Pedal Cadence Research Articles

Effects of artificial gravity on the cardiovascular system: Computational approach

Artificial gravity has been suggested as a multisystem countermeasure against the negative effects of weightlessness. However, many questions regarding the appropriate configuration are still unanswered, including optimal g-level, angular velocity, gravity gradient, and exercise protocol. Mathematical models can provide unique insight into these questions, particularly when experimental data is very expensive or difficult to obtain. In this research effort, a cardiovascular lumped-parameter model is developed to simulate the short-term transient hemodynamic response to artificial gravity exposure combined with ergometer exercise, using a bicycle mounted on a short-radius centrifuge. The model is thoroughly described and preliminary simulations are conducted to show the model capabilities and potential applications. The model consists of 21 compartments (including systemic circulation, pulmonary circulation, and a cardiac model), and it also includes the rapid cardiovascular control systems (arterial baroreflex and cardiopulmonary reflex). In addition, the pressure gradient resulting from short-radius centrifugation is captured in the model using hydrostatic pressure sources located at each compartment. The model also includes the cardiovascular effects resulting from exercise such as the muscle pump effect. An initial set of artificial gravity simulations were implemented using the Massachusetts Institute of Technology (MIT) Compact-Radius Centrifuge (CRC) configuration. Three centripetal acceleration (artificial gravity) levels were chosen: 1g, 1.2g, and 1.4g, referenced to the subject's feet. Each simulation lasted 15.5 minutes and included a baseline period, the spin-up process, the ergometer exercise period (5 minutes of ergometer exercise at 30W with a simulated pedal cadence of 60RPM), and the spin-down process. Results showed that the cardiovascular model is able to predict the cardiovascular dynamics during gravity changes, as well as the expected steady-state cardiovascular behavior during sustained artificial gravity and exercise. Further validation of the model was performed using experimental data from the combined exercise and artificial gravity experiments conducted on the MIT CRC, and these results will be presented separately in future publications. This unique computational framework can be used to simulate a variety of centrifuge configuration and exercise intensities to improve understanding and inform decisions about future implementation of artificial gravity in space.

High intensity interval and moderate continuous cycle training in a physical education programme improves health-related fitness in young females.

The aim of the study was to investigate the effects of eight weeks of regular physical education classes supplemented with high intensity interval cycle exercise (HIIE) or continuous cycle exercises of moderate intensity (CME). Forty-eight collegiate females exercising in two regular physical education classes per week were randomly assigned to two programmes (HIIE; n = 24 or CME; n = 24) of additional (one session of 63 minutes per week) physical activity for 8 weeks. Participants performed HIIE comprising 2 series of 6x10 s sprinting with maximal pedalling cadence and active recovery pedalling with intensity 65%–75% HRmax or performed CME corresponding to 65%-75% HRmax. Before and after the 8-week programmes, anthropometric data and aero- and anaerobic capacity were measured. Two-way ANOVA revealed a significant time main effect for VO2max (p < 0.001), similar improvements being found in both groups (+12% in HIIE and +11% in CME), despite body mass not changing significantly (p = 0.59; +0.4% in HIIE and -0.1% in CME). A significant main time effect was found for relative fat mass (FM) and fat-free mass (FFM) (p < 0.001 and p < 0.001, respectively). A group x time interaction effect was found for relative FM and FFM (p = 0.018 and p = 0.018); a greater reduction in FM and greater increase in FFM were noted in the CME than the HIIE group. Improvements in anaerobic power were observed in both groups (p < 0.001), but it was greater in the HIIE group (interaction effect, p = 0.022). Weight loss is not mandatory for exercise-induced effects on improving aerobic and anaerobic capacity in collegiate females. Eight weeks of regular physical education classes supplemented with CME sessions are more effective in improving body composition than physical education classes supplemented with HIIE sessions. In contrast to earlier, smaller trials, similar improvements in aerobic capacity were observed following physical activity with additional HIIE or CME sessions.

Hypoxia attenuates cardiopulmonary reflex control of sympathetic nerve activity during mild dynamic leg exercise

