Journal of Science and Cycling

The test-retest reliability of a 16.1 km time trial in trained cyclists using the Wattbike Pro ergometer in hot environmental conditions

2024-04-24T17:19:10+02:00

The Wattbike Pro ergometer (Wattbike) is readily available and widely used by athletes, coaches, and researchers as a tool for cycling performance assessment. To-date, no literature has reported the test-reliability of relevant performance criterion using the Wattbike and a 10-mile (16.1 km) TT - which is the most prevalent race distance, often completed in the summer race season. Therefore, the aim of this study was to assess the reliability of 16.1 km TT performance in the heat using the Wattbike Pro ergometer. A cohort of trained cyclists volunteered to take part in this study (n = 16, mean ± SD age 36.4 ± 14.0 y, height, 1.77 ± 0.09 m, body mass 75.2 ± 7.3 kg, PPO 365.1 ± 55.2 W, V̇O_2max 55.0 ± 9.5 mL.kg^-1.min^-1. Participants performed a familiarisation, prior to two 16.1 km TT on the Wattbike Pro ergometer separated by 3-7 days. Differences in mean completion time, power output, and speed were determined using paired samples T-tests, with quartile data assessed using repeated-measures ANOVA. Reproducibility of the performance measures was performed using the coefficient of variation (CV), intraclass correlations, technical error (rTE and sTE) and, Cronbach’s α. There were no significant differences between TT1 and TT2 for time, power output and speed (mean difference = 3.25 s, 3.2 W, and 0.15 km·h^-1, respectively). All performance data demonstrated excellent reproducibility (CV range = 0.8 – 1.9%) with trivial sTE (0.16 – 0.20). The 16.1 km cycling TT when conducted on a Wattbike Pro ergometer demonstrates a very reliable performance criteria in cohorts of trained cyclists, when exercising in hot conditions. Athletes, coaches, and researchers alike, should be aware of the interbike reliability which has been previously reported, and ensure that the same ergometer is used when measuring performance, thereby ensuring the reliability of the 16.1 km TT.

Influence of Cadence and Road Gradient on Metabolic and Biomechanical Parameters during Submaximal Cycling: a Pilot 2×2 Factorial Study

2024-04-24T10:55:32+02:00

Introduction

In cycling, a single power output can be achieved at various combinations of cadence and force; nevertheless, consensus is lacking regarding criteria for selecting the optimal cadence. Several studies reported differences in metabolic (oxygen uptake, lactate, ventilation) and neuromuscular parameters at different pedaling rates (Ahlquist et al., 1992; Lucia et al., 2001). More recently, it has also been observed that the work rates at which respiratory compensation point (RCP) and critical power (CP) occur were influenced by pedaling cadence (Broxterman et al., 2015). Furthermore, other studies indicated that joint contributions are affected by cadence, suggesting that differences in biomechanical parameters could also play a role (Skovereng et al., 2016).

Another factor that affects cadence is road gradient. However, research on how road gradient influences metabolic and biomechanical responses is limited, partly due to the difficulty of obtaining data, both in laboratory and outdoor conditions. To our knowledge, the only study that combined in a comparable way cadence and gradient was that conducted by Bertucci and colleagues (2005), which conducted two tests on level ground (flat road) at 80 and 100 rpm, and two tests on a 9.25% uphill (outdoor), at 60 and 80 rpm. The outcome variable was the crank-torque profile, and the main finding was that the crank-torque profile varied substantially according to cadence and in minor part due to the gradient.

This pilot 2×2 factorial study explored the effects of pedaling cadence and road gradient on cyclists' cardiorespiratory and biomechanical parameters during submaximal cycling. We expected to confirm the literature regarding the metabolic and biomechanical differences between (a) low and high cadences, and (b) flat and uphill positions, and we also hypothesized that the road gradient would enhance the cadence-related differences.

Materials and Methods

Subjects — Four male trained/highly trained cyclists (32.8 ± 4.3 years old) participated in the study.

