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Efficiency in cycling: A review
Abstract and Figures
We focus on the effect of cadence and work rate on energy expenditure and efficiency in cycling, and present arguments to support the contention that gross efficiency can be considered to be the most relevant expression of efficiency. A linear relationship between work rate and energy expenditure appears to be a rather consistent outcome among the various studies considered in this review, irrespective of subject performance level. This relationship is an example of the Fenn effect, described more than 80 years ago for muscle contraction. About 91% of all variance in energy expenditure can be explained by work rate, with only about 10% being explained by cadence. Gross efficiency is strongly dependent on work rate, mainly because of the diminishing effect of the (zero work-rate) base-line energy expenditure with increasing work rate. The finding that elite athletes have a higher gross efficiency than lower-level performers may largely be explained by this phenomenon. However, no firm conclusions can be drawn about the energetically optimal cadence for cycling because of the multiple factors associated with cadence that affect energy expenditure.
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... When measuring cycling efficiency, several methodologies have been used across the literature (16). The most common of these is 'gross efficiency', defined as the ratio of mechanical work performed relative to the total energy expended expressed as a percentage. ...
... While gross efficiency is deemed a suitable measure of whole-body efficiency (16), its incorporation of the basal metabolic rate required to maintain homeostasis means that gross efficiency underestimates muscular efficiency (17). Accordingly, several studies have measured delta efficiency, which purportedly removes the influence of energy expenditure required to maintain homeostasis through the expression of the change in energy expended relative to the change in work accomplished (18)(19)(20)(21). ...
... Accordingly, several studies have measured delta efficiency, which purportedly removes the influence of energy expenditure required to maintain homeostasis through the expression of the change in energy expended relative to the change in work accomplished (18)(19)(20)(21). While there have been criticisms concerning the validity of delta efficiency (16,22), it has been suggested that delta efficiency provides the most suitable estimate of muscular efficiency (18,20,23). Notwithstanding the potential limitations, no study has assessed the effect of EIMD on delta efficiency to our knowledge. ...
Introduction
The effect of eccentric exercise-induced muscle damage (EIMD) on cycling efficiency is unknown. The aim of the present study was to assess the effect of EIMD on gross and delta efficiency and the cardiopulmonary responses to cycle ergometry.
Methods
Twenty-one recreational athletes performed cycling at 70%, 90% and 110% of the gas exchange threshold (GET) under control conditions (Control) and 24 h following an eccentric damaging protocol (Damage). Knee extensor isometric maximal voluntary contraction (MVC), potentiated twitch (Qtw,pot) and voluntary activation (VA) were assessed before Control and Damage. Gross and delta efficiency were assessed using indirect calorimetry, and cardiopulmonary responses were measured at each power output. Electromyography root-mean-square (EMGRMS) during cycling was also determined.
Results
MVC was 25 ± 18% lower for Damage than Control (p < 0.001). Gross efficiency was lower for Damage than Control (p < 0.001) by 0.55 ± 0.79%, 0.59 ± 0.73% and 0.60 ± 0.87% for 70%, 90% and 110% GET, respectively. Delta efficiency was unchanged between conditions (p = 0.513). Concurrently, cycling EMGRMS was higher for Damage than Control (p = 0.004). An intensity-dependent increase in breath frequency and V̇E/V̇CO2 was found, which were higher for Damage only at 110% GET (p ≤ 0.019).
Conclusions
Thus, gross efficiency is reduced following EIMD. The concurrently higher EMGRMS suggests that increases in muscle activation in the presence of EIMD might have contributed to reduced gross efficiency. The lack of change in delta efficiency might relate to its poor reliability hindering the ability to detect change. The findings also show that EIMD-associated hyperventilation is dependent on exercise intensity, which might relate to increases in central command with EIMD.
... Stainsby et al. (1980) stated on the matter that ' Although exercise efficiencies using base line subtractions may be useful, they do not indicate muscle efficiency' . Both Cavanagh and Kram (1985), as well as Ettema and Lorås (2009) in their more recent review article on cycling efficiency, have echoed similar viewpoints. Barclay (2019) also expressed doubt in the validity of baseline subtractions for estimating muscle efficiency from whole-body exercise. ...
