationship, we performed correla-
tion matrix analysis as well as multiple regression analysis
for GE with FE, DC, FCC and work rate as independent
variables.
Statistics
All statistics were performed using Statistical Package for
Social Sciences 15.0 (SPSS). The analysis consisted of two
parts. Firstly, to conWrm or refute Wndings in the literature,
the general eVect of cadence (in the range of 20 rpm around
FCC) and position on the variables of interest was exam-
ined: the intra-individual eVects of position and cadence on
GE, FE, and DC was analysed using a 2-way ANOVA
(cadence and body position) and a 1-way ANOVA (seat
position). FCC and absolute work rate were implemented
as covariates. The second and main part of the analysis
regarded the eVect of cadence on the relationship between
technique and energy expenditure: the inter-individual rela-
tionships between GE (dependent) and FE, DC, FCC, and
work rate (independent variables) was performed by multi-
ple regression analysis at the three cadences. Furthermore,
Pearson’s correlations between variables were compared.
This approach could not only indicate if, but also how FE
and GE are related. Normality of the data distribution was
checked with the one-sample Kolmogorov–Smirnov test.
All data were considered normally distributed (all pvalues
>0.337). The signiWcance level was set at p<0.05.
Results
The FCC in the main experiment (at the predicted work rate
of 80% VO2max, averaging 210 W) was 96 §9.1 rpm
(range 75–107). Thus, the FCC ¡10 and FCC + 10 condi-
tions were performed on 86 §9.1 and 106 §9.1 rpm,
respectively. The load in this test elicited 75% VO2max
instead of the predicted 80% during the steady-state
cycling.
The 2-way ANOVA showed the following results for GE,
FE and DC (average results are presented in Fig. 2). GE, FE
and DC declined signiWcantly (p< 0.001) with each increase
in cadence in a similar way. Body orientation did not seem to
have any eVect on either FE (p= 0.307), GE (p= 0.823) or DC
(p= 0.166). Seat position had no eVect on GE (p= 0.58) or
DC (p= 0.978). The eVect on FE was just not signiWcant
(p= 0.058). No signiWcant cadence–orientation interaction was
detected (FE, p= 0.090; GE, p= 0.794; and DC, p= 0.382).
The weak interaction trend for FE was localized between FCC
and FCC + 10, which was diVerent between the level and
inclined orientation (p= 0.036). Both work rate (mean 210 W,
§40 W) and FCC diVered between participants in present
study. Absolute work rate aVects GE (Leirdal and Ettema
2009) and possibly FE and DC directly as well as being depen-
dent on cadence. Therefore, we also treated absolute work rate
and FCC as a covariate and examined its eVect. The statistical
Wndings using work rate as a covariate remained unaltered
except for DC: cadence on FE, p= 0.001; on DC, p= 0.164;
Eur J Appl Physiol (2011) 111:2885–2893 2889
123
on GE, p= 0.027; orientation on FE, p= 0.308; on DC,
p= 0.553; on GE, p= 0.172; interaction on FE, p= 0.981; on
DC, p= 0.424; on GE, p= 0.708. Thus, the weak interaction
trend on FE is explained by work rate diVerences. When using
FCC as a covariate, all signiWcant eVects on FE, DC and GE
disappeared (all p> 0.175). In summary, within a subject,
cadence was the main variable inXuencing FE, DC and GE in a
similar way. Yet, these eVects seemed to be related to the sub-
ject’s FCC such that cyclists with a high FCC tend to show a
cadence eVect and those with low FCC did not.
Body orientation and seating position did not seem to have
any eVect on any of FE, DC, and GE. We double checked this
by comparing the regression lines for the various conditions
with the line of identity. In all cases, the regression estimate for
FE, DC, and GE between any of the comparable conditions (4
at FCC, 2 at each other cadence) did not signiWcantly diVer
from the line of identity (i.e., the intercept = 0 and slope = 1).
Thus, we could reduce the data by comparing the mean data
for all conditions at each cadence. Table 2 shows a correlation
matrix of all variables of interest. It appears that over the three
cadences, inter-individual diVerences in FE and GE, and to a
lesser extent also DC, are very consistent. FCC is strongly cor-
related with FE at all cadences, but not with DC. DC and FE
are not related. Work rate correlates well with FCC, FE and
GE. In the multiple regression analysis, for all three cadences,
FCC was the only signiWcant variable that remained, indepen-
dent of variable selection method, signiWcantly explaining the
variance in GE. Still, in isolation, also FE and work rate
showed signiWcant correlations with GE (Table 2). In other
words, FCC correlated strongest with GE (see Table 2), and
FE and work rate did not signiWcantly improve the prediction
of GE, likely because they overlap in explaining the variance
in FCC. Figure 3 shows FE and GE for all subjects and
cadence against absolute cadence and indicates that FE and
GE are tightly coupled to absolute cadence, irrespective of
FCC. It is important to note that the intra-individual relation-
ships (three points per subject, not shown in Wgure, but slopes
are presented in the caption) were very similar to the overall
relationship shown in the Wgure.