Design — A factorial 2 × 2 design (two cadences × two gradients) was used. Participants visited the laboratory on two occasions: the first time, a ramp incremental exercise test was performed to determine power at first (W_GET) and second thresholds (W_RCP), while on the second visit, participants underwent the experimental protocol, which consisted in 4 × 5-min bouts at 100% W_RCP, with 10-min active recovery (90% W_GET) in between, one trial for each of the four conditions: flat low cadence (0%, 55-60 rpm), flat high cadence (0%, 90-95 rpm), uphill low cadence (6.5%, 55-60 rpm), uphill high cadence (6.5%, 90-95 rpm).

Methodology — Power, torque, cadence, heart rate, ventilatory (oxygen uptake, ventilation), and biomechanical (kinematics) variables were continuously recorded during the experimental sessions. Power and torque data were recorded second-by-second using SRM pedals (SRM Italia Srl, Italy) to use the same power meter for all participants. The participants’ bike was mounted on a Wahoo Kickr ergometer, connected to the Zwift software (Zwift Inc., US), which regulated the ergometer resistance through the ERG mode; the road gradient was adjusted using a Wahoo Kickr-Climb (Wahoo Fitness, US).

Statistical Analysis — For exploratory purposes, a linear mixed model analysis was conducted to compare conditions (high vs low cadence; flat vs uphill), in which model gradient and cadence were used as fixed effects, while ID as a random effect to account for the repeated measures of the data. The analyses were conducted using Phyton and RStudio, at a standard significance level of alpha = 0.05.

Results

Significant differences were found between high and low cadence (fixed-effect cadence) for torque (p<0.001), VO_2peak (p=0.002), and VE (p=0.008) (Figure 1). No significant differences were reported between flat and uphill conditions. The analysis of the crack-torque profile showed that the angle at which peak torque (T_peak) is expressed varies between conditions (Figure 2). A significant effect on the angle at T_peak was reported both for gradient (p=0.022) and cadence (p<0.001).

Discussion

To our knowledge, this is the first study that investigated the interaction between cadence and gradient, under controlled laboratory conditions, and that integrated both metabolic and biomechanical measurements. The main findings of our research only partially confirm the original hypothesis: indeed, if our results confirmed an effect of pedal cadence on cardiorespiratory and metabolic responses, we failed to find any difference enhancement related to the road gradient. We found that metabolic responses (VO₂ and VE) were higher in the high cadence condition, independently of road gradient, in accordance with previous studies (Boone et al., 2015; Broxterman et al., 2015). Moreover, we reported that both cadence and road gradient were associated with a different angle at T_peak in the crank-torque profile. These results are in accordance with Bertucci et al. (2005), which suggested that, as in each condition the muscles operate across different portions of their active force–length relationship and at different contraction velocities, in order to optimize cycling performance should be important to train in specific conditions (uphill road cycling and level ground, low and high cadences) for stimulating specific muscular adaptations. This can be highlighted as an important limiting point of the literature about low cadence / high torque training in cycling.

Practical Applications

Although the VO₂ associated with RCP does not appear to be different between low and high cadences, the work rate associated with this (and other) intensity boundary differs, and this posits a question of whether training zones, commonly used to prescribe training programs, should be adapted or not to different cadences. For example, when performing low cadence / high torque intervals, if the power output associated with a given intensity (for example, CP) is greater when riding at low cadence, should the power target be set higher accordingly? Future studies are needed to better understand the determinants of optimal cadence during cycling and optimize training programs using the combination of different gradients and cadences to stimulate specific muscular adaptations.

A test design for measuring power uptake of bicycle bottom bracket bearing assemblies

2024-04-22T19:40:30+02:00

The scope of this study was to develop a test design to quantify the power uptake of bicycle bottom bracket bearings. For this, a caloric, contactless measurement laboratory design was set up with the potential extend to field application. The goal was to determine differences in resistance of 30 given bearing assemblies. The assemblies have been systematically modified in order to impact the power uptake during cycling relevant revolutions. Also 3 standard bearing assemblies have been tested for reference. In this test design, each sample was mounted into a vice, comprising a bottom bracket shell, a spindle, corresponding with the bearing dimension and two disks mounted on each side of the spindle’s endings. For each run of the tests, the two discs and the spindle were set into rotation, exceeding 200 rpm and then let itself slowdown until a complete stop. During each of the runs, the angular velocity of the rotating disks was measured. The inertia of the rotating parts at a certain angular velocity represents the rotational energy in the system, hence its decrease over time the power uptake by the bearings. The tests revealed statistically significant differences in resistance amongst the 33 samples of up to 769%. A re-test was done in order to validate the designs reliability which revealed a high level of repeatability and reproducibility.