... Thus, not only do reported delta efficiency values often far exceed physiologically plausible estimates for muscle efficiency, but also the weight of the evidence would suggest that pulmonary delta efficiency and muscle delta efficiency do not actually agree very well with each other anyway, further questioning its use as a proxy for muscle efficiency. In light of these issues, in our review paper, we sided with Ettema and Lorås (2009) in their contention that, as a true, unbiased representation of the efficiency of the entire human body performing work, gross efficiency remains the most 'untroublesome' measure of efficiency during cycling exercise. We would argue that delta efficiency, on the other hand, is a misguided attempt to use whole body exercise to estimate muscle efficiency. ...
... The substantial and continuous losses in mechanical power could signify a decrease in workload due the loss of velocity, providing a significant limitation to performance due to the inability to utilize maximum metabolic potential. This theory is supported by data from Ettema et al., (2009) [58], who stated that power output is the main determinant of efficiency (more power leads to more efficiency and vice versa), owing to a greater utilization of metabolic power in running. The imbalance between mechanical power and metabolic power, resulting in a decrease in net mechanical efficiency, could be attributed to decreased energy transduction (due to decreased speed and stretch-shortening cycle) coupled with an increase in respiratory cost [24]. ...
... The substantial and continuous losses in mechanical power could signify a decrease in workload due the loss of velocity, providing a significant limitation to performance due to the inability to utilize maximum metabolic potential. This theory is supported by data from Ettema et al., (2009) [58], who stated that power output is the main determinant of efficiency (more power leads to more efficiency and vice versa), owing to a greater utilization of metabolic power in running. The imbalance between mechanical power and metabolic power, resulting in a decrease in net mechanical efficiency, could be attributed to decreased energy transduction (due to decreased speed and stretch-shortening cycle) coupled with an increase in respiratory cost [24]. ...
New and promising variables are being developed to analyze performance and fatigue in trail running, such as mechanical power, metabolic power, metabolic cost of transport and mechanical efficiency. The aim of this study was to analyze the behavior of these variables during a real vertical kilometer field test. Fifteen trained trail runners, eleven men (from 22 to 38 years old) and four women (from 19 to 35 years old) performed a vertical kilometer with a length of 4.64 km and 835 m positive slope. During the entire race, the runners were equipped with portable gas analyzers (Cosmed K5) to assess their cardiorespiratory and metabolic responses breath by breath. Significant differences were found between top-level runners versus low-level runners in the mean values of the variables of mechanical power, metabolic power and velocity. A repeated-measures ANOVA showed significant differences between the sections, the incline and the interactions between all the analyzed variables, in addition to differences depending on the level of the runner. The variable of mechanical power can be statistically significantly predicted from metabolic power and vertical net metabolic COT. An algebraic expression was obtained to calculate the value of metabolic power. Integrating the variables of mechanical power, vertical velocity and metabolic power into phone apps and smartwatches is a new opportunity to improve performance monitoring in trail running.
... Such approaches require sophisticated laboratory assessments of joint kinetics and/or kinematics based on ground reaction force and motion-capture data. Several methodological challenges also limit the utility of running mechanical PO to approximate the metabolic work rate [1,3], and, in contrast to cycling, where there is a strong relationship between mechanical and metabolic PO [4,5], many factors complicate the relationship between mechanical and metabolic PO when running [6][7][8]. Nevertheless, a wearable running device that can quantify and monitor training intensity, analogous to a cycling power meter [9,10], would be useful to guide training and maximize running performance. ...
... Our Stryd-derived measures of mechanical efficiency (~21-25%) are lower than previous estimates of "apparent" running mechanical efficiency during level running (e.g., 50-70%) [6,7,39] but are similar to estimates of gross cycling efficiency (e.g.,~20-25%) [4]. Furthermore, in comparison with the up to~20% difference in previously reported estimates of running efficiency measurements at various running speeds [6,7,39], the Stryd estimates of running mechanical efficiency for level running during MOD and heavy-intensity running were relatively small (i.e.,~4%). ...