What is the central question of this study? The cardiopulmonary baroreflex inhibits adjustment of sympathetic vasomotor outflow during mild-intensity dynamic exercise. However, it is unclear how suppression of sympathetic vasomotor outflow by the cardiopulmonary baroreflex is modulated by a powerful sympatho-excitatory drive from the exercise pressor reflex, central command and/or the arterial chemoreflex. What is the main finding and its importance? Hypoxia-induced heightened sympathetic nerve activity during dynamic exercise attenuated cardiopulmonary baroreflex control of sympathetic vasomotor outflow. This could facilitate the redistribution of blood flow to the active muscles by sympathetically mediated vasoconstriction of inactive muscles. Muscle sympathetic nerve activity (MSNA) does not increase during mild-intensity dynamic leg exercise in normoxic conditions, despite activation of central command and the exercise pressor reflex. Suppression of MSNA could be caused by muscle pump-induced loading of cardiopulmonary baroreceptors. In contrast, MSNA increases during mild dynamic leg exercise in hypoxic conditions. We hypothesized that hypoxic exercise, which induces a powerful sympatho-excitatory drive from the exercise pressor reflex, central command and/or arterial chemoreflex, attenuates cardiopulmonary reflex control of sympathetic vasomotor outflow. To test this hypothesis, MSNA was recorded during leg cycling in hypoxic conditions and with increased central blood volume by increasing the pedalling frequency to change the cardiopulmonary baroreflex. Subjects performed two leg cycle exercises at different pedal cadences of 60 and 80 r.p.m. (60EX and 80EX trials, respectively) in two (haemodynamic and MSNA) measurement conditions while breathing a hypoxic gas mixture (inspired oxygen fraction = 0.12). Thoracic impedance, stroke volume and cardiac output were measured non-invasively using impedance cardiography. During the MSNA test, MSNA was recorded via microneurography at the right median nerve at the elbow. Changes in thoracic impedance, stroke volume and cardiac output during the 80EX trial were greater than those during the 60EX trial. The MSNA burst frequency during hypoxic exercise in the 80EX trial (39 ± 4 bursts min(-1)) did not differ from that during the 60EX trial (39 ± 3 bursts min(-1)). These results suggest that the cardiopulmonary baroreflex of sympathetic vasomotor outflow during dynamic exercise is modulated by heightened hypoxia-induced sympathetic nerve activity.

Joint Torque Evaluation of Lower Limbs in Bicycle Pedaling

In this paper, joint torque powers of lower limbs in bicycle pedaling were investigated numerically. An approximation method of relationship between the angle of the ankle and normal force in the rotation direction of a bicycle crank while pedaling was investigatedTo calculate the joint torque power of lower limbs, a free body diagram of the motion of the lower limbs was formulated in the 2-dimensional plane. We assumed that the movements of the greater trochanters while pedaling were too small to consider. Also, bicycle shoes were supposed to be fixed to binding pedals. The free body diagram of one leg has two degrees of freedom, the crank angle and the ankle angle, when it is assumed that the greater trochanters are relatively motionless during bicycle pedaling. In previous research, the ankle angle during bicycle pedaling was obtained directly from image analysis using high-speed cameras each time the pedaling output or cadence changes. However, the relationship proposed here does not require image analysis software with high-speed cameras each time the pedaling output or cadence changes: All positions of the lower limb segments, the joint torques and the joint torque powers were calculated from the lower-limb model.The analytical system for bicycle pedaling comprised cleat-shape biaxial load cells and a program to evaluate pedaling effectiveness, joint torque and joint torque power. The plastic cleats between shoe-sole and binding pedal were replaced with biaxial load cells, which measured the biaxial-forces of right and left legs independently. Evaluations of the joint torques of the lower limbs were conducted with five male subjects to demonstrate the applicability of the proposed method.

A comparison of static and dynamic measures of lower limb joint angles in cycling: application to bicycle fitting

PurposeConfiguration of bicycle components to the cyclist (bicycle fitting) commonly uses static poses of the cyclist on the bicycle at the 6 o’clock crank position to represent dynamic cycling positions. However, the validity of this approach and the potential use of the different crank position (e.g. 3 o’clock) have not been fully explored. Therefore, this study compared lower limb joint angles of cyclists in static poses (3 and 6 o’clock) compared to dynamic cycling.MethodsUsing a digital camera, right sagittal plane images were taken of thirty cyclists seated on their own bicycles mounted on a stationary trainer with the crank at 3 o’clock and 6 o’clock positions. Video was then recorded during pedalling at a self-selected gear ratio and pedalling cadence. Sagittal plane hip, knee and ankle angles were digitised.ResultsDifferences between static and dynamic angles were large at the 6 o’clock crank position with greater mean hip angle (4.9 ± 3°), smaller knee angle (8.2 ± 5°) and smaller ankle angle (8.2 ± 5.3°) for static angles. Differences between static and dynamic angles (&lt; 1.4°) were trivial to small for the 3 o’clock crank position.ConclusionsTo perform bicycle fitting, joint angles should be measured dynamically or with the cyclist in a static pose at the 3 o’clock crank position.