Training volume and altitude training are associated with power output and race results; a longitudinal case study of an elite female cyclist

2024-04-22T14:19:46+02:00

Since the introduction of the UCI Ladies World Tour in 2016, the popularity of female competitive cycling has grown exceptionally. While training characteristics that correlate with power-output and racing results have been fairly well established in male elite cyclists, only little research has investigated these characteristics in female cyclists. However, the distinct nature of racing, with higher intensities and shorter distance covered in females compared to males, the physiological sex differences and the brief history of female cycling urge for sex specific examination of determinants of bike racing performance. Further, previous research investigated professional but not world-class level female cyclists. Thus, the aim of this study was to identify training characteristics that are related to power output and race results in a world-class female cyclist. Moreover, this analysis permitted the identification of key characteristics including length, duration and power outputs of classical races and grand tours where this cyclist excelled.

Training and racing data were retrieved from a recently retired world-class female cyclist. The participant was born in 1982 and was highly successful from 2012 to 2023 in female professional cycling, obtaining 37 one day victories and 15 stage races at the highest level in cycling. Training characteristics such as the training volume and days spent at altitude were correlated with 5-second, 1- 5- 20-minute power output and critical power as assessed during training and races. In the second part, a detailed overview was given of power output in classic races and grand tour races to investigate what power output was needed to excel in these races.

Mean training volume was 902 ± 302 hours per year (range 420-1296 hours, cycling-only). Both training volume and time spent at altitude were significantly correlated with a composite performance measure (ProCyclingStats (PCS) points scored) (r = .878, p < .001 and r = .913, p < .001 respectively).

Additionally, training volume and time spent at altitude correlated significantly with stage race wins (r = .806, p = .005 and r = .825, p = .003 respectively). Further, fatigue resistance as determined by the critical power after 2000 kJ of work had been performed, correlated strongly with PCS points achieved and stage race wins (r = .824, p = .003 and r = .862, p = .001). Lastly, repeated power outputs of 5.9 ± 0.2 W*kg-1 for 4 ± 2 minutes and 5.5 ± 0.6 W*kg-1 for 22 ± 16 minutes on decisive climbs were needed to excel in female classic races and grand tours respectively.

Retrospective analysis of training and race data of multiple successive years in a multiple world champion female cyclist revealed that training volume and altitude training were positively correlated with power output and race results. Furthermore, a higher fatigue resistance was correlated with race results. In conclusion, high training volumes and altitude training appear to be pivotal training components to excel in professional female cycling.

Cycling Power Characteristics between Instrumented and Power Meter Pedals

2024-04-16T02:03:03+02:00

The purpose of this study was to evaluate the differences in crank power measured by instrumented pedals and a pedal-based power meter during stationary cycling at multiple workloads. Nine healthy participants performed 2-minute trials at 1kg, 2kg, and 3kg workload conditions at 80 revolutions per minute on a cycle ergometer, with a commercial set of power pedals and customized instrumented pedals. A 3x2 (Condition x Pedal Type) ANOVA was used to determine differences in total, right, and left crank power. No significant interaction or main effect for pedal type was found, but a significant workload effect was present for all variables. The percentage differences in measurement between the two pedals were approximately 3.6%, 1.3%, and 1.2% for average total power of 1kg, 2kg, and 3kg, respectively. This study provides evidence that the crank power measured by Favero power meter adequately matched the total crank power and individual limb crank power obtained by gold-standard instrumented pedals during stationary cycling. These results indicate that the commercial power pedals can adequately match gold standard instrumented pedals in measuring bilateral crank power in short sessions of low to moderate intensity stationary cycling. The power meter may be suitable to measure crank power output for endurance or clinical applications, but further research is needed to investigate these use cases.