We sought to determine the utility of Stryd, a commercially available inertial measurement unit, to quantify running intensity and aerobic fitness. Fifteen (eight male, seven female) runners (age = 30.2 [4.3] years; V·O2max = 54.5 [6.5] ml·kg−1·min−1) performed moderate- and heavy-intensity step transitions, an incremental exercise test, and constant-speed running trials to establish the maximal lactate steady state (MLSS). Stryd running power stability, sensitivity, and reliability were evaluated near the MLSS. Stryd running power was also compared to running speed, V·O2, and metabolic power measures to estimate running mechanical efficiency (EFF) and to determine the efficacy of using Stryd to delineate exercise intensities, quantify aerobic fitness, and estimate running economy (RE). Stryd running power was strongly associated with V·O2 (R2 = 0.84; p < 0.001) and running speed at the MLSS (R2 = 0.91; p < 0.001). Stryd running power measures were strongly correlated with RE at the MLSS when combined with metabolic data (R2 = 0.79; p < 0.001) but not in isolation from the metabolic data (R2 = 0.08; p = 0.313). Measures of running EFF near the MLSS were not different across intensities (~21%; p > 0.05). In conclusion, although Stryd could not quantify RE in isolation, it provided a stable, sensitive, and reliable metric that can estimate aerobic fitness, delineate exercise intensities, and approximate the metabolic requirements of running near the MLSS.
... relationship between the amount of energy consumed and the work produced. 22 But how these parameters could improve with SIT concerning to Mict has not been extensible reported previously. the time course of adaptations in endurance training is a variable with very little information in the literature. ...
... It is known that the efficiency changes when it is evaluated in different loads, and at higher loads are reported higher efficiency values. 22 An improvement in efficiency at higher loads can explain the increase in ppo, especially in Mict group, regardless the non-significative change in V o 2max , nevertheless the efficiency assessment in our work don't let us to make further assumptions on the change in this parameter. Our results show that both groups improve in at least one of the parameters that determine crF and endurance performance (maximal oxygen uptake, the position of the ventilatory threshold, and efficiency 3 ). ...
BACKGROUND: Endurance training has several health benefits, mainly mediated by the improving of cardiorespiratory fitness (CRF). It is known that sprint interval training (SIT) and moderate intensity continuous training (MICT) could improve similarly maximal oxygen uptake, a component of CRF. Nevertheless, little is known if SIT could modify other markers of CRF like ventilatory threshold and efficiency in comparison to MICT. Additionally, the evolution of markers related to the adaptations of both kinds of training has been less explored. Thus, this study aimed to examine and compare the training response and time-course adaptations of both training methodologies.
METHODS: Twenty sedentary volunteers were randomly allocated to 12 sessions of MICT or 12 sessions of low volume SIT. Maximal oxygen uptake, peak power output (PPO), first ventilatory threshold (VT1), and efficiency were assessed pre- and post-training. A training analysis along sessions was done to establish how was the evolution of adaptations to training.
RESULTS: In the pre-post comparison, the SIT group improved significantly maximal oxygen uptake, power at VT1, and PPO, whereas the moderate intensity continuous training group only significantly improved PPO at VT1. No differences were observed between groups in PPO and PPO at VT1, both at baseline and at follow-up. Training trend analysis shows a continuous improvement in both groups.
CONCLUSIONS: Low volume sprint interval training is a time-effective strategy to improve CRF parameters such as V̇O2max and VT1, in sedentary subjects compared to moderate intensity continuous training. Both training methodologies showed continuous and linear response after 12 sessions.
KEY WORDS: Exercise; Cardiorespiratory fitness; High Intensity Interval Training
... When work (or any other activity) is performed, the energy required is provided by different chemical reactions and adenosine triphosphate (ATP) hydrolysis for muscular contraction. This reaction allows the human body to release energy, but a percentage of this is transformed into work or activity, while another part (which depends on low human body efficiency) is transformed into heat [35]. Cycling has the main advantage that cycling activity power can be measured in a very specific way, for example, by following Hook's law, strain gauges are attached to areas where consistent deformation of the material is expected (for instance, the most used sensors are located on the pedals due to their low-cost solution) [36]. ...
Several determinants affect the reason to cycle or not, and some of them are described in a detailed way in the current technical literature review. The recent spread of new modes of active mobility brings up questions for urban transport planners on how to foresee future demand and assess safety conditions; from this comes the need to explore the relationships among several determinants. In this paper, after the collection of the main data required, three Regression Models are proposed, which demonstrate evidence for the role of safety and energy expenditure issues as important predictors. The method is applied to a dataset of 90 Italian cities selected according to their class of dimensionality and geographical position. The three models for each class of dimensionality (50,000-100,000 no. of inhabitants, 10,000-50,000 no. of inhabitants, and 0-10,000 no. of inhabitants) show a good accuracy (in terms of adj-R 2 values of 0.6991, 0.7111, and 0.6619, respectively). The results show that energy expenditure, which is related to the terrain characteristics of an urban area and individual aerobic abilities, and safety perception, which is related to cycle network extensions, appear to be significant determinants in predicting bicycle modal share. The aim is to provide a useful and simplified tool, when only aggregated-type data are available, to help urban road designers and city planners in identifying and forecasting bike-sharing.