Although the mean values of both GE and FE are clearly
aVected by cadence (see ANOVA results above and Fig. 3),
the changes are very consistent as indicated by the FE–FE and
GE–GE correlations between cadences and the intra-class cor-
relation (ICC) values (Table 2). Therefore, we also used the
grand mean data of all conditions to estimate the average rela-
tionship between GE, FE and FCC. This led to a correlation
between FE–GE of 0.660, which was just signiWcant
(p= 0.037), between FCC and GE of ¡0.812 (p= 0.004), and
between FCC and FE of ¡0.914 (p< 0.001).
Discussion
The present study showed that cadence has a strong nega-
tive and similar eVect on both FE and DC, as well as GE,
which is in line with the literature for both FE (Patterson
and Pearson 1983; Sanderson 1991; Candotti et al. 2007;
Lorås et al. 2009) and GE (Seabury et al. 1977; Coast and
Welch 1985; Belli and Hintzy 2002; Foss and Hallen 2004,
2005; Samozino et al. 2006; Hansen and Sjøgaard 2007).
The same eVect for DC has, to our knowledge, not been
reported before. The multiple regression analysis (plus cor-
relation matrix) showed that both FE and GE are strongly
aVected by absolute cadence and thus by FCC. This Wnding
is important when interpreting the relationship between FE
and GE, which is probably not a causal one.
Within the range of frequencies used by this group of
cyclists, there is clear and linear (negative) relationship
between absolute cadence and GE, and even more so
between cadence and FE (Fig. 3). It may be tempting to
Fig. 2 The eVect of cadence and body orientation on FE (top), DC
(middle) and GE (bottom). FE, DC, and GE declined with increasing
cadence (p< 0.001). Body orientation or seat adjustments did not have
any impact. Vertical bars indicate SEM
0
5
10
15
20
25
30
35
DC ( -)
Tilt
Level
Forward
Backward
0.25
0.29
0.33
0.37
0.41
0.45
FE ( -)
18.0
19.0
20.0
21.0
22.0
FCC -10 FCC FCC + 10
GE (%)
2890 Eur J Appl Physiol (2011) 111:2885–2893
123
conclude that the reduced FE with increasing cadence
causes the cadence–GE relationship, in other words, that
GE is directly aVected by FE. However, this is unlikely
because the cadence-induced FE reduction is explained by
inertial mechanisms (Lorås et al. 2009) that have no bear-
ing on energy consumption. The increased energy cost for
moving the lower extremities is a more likely explanation.
The Xuctuations in internal kinetic energy (rotation of the
lower extremities) increase with cadence. Although this
energy Xow can be utilised as external work (see Kautz and
Neptune 2002; Ettema and Lorås 2009), it is likely associ-
ated with an increased energy cost and thus aVects
eYciency negatively. There are no studies, however, that
have properly investigated the amount of this cost. (Note:
These Xuctuations are often referred to as internal work and
considered fully as energy loss; various biomechanical
analyses have shown this to be a Xaw; for discussion, see
e.g., Kautz and Neptune 2002 and Ettema and Lorås 2009.)
A higher cadence will also increase the inertial, non-muscu-
lar component of the pedal forces (Kautz and Hull 1993;
Ettema et al. 2009; Lorås et al. 2009), which are closely
related to the kinetic energy Xuctuations. An increase in
inertial forces increases the radial force component in par-
ticular, and thereby aVects FE in a negative way (e.g.,
Kautz and Hull 1993; Kautz and Neptune 2002; Lorås et al.
2009). Kautz and Neptune (2002) even argue that “eVective
force” is a misnomer. Thus, the similarity in cadence eVect
on eYciency and FE may be explained by two separate
aspects of a common mechanism. However, this does not
mean that force eVectiveness is aVecting eYciency. The
inertial forces that aVect the non-propulsive force compo-
nent have, by deWnition, no associated metabolic cost.