Estimation of Handgrip Position Based on Force Measurement During Steady Pedaling

There have been many studies on pedaling skills (Bini et al., 2013) to improve cycling efficiency. Riding position of upper body as well as leg motion is very important for cycling because it has a substantial impact on air resistance and physical fatigue (Burke & Pruitt, 2003). Although camera-based motion capture systems are the most popular solution to measure riders’ position during cycling, they limit the range of motion and cannot be applied to actual outdoor cycling. In this study, we aim for developing a bike--mountable position estimation system. For this purpose, as a first step, we propose a method for estimation of handgrip position based on the force measurement during steady pedaling. Wattbike Trainer (Wattbike Ltd.) was used for our prototype system. A 6-- ‐ axis force/torque Sensor (BFS067XS102EU6S, Leptrino) was installed at an ahead- ‐ stem to measure the forces and torques loaded on the handlebar. According to the preliminary experiments, three parameters– 𝐹 ! , 𝐹 ! ,!–were chosen for the estimation. The proposed system classifies the observed data into three classes corresponding to the positions of handgrip, such as drops, hoods, and tops (Fig. 1) based on the SVM (Support Vector Machine) (Cortes & Vapnik, 1995), which is one of the most powerful machine learning techniques Experiments were conducted to verify the effectiveness of the proposed method. Four amateur male cyclists (mean 45.5 years old) participated in the experiments. The experiments consist of two phases, such as a learning phase and a test phase. To construct an SVM classifier, 60 seconds learning data for each handgrip position was collected at 100Hz for each participant in the learning phase. In the test phase, participants changed their handgrip positions every 30 seconds and steadily pedaled 6 minutes in total. Based on the individually learned SVM classifier, the system estimated the handgrip position at each sampling time. In both phases, the pedaling load and cadence were set according to each participant’s preference. Table 1 shows a confusion matrix of the experimental results. The proposed method achieves both high precision and recall. According to the experimental results, the proposed method can estimate the handgrip position with high reliability during steady pedaling. For future works, we will apply our system and estimation method to normal road bikes and develop a method to estimate positions of cyclists’ upper body.

Power-velocity curve: relevance of the SRM Ergometer for simulated cycling performance and constant duration tests

Introduction : When trying to obtain cycling performance capacity, a controlled laboratory setting is required to obtain valid and reliable results [1]. Ecological validity is important, as several studies found poor agreement between lab and field time trials [2,3]. To perform realistic time trials on an ergometer, it is important that the cyclist is able to 1) choose its own cadence, 2) that the ergometer accounts for changes in kinetic energy and 3) the ergometer accounts for the non-linear relation between air-frictional forces and velocity. The SRM Ergometer has a free mode with a gear box and a big flywheel, so requirements 1 and 2 are fulfilled. It is unknown if the brake algorithm of the ergometer is linear or non- linear and how this mimics real life cycling. The aim of the present study is therefore to determine the relationship between the mechanical power output and the velocity in the SRM ergometer compared to cycling on a velodrome. Methods : The relation between mechanical power output and velocity in incremental cycling on an SRM Ergometer (2Hz sampling rate) was determined with the ergometer set in the “Open End Test” mode, which allows the cyclist to freely choose his gear and self-select his pace. Power output and velocity were collected over 30 s intervals of steady state cycling per stage, resulting in the power-velocity curve. The SRM Ergometer was propelled using a dynamic calibration rig to simulate a pedalling cadence ranging from 60-160 rpm, with 10 rpm steps through gears 7- 12 of the Rohloff nave. The rig was attached to the crank of the SRM Ergometer via a counterbalanced double universal joint. The axle was centred at the bottom bracket of the SRM Ergometer and attached to the crank at the position of the left pedal. By upshifting gears and increasing cadence, a range of velocities and accompanying power outputs could be evaluated. The calibration rig was powered by a 3 Ph – AC electro motor with a maximum power output of 2.2 kW. Data of 2 elite track pursuit cyclists were obtained for comparison with the ergometer. Cyclist 1 rode in standard position and cyclist 2 in aerodynamic position on a 250 m indoor velodrome in Alkmaar, the Netherlands, with an air density of 1.19 and 1.20 kg.m3 respectively. The track bikes were equipped with a SRM 7 track system. Sample rate was set at 2 Hz. Two laps at six different velocities were cycled, starting at 30 km/h with an increase in velocity of 5 km/h to 55 km/h. For SRM ergometer cycling as well as for track cycling, trend lines were added based on least-squares fit, and coefficients of determination were obtained. The best fits were used to predict power output at fixed speeds between 25 and 60 km/h for the ergometer and track cyclists. From these data Pearson product-moment correlation coefficient and absolute and relative differences in power output between the ergometer and track cyclist were determined Purpose: The objective of this study was to determine if exercise mode played a part in the acute immune responses to exercise. Results : Power fit trend lines were found to resemble the best fit for the power-velocity curve for both the SRM Ergometer as well as in the real world situation (see Figure 1). This indicates that the SRM Ergometer uses a non- linear instead of a linear breaking algorithm, related to the velocity of the flywheel. The correlation for the predicted power output at fixed speeds was perfect (r=1.000) between the SRM ergometer and both cycling position on the track, with a standard error of the estimate of 1.64 and 2.96 respectively for standard and aero position. At high velocities, the SRM Ergometer required a similar power output as standard cycling but a higher power output than required in track cycling in aero position at the same velocity (see Table 1). Conclusion : The non-linear power-velocity curve of the SRM Ergometer that closely resembles the power-velocity curve of track cycling indicates that it mimics real life cycling behaviour and that it therefore could be used to simulate free ride efforts like time trials and constant duration tests to determine mean maximal power output. However, one must be cautious to use the velocity measured by the ergometer to predict field performance, as at the same power output the speed on the track is higher in aero position.