... This observation demonstrates that a higher body mass is associated with a greater V'O 2 of unloaded cycling, as expressed by greater values of the intercept of V'O 2 (PO). Since the metabolic rate of unloaded cycling is the sum of the resting metabolic rate and the metabolic rate required for performing the 'internal work' (29), then the observed shift of the V'O 2 (PO) in the individuals with higher body mass (Fig. 2B) would be caused not only by an increased 'internal work', as postulated previously (23,24,27), but also by an increased resting metabolic rate, attributable to a greater body mass (30)(31)(32). The elevated V'O 2 of unloaded cycling would lead to a lower GE during cycling at a given PO. ...
Seventeen young healthy physically active males (age 23 ±3 years; body mass (BM) 72.5 ±7.9 kg; height 178 ±4 cm, (mean ±SD)), not specifically trained in cycling, participated in this study. The subjects performed two cycling incremental tests at the pedalling rate of 60 rev x min-1. The first test, with the power output (PO) increases of 30 W every 3 min, was to determine the maximal oxygen uptake (V'O2max) and the power output (PO) at V'O2max, while the second test (series of 6 minutes bouts of increasing intensity) was to determine energy expenditure (EE (V'O2)), gross efficiency (GE (V'O2/PO)) and delta efficiency (DE(ΔV'O2/DPO)) during sub-lactate threshold (LT) PO. V'O2max was 3.79 ±0.40 L x min-1 and the PO at V'O2max was 288 ±27 W. In order to calculate GE and DE the V'O2 was expressed in W, by standard calculations. GE measured at 30 W, 60 W, 90 W and 120 W was 11.6 ±1.4%, 17.0 ±1.4%, 19.6 ±1.2% and 21.4 ±1.1%, respectively. DE was 29.8 ±1.9%. The subjects' BM (range 59-87 kg) was positively correlated with V'O2 at rest (p<0.01) and with the intercept of the linear V'O2 vs. PO relationship (p<0.01), whereas no correlation was found between BM and the slope of V'O2 vs. PO. No correlation was found between BM and DE, whereas GE was negatively correlated with BM (p<0.01). GE was also negatively correlated with V'O2max and the PO at V'O2max (p<0.01). We conclude that: V'O2 at rest affects GE during moderate-intensity cycling and GE negatively corelates with V'O2max and the PO at V'O2max in young healthy men.
... Another plausible explanation for the increase in LBM is the passage of time (the pubertal period is characterized by dynamic tissue growth and maturation) [56], taking supplements promoting muscle hypertrophy [57], or an interaction effect of these factors [58]. Whatever the cause, the changes are adverse in the context of performance because each additional kilogram of BM produces metabolic heat [59] and requires the supply of energy substrates [60], which additionally burdens the body during long-lasting races. Following the 18-week PrPe period, anaerobic fitness deteriorated in the studied cyclists. ...
Background: Road cycling is one of the most extreme endurance sports. Professional road cyclists typically train ~20 hours per week and cover ~600 km a week. The longest 1-day race in men’s cycling can be up to 300 km while the longest multiple-stage races can last up to 21 days. Twenty to seventy accelerations are performed during a race, exceeding maximal aerobic power. Training is a crucial component of athletes’ preparation for competitions. Therefore, strong emphasis should be on recording the applied training loads and monitoring how they influence aerobic and anaerobic fitness, as well as performance. The aim of the study was to analyze the training loads in the preparatory period and their effects on aerobic and anaerobic fitness in adolescent road cyclists. Materials and Methods: The study involved 23 highly trained/national elite male road cyclists. Of them, 16 athletes (age: 16.21.1 years; training experience: 5.02.1 years) fully completed all components of the study. Aerobic fitness was measured using cardiopulmonary exercise testing (graded exercise test to exhaustion), while anaerobic fitness was evaluated using the 30-second modified Wingate anaerobic test. Each recorded training session time was distributed across training and activity forms as well as intensity zones. Results: The endurance training form used in the preparatory period was characterized by low-volume (~7.7h×wk-1), nonpolarised (median polarization index 0.15) pyramidal intensity distribution (zone1~68%; zone2~26%; zone3~1% total training volume). Endurance (specific and non-specific) and strength training forms accounted for ~95% and ~5% (respectively) of the total training time. Conclusion: Low-volume, non-polarised pyramidal intensity distribution training is probably not an effective stimulus for improving physical fitness in adolescent road cyclists. Disregarding high-intensity exercises in training programs for adolescent cyclists may result in stagnation or deterioration of physical fitness.