Table 2 Correlation matrix of signiWcant relationships between FCC, work rate, and DE, FE, and GE at three cadences
Correlations with a signiWcance <0.001 are shown in bold. pvalues are given in parentheses. These are generally very high, except for DC between
FCC ¡10 and FCC + 10. The (average measure) ICC for DC, FE and GE are shown in the left bottom corner
* The correlations between the same variables but diVerent cadence
FCC 10 FCC FC + 10
Work
rate DC FE GE DC FE GE DC FE GE
0.824
(0.003)
0.906
(<0.001)
0.727
(0.017)
0.889
(0.001)
0.782
(0.008)
0.908
(<0.001)
0.870
(0.001)
FCC
0.784
(0.007)
0.848
(0.002)
0.684
(0.029)
0.866
(0.001)
0.730
(0.017)
Work
Rate
0.798*
(0.006)
DC
FCC 10
0.966*
(<0.001)
0.936*
(<0.001)
0.724
(0.018)
FE
0.947*
(<0.001)
0.885*
(0.001)
GE
0.913*
(<0.001)
DC
FCC
0.653
(0.040)
0.986*
(<0.001)
0.766
(0.010)
FE
0.653
(0.041)
0.967*
<0.001)
GE
CCI
DC FE GE DC
FCC + 10
0.905 0.987 0.976
0.789
(0.007)
FE
Eur J Appl Physiol (2011) 111:2885–2893 2891
123
Lorås et al. (2009) showed that FE of the muscular force
component is almost independent of cadence and relatively
high (>0.8) (Lorås et al. 2009). Thus, the changes in eVec-
tive crank forces are likely mainly caused by the inertial
force component, which was also indicated by Kautz and
Hull (1993) and Kautz and Neptune (2002). The present
results conWrm this notion that the cadence–FE relationship
is caused by a mechanism that is extremely consistent,
within and between subjects. Not only do all cyclists show
the same trend when changing form FCC ¡10 to FCC +
10 rpm, but this trend is identical with the inter-individual
diVerence that is created by choice of cadence (FCC)
(Fig. 3a). Furthermore, the multiple regression analysis
demonstrates that cadence (or FCC) rather than the associ-
ated FE determines GE. The increase of metabolic cost
(decrease in eYciency) can therefore not be linked to the
decrease in FE, at least not in a direct causal manner.
Beside the assumed metabolic cost of rotating the legs,
extra costs may occur because high cadence requires addi-
tional muscle activity for coordination. Zameziati et al.
(2006) reported a signiWcant FE–GE relationship, deter-
mined over a range of work rates at 80 rpm cadence. This
may be explained in a similar way. When increasing work
rate at one cadence, the ineVective inertial forces will
remain constant while the propulsive force must increase to
increase power. This will automatically lead to an enhanced
FE which is not necessarily indicating an improved tech-
nique (work rate has a diminishing eVect on the inertial
force contribution). Work rate also has a positive eVect on
eYciency but via a diVerent mechanism (see Ettema and
Lorås 2009).
Absolute work rate co-varies negatively with FCC and
may be a partial explanation for the cadence–GE relationship.
Because of the general work rate–eYciency relationship
(Ettema and Lorås 2009), a higher work rate (i.e., lower
FCC) will result in a higher GE. However, the intra-
individual eVect of cadence on GE is not aVected by the
work rate that was applied. Thus, the work rate eVect does
not explain the entire relationship between cadence and GE.