A test design for measuring power uptake of bicycle bottom bracket bearing assemblies

2024-04-16T10:57:58+02:00

The scope of this study was to develop a test design to quantify the power uptake of

bicycle bottom bracket bearings. For this, a caloric, contactless measurement laboratory design

was set up with the potential extend to field application. The goal was to determine differences

in resistance of 30 given bearing assemblies. The assemblies have been systematically modified

in order to impact the power uptake during cycling relevant revolutions. Also 3 standard

bearing assemblies have been tested for reference. In this test design, each sample was

mounted into a vice, comprising a bottom bracket shell, a spindle, corresponding with the

bearing dimension and two disks mounted on each side of the spindle’s endings. For each run

of the tests, the two discs and the spindle were set into rotation, exceeding 200 rpm and then

let itself slowdown until a complete stop. During each of the runs, the angular velocity of the

rotating disks was measured. The inertia of the rotating parts at a certain angular velocity

represents the rotational energy in the system, hence its decrease over time the power uptake

by the bearings. The tests revealed statistically significant differences in resistance amongst the

33 samples of up to 769%. A re-test was done in order to validate the designs reliability which

revealed a high level of repeatability and reproducibility.

The The effect of low-intensity exercise dura6on on acute skeletal muscle signalling responses.

2024-04-16T11:00:46+02:00

Attached as PDF document.

Understanding optimal cadence dynamics: a systematic analysis of the power-velocity relationship in track cyclists with increasing exercise intensity

2024-04-09T17:07:34+02:00

Background: This study aimed to investigate the changes in force-velocity (F/v) and power-velocity (P/v) relationships with increasing work rate up to maximal oxygen uptake and to assess the resulting alterations in optimal cadence, particularly at characteristic metabolic states.

Methods: Fourteen professional track cyclists (9 sprinters, 5 endurance athletes) performed submaximal incremental tests, high-intensity cycling trials, and maximal sprints at varied cadences (60, 90, 120 rpm) on an SRM bicycle ergometer. Linear and non-linear regression analyses were used to assess the relationship between heart rate, oxygen uptake (V̇O₂), blood lactate concentration and power output at each pedaling rate. Work rates linked to various cardiopulmonary and metabolic states, including lactate threshold (LT1), maximal fat combustion (FAT_max), maximal lactate steady-state (MLSS) and maximal oxygen uptake (V̇ O_2max), were determined using cadence-specific inverse functions. These data were used to calculate state-specific forcevelocity (F/v) and power-velocity (P/v) profiles, from which state-specific optimal cadences were derived. Additionally, fatigue-free profiles were generated from sprint data to illustrate the entire F/v and P/v continuum.

Results: HR, V̇O₂ demonstrated linear relationships, while BLC exhibited an exponential relationship with work rate, influenced by cadence (p < 0.05, η2 ≥ 0.655). Optimal cadence increased sigmoidally across all parameters, ranging from 66.18 ± 3.00 rpm at LT1, 76.01 ± 3.36 rpm at FAT_max, 82.24 ± 2.59 rpm at MLSS, culminating at 84.49 ± 2.66 rpm at V̇O_2max (p < 0.01, η2 = 0.936). A fatigue-free optimal cadence of 135 ± 11 rpm was identified. Sprinters and endurance athletes showed no differences in optima cadences, except for the fatigue-free optimum (p < 0.001, d = 2.215).

Conclusion: Optimal cadence increases sigmoidally with exercise intensity up to maximal aerobic power, irrespective of the athlete’s physical condition or discipline. Threshold-specific changes in optimal cadence suggest a shift in muscle fiber type recruitment toward faster types beyond these thresholds. Moreover, the result indicate the need to integrate movement velocity into Henneman’s hierarchical size principle and the critical power curve. Consequently, intensity zones should be presented as a function of movement velocity rather than in absolute terms.