Limb movement frequency is a significant modulator of the ventilatory response during submaximal cycling exercise in humans

Human experimentation investigating the contribution of limb movement frequency in determining the fast exercise drive to breathe has produced controversial findings. To evaluate the role of limb movement frequency in determining the fast exercise drive to breathe, endurance runners and recreationally-active controls performed two sinusoidal exercise protocols on a cycle ergometer. One protocol was performed at constant workload with sinusoidal pedaling cadence, and a second with sinusoidal workload at constant cadence. Metabolic rate (VO2) increases and means were matched between these two experiments. The ventilatory response was significantly faster when limb movement speed was varied, compared to when pedal loading was varied (18.49±15.6s vs. 50.5±14.5s, p<0.05). Ventilation response amplitudes were significantly higher during pedal cadence variation versus pedal loading variation (3.99±0.25 vs. 2.58±0.17L/min, p<0.05). Similar findings were obtained for endurance athletes, with significantly attenuated ventilation responses to exercise versus control subjects. We conclude that fast changes in limb movement frequency are a potent stimulus for ventilation at submaximal workloads, and that this response is susceptible to attenuation through training.

Dynamic High-Cadence Cycling Improves Motor Symptoms in Parkinson's Disease.

Individuals with Parkinson's disease (PD) often have deficits in kinesthesia. There is a need for rehabilitation interventions that improve these kinesthetic deficits. Forced (tandem) cycling at a high cadence improves motor function. However, tandem cycling is difficult to implement in a rehabilitation setting. To construct an instrumented, motored cycle and to examine if high cadence dynamic cycling promotes improvements in motor function. This motored cycle had two different modes: dynamic and static cycling. In dynamic mode, the motor maintained 75-85 rpm. In static mode, the rider determined the pedaling cadence. UPDRS Motor III and Timed Up and Go (TUG) were used to assess changes in motor function after three cycling sessions. Individuals in the static group showed a lower cadence but a higher power, torque and heart rate than the dynamic group. UPDRS score showed a significant 13.9% improvement in the dynamic group and only a 0.9% improvement in the static group. There was also a 16.5% improvement in TUG time in the dynamic group but only an 8% improvement in the static group. These findings show that dynamic cycling can improve PD motor function and that activation of proprioceptors with a high cadence but variable pattern may be important for motor improvements in PD.

Effect of pedaling cadence on muscle oxygenation during high-intensity cycling until exhaustion: a comparison between untrained subjects and triathletes.

The aim of this study was to compare the muscle oxygenation between trained and untrained subjects during heavy exercise until exhaustion at two extreme pedaling cadences using a NIRS system. Nine untrained male subjects and nine male competitive triathletes cycled until exhaustion at an intensity corresponding to 90 % of the power output achieved at peak oxygen uptake at 40 and 100 rpm. Gas exchanges were measured breath-by-breath during each exercise. Muscle (de)oxygenation was monitored continuously by near-infrared spectroscopy on the Vastus Lateralis. Muscle deoxygenation (∆deoxy[Hb + Mb], i.e., O2 extraction) and ∆total[Hb + Mb] were significantly higher at 40 rpm compared to 100 rpm during the exercise in untrained subjects but not in triathletes (p < 0.05). The time performed until exhaustion was significantly higher at 40 than at 100 rpm in untrained subjects (373 ± 55 vs. 234 ± 37 s, respectively) but not in triathletes (339 ± 69 vs. 325 ± 66 s). These results indicate that high aerobic fitness (1) allows for better regulation between [Formula: see text]O2M and VO2M following the change in pedaling cadence, and (2) is the most important factor in the relationship between pedaling cadence and performance.