... Measuring work done has been criticised for its accuracy, and it is challenging to be used in different tasks. Ettema and Lorås [27] noted that efforts for the evaluation of the efficiency of whole-body muscles are unproductive. In the same context, Neptune et al. [28] revealed that considering the efficiency of muscles to represent motion efficiency is inappropriate. ...
Uncomfortable posture may not contribute only to the development of musculoskeletal disorders (MSDs) but also to the loss of energy and the decrease in work efficiency (WE). Measuring WE based on activity energy expenditure (AEE) have not got much attention in work places. The study aims to develop a model of work efficiency (WE) based on body posture for performing horizontal drilling tasks. Ten subjects, all men with an average age of 23.3 ± 0. 67, participated in the experiment. Six coordinated postures of shoulder and trunk flexion were tested. Activity Energy Expenditure (AEE) and Work Efficiency (WE) were the dependent variables. Repeated measures ANOVA were used to analyze the data. The findings showed that statistically significant trends (P <0.01) of increasing AEE while the trunk and shoulder move away from the neutral posture. Overall, these results provide valuable insights into assessing WE on the basis of the AEE and the activity wasted energy (AWE) due to unproductive movements while standing in difficult postures, taking the neutral posture as a zero reference of wasted energy.
Theoretical models of the effect of aerobic activity on concurrent
cognitive tasks predict both impairments and improvements
depending on the specific characteristics of the cognitive task. It
can be assumed that both aerobic and cognitive tasks share
neural resources of limited capacity (such as self-control) or that
they interact by confliction or facilitation of brain activation.
Detrimental effects are thus expected for cognitive tasks requiring
self-control or conflicting brain activation. Effects of cognitive
tasks on simultaneous aerobic activity have rarely been
investigated, but predictions can be made by adaptations of the
same theoretical models. The predicted effects should be
enhanced at higher intensities due to increasing drains of neural
resources and stronger brain activations. The current study aimed
to investigate the interaction of aerobic and cognitive tasks under
increasing and maximum physical load. Fifty participants (31 men,
19 women, mean age 22.8 ± 2.6 years) performed two maximum
performance cycling tests, one in combination with mental
rotation tasks (dual-task condition) and one without a cognitive
task (control condition). Cognitive (reaction time, accuracy) and
physical (power, cadence) performance, as well as objective (heart rate) and subjective (cognitive and physical ratings of perceived exertion) effort, were measured during the respective tests. The results showed increased cognitive effort during increased physical load and a focus on speed rather than accuracy, which can be interpreted in support of the models. Physical performance, however, could be upheld without increased physiological effort. The physical results contradict the suspected impairment predicted by the adaptations of the theoretical models.
LUCÍA, A., J. HOYOS, M. PÉREZ, A. SANTALLA, and J. L. CHICHARRO. Inverse relationship between V̇O2max and economy/efficiency in world-class cyclists. Med. Sci. Sports Exerc., Vol. 34, No. 12, pp. 2079–2084, 2002. Purpose: To determine the relationship that exists between V̇O2max and cycling economy/efficiency during intense, submaximal exercise in world-class road professional cyclists. Methods: Each of 11 male cyclists (26 ± 1 yr (mean ± SEM); V̇O2max: 72.0 ± 1.8 mL·kg−1·min−1) performed: 1) a ramp test for V̇O2max determination and 2) a constant-load test of 20-min duration at the power output eliciting 80% of subjects’ V̇O2max during the previous ramp test (mean power output of 385 ± 7 W). Cycling economy (CE) and gross mechanical efficiency (GE) were calculated during the constant-load tests. Results: CE and GE averaged 85.2 ± 2.3 W·L−1·min−1 and 24.5 ± 0.7%, respectively. An inverse, significant correlation was found between 1) V̇O2max (mL·kg−0.32·min−1) and both CE (r = −0.71;P = 0.01) and GE (−0.72;P = 0.01), and 2) V̇O2max (mL·kg−1·min−1) and both CE (r = −0.65;P = 0.03) and GE (−0.64;P = 0.03). Conclusions: A high CE/GE seems to compensate for a relatively low V̇O2max in professional cyclists.