Leirdal and Ettema (2010) found that inertial eVects not
to aVect DC. Still, within each subject, cadence negatively
aVects DC when using a high FCC. Furthermore, Leirdal
and Ettema (2010) reported an inter-individual relationship
between DC and GE. Thus, it seems reasonable to suggest
that the diminishing DC with increasing cadence explains
the relationship between cadence and GE. However, the
Wnding by Leirdal and Ettema (2010), i.e., the DC–GE rela-
tionship, was not reproduced in the present study, which
leaves this proposed explanation open for debate. A reason
for the contradicting results of this study and Leirdal and
Ettema (2010) may be the type of bicycle–ergometer
system that was used. Leirdal and Ettema (2010) used a
racer bicycle with regular gears on resisting rollers,
whereas in the present study a computer-controlled electro-
magnetic brake system was used. Leirdal and Ettema
(2009) showed that these systems have a diVerent outcome
on the choice of cadence in relation to work rate. Thus,
cycling technique (e.g., DC) may also have been aVected by
the choice of ergometer system. This may also explain the
relative low FE values as compared with other studies (e.g.,
Dorel et al. 2009; Lorås et al. 2009; Sanderson and Black
2003; Hug et al. 2008). Our lower FE values cannot be
explained by the method of calculation; Lorås et al. (2009)
showed that this method leads to higher values rather than
Fig. 3 FE (a) and GE (b) plotted against absolute cadence. Data are
all subjects for all three cadences each subject performed at. The over-
all linear regression lines are indicated in the diagrams. The correla-
tions were ¡0.935 (FE) and ¡0.825 (GE), p< 0.001. The regression
for each subject (3 data points) are not shown, but the slopes of these
were not diVerent from the slope of the regression of all data; FE: indi-
vidual slopes ¡0.0051 §0.0009 versus all data ¡0.0056; GE: indi-
vidual slopes ¡0.103 §0.042 versus all data ¡0.128
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
60 70 80 90 100 110 120
15
16
17
18
19
20
21
22
23
24
25
B
A
60 70 80 90 100 110 120
FE (-)
GE (%)
Cadence (rpm)
2892 Eur J Appl Physiol (2011) 111:2885–2893
123
lower. The data by Lorås et al. (2009) were collected in the
same laboratory with identical measurement equipment and
calculation algorithms and a similar subject group. The
only diVerence was the type of ergometer/bicycle that was
used. This supports the notion that the type of ergometer
may aVect these technique values considerably.
There was no diVerence on any parameter between level
and tilted cycling or between preferred, forward, and back-
ward seat position. FE, DC and GE showed almost identical
values and eVects of cadence in both level and tilted cycling
and for the three seat positions. This is quite a noteworthy
Wnding as it suggests that the individual cyclist has his own
pedalling characteristic that is unaVected by (upper) body
orientation. The present results are in disagreement with the
notion that cycling technique and thereby power production
and energy consumption is aVected by relatively small
changes in body orientation as occur in practice (e.g., Cald-
well et al. 1998; Heil et al. 1997; Price and Donne 1997).
The high ICC values for FE, DC and GE between condi-
tions conWrm the notion that FE, DC and GE are very sub-
ject speciWc. The changes between the various orientation
and seating conditions (about 6° rotation) may appear mar-
ginal. This could explain the lack of any eVect of these
parameters. However, from a practical standing, these
changes are quite large: to obtain a change of 3° in the seat–
crank angle, the seat was shifted approximately 4 cm. Fur-
thermore, changes in other technique variables caused by
such position changes have been detected: unpublished
results from our laboratory indicate that the 6° rotation of
the cyclist (inclined position) or the lower extremities (by
seat position) cause a phase shift of the crank cycle (see
also McGhie and Ettema 2011) of the same amount (i.e., 6
degrees); Umberger et al. (1998) reported relatively small
but signiWcant changes in power at maximal eVort (about
4 W per degree seat–crank angle) and hip angles (about
1 degree degree¡1). Thus, the relatively small range of
body orientation used in this study should not be considered
as a limiting factor for detection of its eVect on technique
and energy consumption.
There are some limitations in the present study. The ped-
alling rates investigated (86–106 rpm) are a relatively small
range around the FCC for competitive cyclists that covers
most cadences used in mass starts competitive cycling.
However, the Wndings of this study cannot be generalised to
a wider range of cadences that is used regularly in experi-
mental studies and in other cycling disciplines. Further-
more, the ergometer used in present study may have
inXuenced the choice of cadence (Leirdal and Ettema 2009)
and might also aVect pedalling dynamics.
In conclusion, energy expenditure is strongly coupled to
cadence, but force eVectiveness, as a measure for pedalling
technique, is not likely the cause of this relationship. Along
with other studies (Kautz and Hull 1993; Ettema et al.
2009; Lorås et al. 2009), we are inclined to conclude that
FE is mostly aVected by inertial forces, and thus the value
of this parameter as a measure for technique should be
questioned. Contrary to Leirdal and Ettema (2010), we do
not Wnd a signiWcant relationship between DC and GE.
Thus, the present study provides no indication for the
notion that technique aVects energy consumption. There
was no signiWcant eVect of body orientation or seat position
on GE, FE or DC, or on the relationship between them,
indicating that these parameters and the relationship
between them are robust to coordinative challenges within
a range of cadence, body orientation and seat position that
is used in regular cycling.
Open Access This article is distributed under the terms of the Crea-
tive Commons Attribution Noncommercial License which permits any
noncommercial use, distribution, and reproduction in any medium,
provided the original author(s) and source are credited.
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