Lower Wingate Test Power Outcomes From "All-Out" Pretest Pedaling Cadence Compared With Moderate Cadence.

The aim of the present study was to determine the effect of different pretest pedaling cadences on power outcomes obtained during the Wingate Anaerobic Test (WAnT). Vigorously exercising adult men (n = 14, 24.9 ± 1.2 years) and women (n = 14, 20.4 ± 0.6 years) participated in a randomized crossover study during which they performed the 30-second WAnT on a mechanically braked cycle ergometer (0.075 kg·kg(-1) body weight) under 2 conditions. Participants pedaled maximally with an unloaded flywheel during 5 seconds before resistance was applied and the test began (FAST). In another trial, participants maintained a moderate cadence (80 revolutions per minute [rpm]) during 5 seconds before the test began (MOD). All other components of the WAnT were identical. Peak power (PP), mean power (MP), minimum power (MinP), fatigue index (%FAT), and maximum cadence during test were recorded. Comparisons were made using a 2 × 2 factorial repeated-measures analysis of variance. Regardless of gender, the FAST condition resulted in 22.2% lower PP (612.6 ± 33.0 W vs. 788.3 ± 43.5 W), 13.3% lower MP (448.4 ± 22.2 W vs. 517.2 ± 26.4 W), 11.7% lower MinP (280.9 ± 14.8 W vs. 318.3 ± 17.2 W), and 9.0% lower %FAT (53.5 ± 1.3% vs. 58.8 ± 1.5%) than MOD condition (p < 0.01; mean ± SD). Similar outcomes were observed within gender. The authors conclude that practitioners of the WAnT should instruct participants to maintain a moderate pedal cadence (∼80 rpm) during 5 seconds before the test commences to avoid bias from software sampling and peripheral fatigue. Standardizing the pretest pedal cadence will be important to exercise testing professionals who compare data with norms or generate norms for specific populations.

Effects of Workload on Frontal Plane Knee Biomecahnics during Cycling

Cycling is a recommended exercise for individuals with knee osteoarthritis (OA) because of its low impact loading to lower extremity joints. Effects of workload on sagittal plane knee biomechanics in cycling have been widely studied. However, few studies have examined impacts of workload on frontal plane biomechanics. PURPOSE: To investigate the effects of different workloads on frontal plane knee loading related biomechanical characteristics. METHODS: Eighteen healthy participants (mean±SD; age: 55.7±11.0 years, height: 1.80±0.10 m, weight: 78.8±6.3 kg) cycled on a stationary ergometer for two minutes at five different workloads (0.5, 1, 1.5, 2, and 2.5 kg) at 60 revolutions per minute (RPM). Three-dimensional kinematics (240 Hz) and pedal reaction force (PRF, 1200 Hz) using an instrumented pedal were collected for five pedal cycles. Selected knee kinetic variables were compared using a one-way repeated measures ANOVA (alpha=0.05). RESULTS: Peak medial PRF significantly increased between 0.5 (8.0 N) and 1 kg (20.4 N), 1.5 kg (27.6 N), 2 kg (34.8 N), and 2.5 kg (36.0 N), and between 1 and 1.5 kg and 2 kg (all comparisons, p < 0.05). Peak knee abduction moment significantly increased when workloads increased from 0.5 kg (-5.82 Nm) to 1 kg (-9.5 Nm), 1.5 kg (-10.18 Nm), 2 kg (-11.6 Nm), and 2.5 kg (-14.36 Nm) (all comparisons p < 0.05). Furthermore, peak knee extension moment increased significantly (p≤0.003) with increased workload between all pairs of workloads of 0.5 kg (11.6 Nm), 1 kg (20.2 Nm), 1.5 kg (26.0 Nm), 2 kg (34.2 Nm) and 2.5 kg (37.2 Nm) except for the difference between 2 and 2.5 kg. CONCLUSION: The results indicate that increased workload at a constant pedal cadence caused increased peak knee abduction moments as well as peak knee extension moments. During exercise or rehabilitation, a low cycling workload may be appropriate for individuals with medial knee OA in order to minimize loading to the knee joint. Future studies may be needed to establish appropriate levels of workload for knee OA and other knee pathological populations.

La poética del gran disparate y el ritmo pedal de Trilce

Este artículo muestra algunos apuntes acerca de la aventura poética de Trilce, desde el plano general de la concepción del trabajo artístico hasta el plano puntual de la elaboración versal, donde el ritmo de cadencia pedal actúa como eje que vertebra los sentidos y la sintaxis extraviada del discurso.