The purpose of this study was to investigate the interactions between cadence and power output effects on cycling efficiency. Fourteen healthy subjects performed four constant power output-tests (40, 80, 120 and 160 W) in which the cadence varied in five bouts from 40 to 120 rpm. Gross efficiency (GE) was determined over the last ten respiratory cycles of each bout and was calculated as the ratio of mechanical energy to energy expenditure. Results showed that (1) GE-cadence relationships reached a maximum at each power output corresponding to the cadence maximising efficiency (CAeff) and (2) GE increased with power output whatever the cadence until a maximal theoretical value. Moreover, interactions were found between these two factors: the cadence effect decreased linearly with power output and the power output effect increased exponentially with cadence. Consequently, cycling efficiency decreased more when cadence differed from CAeff at low than at high power output, and increased more with power output at high cadence than at low cadence. These interactions between cadence and power output effects on GE were mainly due to cadence and power output effects on the energy expenditure shares not contributing to power production.
Changes in pedaling rate during cycling have been found to alter the pedal forces. Especially, the force effectiveness is reduced when pedaling rate is elevated. However, previous findings related to the muscular force component indicate strong preferences for certain force directions. Furthermore, inertial forces (due to limb inertia) generated at the pedal increase with elevated pedaling rate. It is not known how pedaling rate alters the inertia component and subsequently force effectiveness. With this in mind, we studied the effect of pedal rate on the direction of the muscle component, quantified with force effectiveness. Cycle kinetics were recorded for ten male competitive cyclists at five cadences (60-100 rpm) during unloaded cycling (to measure inertia) and at a submaximal load (~260 W). The force effectiveness decreased as a response to increased pedaling rate, but subtracting inertia eliminated this effect. This indicates consistent direction of the muscle component of the foot force.
The definition of efficiency of human movement has often been unable to cope with activities such as level gait because the numerator of the efficiency equation includes only external work done by the body on an external load. The major purpose of this paper is to propose a definition that not only accounts for any external work but also the internal work done by the limbs themselves. The internal work involves a new biomechanical analysis that takes into account all potential and kinetic energy components, all exchanges of energy within and between segments, and both positive and negative work done by the muscles. This analysis was applied to a study of over-ground level gait on eight subjects walking at different walking speeds. The internal work/stride as calculated from the sum of segment energies was compared with the same calculation on the body's center of mass energy. The latter was found to be in error (low) by 16.2% and could be low by as much as 40%. The average internal work per body mass per distance walked was 1.09 J/kg.m.
After review of previous studies, it seemed desirable to investigate further the interrelationships between pedalling rate, power output, and energy expenditure, using bicycle ergometry as a model for recreational bicycling. Three young adult male subjects rode a Monark ergometer at eight pedalling rates (30-120 rev min ) and four power outputs (‘ 0 ’ 81-7. 163-4. and 1961 W) [vdot] o2 determinations were made, and using measured R, gross energy expenditure was derived. When these values were combined with the results of other researchers using similar protocol but different power outputs, it was found that: (I) a ‘ most efficient’ pedalling rate exists for each power output studied: (2) the ( most efficient ) pedalling rate increases with power output from 42 rev min at 40-8 W to 62 rev min at 326-8 W: and (3) the increase in energy expenditure observed when pedalling slower than‘ most efficient’ is more pronounced at high power outputs than at low outputs, while the increase in response to pedalling faster than “lsquo; most efficient’ is less pronounced at high power outputs than at low outputs. Thus, there is appreciable interaction between pedalling rate and power output in achieving the ‘ most efficient ’ rate in bicycle ergometry. The ‘ most efficient’ pedalling rate observed at high power outputs in the present study is considerably lower than that reported for racing cyclists by others. This discrepancy may well be related to the difference in swing weights between the ergomeler' s heavy steel flywheel and crankset, and that of the lightweight wheel and crankset used on racing bicycles.