Influence of pedal cadence on the respiratory compensation point and its relation to critical power

It is not known if the respiratory compensation point (RCP) is a distinct work rate (Watts (W)) or metabolic rate (V˙O2) and if the RCP is mechanistically related to critical power (CP). To examine these relationships, 10 collegiate men athletes performed cycling incremental and constant-power tests at 60 and 100rpm to determine RCP and CP. RCP work rate was significantly (p≤0.05) lower for 100 than 60rpm (197±24W vs. 222±24W), while RCP V˙O2 was not significantly different (3.00±0.33lmin−1 vs. 3.12±0.41lmin−1). CP at 60rpm (214±51W; V˙O2: 3.01±0.69lmin−1) and 100rpm (196±46W; V˙O2: 2.95±0.54lmin−1) were not significantly different from RCP. However, RCP and CP were not significantly correlated. These findings demonstrate that RCP represents a distinct metabolic rate, which can be achieved at different power outputs, but that RCP and CP are not equivalent parameters and should not, therefore, be used synonymously.

Pedal force effectiveness in Cycling: a review of constraints and training effects

Pedal force effectiveness in cycling is usually measured by the ratio of force perpendicular to the crank (effective force) and total force applied to the pedal (resultant force). Most studies measuring pedal forces have been restricted to one leg but a few studies have reported bilateral asymmetry in pedal forces. Pedal force effectiveness is increased at higher power output and reduced at higher pedaling cadences. Changes in saddle position resulted in unclear effects in pedal force effectiveness, while lowering the upper body reduced pedal force effectiveness. Cycling experience and fatigue had unclear effects on pedal force effectiveness. Augmented feedback of pedal forces can improve pedal force effectiveness within a training session and after multiple sessions for cyclists and non-cyclists. No differences in pedal force effectiveness were evident between summarized and instantaneous feedback. Conversely, economy/efficiency seems to be reduced when cyclists are instructed to improve pedal force effectiveness during acute intervention studies involving one session. Decoupled crank systems effectively improved pedal force effectiveness with conflicting effects on economy/efficiency and performance.

New Zealand Sujon blackcurrant lowers lactate accumulation during cycling in triathletes

Background Blackcurrant intake has been reported to increase peripheral blood flow in humans (Matsumoto, et al., 2005), potentially by anthocyanin-induced vasorelaxation and vasodilation (Ziberna, et al., 2013). Increased peripheral blood flow may affect the exercise intensity at lactate indicators (e.g. onset of blood lactate accumulation (OBLA) at 4 mmol∙L-1) and maximum oxygen uptake. We examined the effect of 1-week Sujon blackcurrant powder supplementation on the blood lactate curve and aerobic capacity of trained triathletes. Methods Healthy male (n=8) and female (n=5) triathletes with >3 yrs experience (age: 38±8 yrs, height: 174±5 cm, body mass: 71±9 kg, BMI: 23±2, BF%: 19±5%, mean±SD) performed cycling tests for lactate responses (4 min stages with 2 min recovery, start power 50 W with 30 W increments) and maximum oxygen uptake (start power 50 W for 4 min with 30 W∙min-1 increments) at self-selected pedal cadence (SRM ergometer, SRM International, Germany). Familiarized participants were tested following 7 days of Sujon blackcurrant powder (S, 6g/day) or placebo (P) intake. Experimental design was double-blind and randomized with a wash-out period of 4 weeks. Oxygen consumption (Douglas bag technique) and heart rate were recorded during the cycling tests. Intensity, oxygen uptake and heart rate at 4 mmol∙L-1 OBLA were calculated using lactate analysis software (Newell et al., 2007). Lactate responses were calculated at relative intensities with individual lactate curves. Paired t-tests were used for analysis with significance accepted at p<.05. Results The intensity at 4 mmol∙L-1 OBLA was 6% higher with Sujon (P: 223±57, S: 236±60 W, range -5 to 22%, 11 participants showed an increase and 1 no change) (p<.01). In both conditions at 4 mmol∙L-1 OBLA, there were no differences in heart rate (P: 159±7, S: 164±10 b∙min-1, p=.13) or oxygen uptake (P: 2.91±0.73, S: 2.96±0.71 L∙min-1, p=.31). Blood lactate was lower at 40% (P: 1.24±0.52, S: 0.91±0.46 mmol∙L-1), 50% (P: 1.58±0.78, S: 1.23±0.64 mmol∙L-1), 60% (P: 2.29±0.96, S: 1.91±0.87 mmol∙L-1) and 70% (P: 3.52±1.10, S: 3.08±1.21 mmol∙L-1) of maximum power, decreases of 27%, 22%, 17% and 13%, respectively (all p<.01). There was no effect on maximum values of oxygen uptake (P: 49.1±6.2, S: 49.7±6.1 mL∙kg-1∙min-1, p=.16), power (P: 305±68, S: 307±62 W, p=.66) or heart rate (P: 172±10, S: 172±11 b∙min-1, p=.68). However, maximum oxygen uptake with Sujon was obtained with 14% lower lactate values (measured 3-min after exhaustion; P: 7.85±1.69, S: 6.79±1.51 mmol∙L-1, range -27 to 48%, 10 participants showed a decrease and 1 no change) (p=0.02). Conclusions Intake of New Zealand Sujon blackcurrant powder is associated with 1) a substantial downward and rightward shift of the lactate curve during cycling over a wide range of intensities, and 2) lower lactate accumulation at aerobic capacity suggesting increased lactate clearance or altered substrate oxidation. These findings may have implications for training practice and aerobic performance of endurance athletes. Acknowledgement Funding for this study and conference attendance was provided by the University of Chichester, Health Currancy Ltd (UK) and Gibb Holdings (Nelson) Ltd (NZ).

Effects of 6 weeks of aerobic exercise combined with conjugated linoleic acid on the physical working capacity at fatigue threshold.

The purpose of this study was to examine the effects of conjugated linoleic acid (CLA) supplementation in conjunction with 6 weeks of aerobic exercise training on the physical working capacity at the fatigue threshold (PWCFT), timed sit-ups, and the standing long jump. Thirty-three untrained to moderately trained men (mean ± SD; age = 21.6 ± 2.8 years) participated in this double-blind, placebo-controlled study and were randomly assigned to either a CLA (Clarinol A-80; n = 17) or placebo (PLA; sunflower oil; n = 16) group. Before and after 6 weeks of aerobic training (50% VO2peak for 30 minutes, twice per week) and supplementation (8 ml CLA or PLA per day), each subject completed an incremental cycle ergometer test to exhaustion to determine the PWCFT, maximal number of sit-ups in 1 minute, and the standing long jump. There were no differences (all p ≥ 0.23) between the CLA and PLA groups for the analysis of covariance-adjusted posttest mean values for PWCFT, sit-ups, or standing long jump. The PWCFT increased from pre- to posttraining in the CLA (p = 0.003) and PLA (p = 0.003) groups. There were no differences (p > 0.05) from pre- to posttraining for sit-ups and standing long jump in either the CLA or PLA groups. There was no effect of CLA on the training-induced increases in PWCFT, nor were there any effects of CLA or aerobic training on the maximum number of sit-ups or standing long jump. Thus, CLA had no ergogenic benefits on this model of aerobic training-induced improvements in neuromuscular fatigue, or on field tests of muscle endurance and power.

Gross efficiency is improved in standing position with an increase of the power output

Background: Gross efficiency (GE) has been shown to be one of the most relevant parameter influencing cycling performance but to the best of our knowledge, just one study focused on measuring GE in seated and standing positions during field conditions (Millet et al., 2002: Medicine & Science in Sports & Exercise, 34(10), 1645-52). Other authors investigated the effects of change in body position (seated vs. standing) on energy expenditure, heart rate (HR) or pulmonary ventilation (VE) but there were large changes in the results (Ryschon & Stray-Gundersen, 1991: Medicine & Science in Sports & Exercise, 23, 949-953; Swain & Wilcox, 1992: Medicine & Science in Sports & Exercise, 24, 1123-1127) due to the different protocols. Indeed, the cross effect of slope and intensity on GE in standing compared to seated position has not been studied. Thus, we found interesting to measure GE in real locomotion with elite cyclists at different intensities and slopes. Purpose: This study was designed to examine the effects of standing position on GE compared to seated position at different intensities and slopes. Methods: After a period of familiarisation, 13 elite participants performed on a motorised treadmill with their own bike one session during which they rode in a randomized order seated vs. standing positions with several slopes (5, 7.5 and 10%) and intensities (3.8, 4.2 and 4.6 W.kg-1). GE was calculated for each condition using the ratio of power output (PO) measured with a Powertap G3 hub (CycleOps, Madison, USA) and the oxygen uptake (VO2) measured with a portable gas analyzer (Metamax 3B, Cortex, Leipzig, Germany). Results: GE was significantly higher (+4.5%) in standing position (21.5 ± 5.2 %, CV = 5.2%) compared to seated position (20.6 ± 1.1 %, CV = 5.5%) for all the intensities and slopes. This improvement was due to a significant (p < 0.001) increase of PO in standing position (+4.5%) associated with a stabilization of VO2. The more the slope was low and the intensity was high, the more the pedaling cadence was high. That leads to higher PO changes between standing and seated positions (R = 0.93, p < 0.001) (Figure 1). Discussion: The main finding of this study shows that in standing position, GE was increased from a higher PO. The non-significant increase in VO2 is in accordance with the previous results of Millet et al. (2002). It's the first time that a study shows an increase in PO in standing position. The difference in PO is linked to an increase of the pedaling cadence. We hypothesize that the increase in PO is due to the technique adopted in standing position, the latter has an impact on the mechanical deformation both of the tires and the bike frame. The loss of energy in the bike and the tires would require to increase the PO in standing position according to the technique of each cyclist. Conclusion: Despite a significant decrease of GE, the standing position involves a significant increase in PO probably due to an increase of the deformation of both the tires and the bike frame according to the pedaling techniques of the cyclist.

Power output and affective load change during time trial according to environmental conditions

Introduction: During cycling events, riders have to face to different environmental conditions like wind or road gradient, which leads to variable resistive forces. Those resistances involve a specific pedaling cadence (PC) – crank inertial load (CIL) association and modify the level of power output (PO) (Hansen et al., 2002). The different environmental conditions also could influence the affective load (AL), defined like the difference between perception of exertion rate and pleasure (Baron et al., 2011). The purpose of this study was to analyze the influence of different environmental conditions on PO and AL. Method: Eight amateur competitive cyclists performed five 25 ± 5min TT sessions at their maximal capacity in different environmental conditions: 1) in level ground with 3 different wind conditions: no wind (NW), headwind (HW), tailwind (TW). The wind velocity was 40 ± 5 km/h, 2) in uphill (UP) with a mean slope of 8% and 3) on Home Trainer (HT). PO was recorded from a Power Tap® power meter. Every 4 minutes, riders had to rate their exercise perceived exertion from a CR10 Borg scale and their pleasure on a “pleasure scale” to evaluate their AL. An ANOVA statistical test was used to analyze the evolution of PO and AL over the time between the different conditions. Results: PO is significantly different between all conditions and varies over the time. Different pacing strategies are observed with a fast start and a final spurt. PO is higher in NW and TW (+ 3.5%) compared with HW and UP. There are correlations between PC and cycling speed (v) (r = 0.84, p<0.001) and between CIL and v (r = 0.92, p<0.001). AL increases over the time (p<0.05) for all the conditions and is significantly different between all conditions (p<0.05). AL is higher (+56%) in HW compared with the others conditions. Discussion / Conclusion: PO varies significantly according to wind and road gradient conditions. For each condition, riders select a specific PC – CIL combination which modifies PO and AL. The higher AL observed in HW was not associated with the higher PO. The changes in the PC – CIL combinations determined different whole body sensations that could play a role on AL. The changes in resistive forces involve different crank torque profiles which modify the force-length relationship, the muscular contraction velocity and muscular strains. So, to decrease AL it seems necessary to adopt an optimal gear according to the field and learn to tame the environmental conditions. This requires specific and regular training.

Stationary roller versus velodrome for maximal cycling test: a comparison

Brito, J., Lopes, L., Conceicao, A., Costa A.M. & Louro, H. (2014). Wheelchair Stationary roller versus velodrome for maximal cycling test: a comparison. J. Hum. Sport Exerc., 9(1), pp.7-16. The present study aimed to compare the acute cardio-respiratory responses of elite cyclists to a maximal progressive exercise carried out in two different conditions: in a laboratory (using a braked roller) and in an uncovered velodrome. In both testing conditions, ten elite male cyclists (age, 22.3 ± 3.9 years) performed a maximal discontinuous progressive test of 6 minutes per level with 150 W of initial load and increasing 50 W at each level until exhaustion. The heart rate and the ventilation parameters were measured breath-by-breath using a portable metabolic cart gas analysis system with telemetry data transmission. In the first 4 levels of effort, no significant differences were found between the two test conditions regarding VO2, (p=0.193), heart rate (p=0.973) and pedaling cadence (p=0.116). Comparing the maximum values achieved by each athlete in both exercise conditions, significant differences were found for heart rate (p=0.008) and pedaling cadence (p=0.005) but not for VO2max and peak power. Each variable showed a strong correlation between both assessments (VO2, r=0.984, p=0,000; heart rate, r=0.944, p=0.005; pedaling cadence, r=0.900, p=0.014). The amount of variability explained by the linear regression model for both cardio-respiratory parameters also showed a good fit value close to one (VO2max, r2=0.968; heart rate, r2=0.892). Our results suggest that identical cycling protocols conducted in different testing conditions with the same bike leads to