Sensitivity analysis of bicycle characteristics for pavement roughness monitoring by vibration data

2024-04-04T22:21:28+02:00

Promoting cycling, both as a mode of transport and as an integrating element of other forms of urban mobility, is a key part of making cities sustainable. Vibration caused by lack of pavement maintenance affects the comfort, health and safety of cyclists and has been identified as one of the main infrastructural barriers to cycling. The focus of this paper is to investigate how the physical characteristics of bicycles affect the vibration response under different pavement conditions, and to explore the potential of crowdsourced collection with sensor-equipped bicycles to collect data for road condition and comfort assessment of micro-mobility users.

The organization of the paper follows the research development based on 3 main tasks:

1) Experimental data collection of vibration and pavement characteristics

2) Numerical modeling and genetic algorithm to identify the mechanical configuration of the test bicycle to match the experimental data.

3) Sensitivity analysis to study how the variability in bicycle characteristics contributes to the overall uncertainty in multiple measurements.

An experiment was conducted in which an equipped bicycle was used to collect vertical accelerations at different speeds, and an advanced laser profiler and laser crack measurement system (LCMS) was used to model the pavement surface in the travel path. Vertical acceleration data with GNSS coordinates, along with pavement longitudinal profiles and distresses, were collected with several runs at different speeds on selected test roads.

Various pre-processing steps were then applied to synchronize the data collected by smartphone and mobile laboratory. The vertical accelerations recorded in the field were filtered and synchronized to ensure comparability with the simulation carried out on the actual profile of the pavement roughness. The road profile was used as input to simulate the vehicle dynamics with a half car model in MATLAB Simulink. Given a road profile and running speed, in the half-car model, the acceleration signal is affected by the 6 bicycle dynamic parameters related to stiffness and damping factors (kt1-2, k1-2 and c1-2). Different settings of the bicycle parameters change the goodness of fitting between measured and simulated RMSs. Due to the complexity of the system and the number of variables, we implemented a genetic algorithm (GA) to identify the model parameters that minimize the difference between simulated and measured RMS.

Therefore, the mathematical formulation based on the half-car relaxation model was integrated in a genetic algorithm optimization process to identify the bike parameters which minimize the error between the simulated and in-field Root Mean Square (RMS) of vertical accelerations. The optimization aimed to ensure the model parameters’ best consistency with the real dynamic response of bicycle to road profiles. Finally, the sensitivity analysis was carried out by varying the bicycle characteristics in the range of values that can be expected in real world data collection from several bicycle types.

The sensitivity analysis was performed to investigate how the variability from the best fitting bicycle parameters contributes to the overall uncertainty in the vibration response over repeated measurements. For the proposed sensor configuration and speed range, the sensitivity analysis showed the relative relevance of the bicycle characteristics when compared to the overall accuracy of the results effected by the position of the bicycle path over the variability of the road surface.

As further practical information, the results confirmed the opportunity to apply different data analyses for the detection of pavement anomalies such as potholes, bumps and high severity linear cracks based on the RMS of the peaks. The average RMS data, cleansed of outliers, can be used to assess rider comfort as well as different types of pavement distress such as alligator cracking, moderate linear cracking and bumps.

Application of an innovative W' model in practice: optimizing the pacing strategy in elite track cycling

2024-04-04T22:20:11+02:00

Since more than 50 years, the 'Critical Power' model provides a robust mathematical and physiological framework to study human exercise capacity and fatigue development. This concept is built upon Critical power (CP), an estimate of the maximal metabolic steady-state intensity, and W', a finite anaerobic work capacity above CP. Only recently, it has been applied to intermittent exercise, in which high-intensity exercise (i.e., above CP) is alternated with low-intensity intervals (i.e., below CP). In essence, the application of the CP model to intermittent exercise allows for the prediction of an individual's acute energy balance at any time during exercise. For a broad spectrum of people within sports and clinical practice, the practical relevance of having access to this information is great (e.g., to make strategic decisions or improve pacing strategies during races, or to individualize training sessions). Although these field applications are very promising, the predictive capabilities of current models are limited as they do not account well for the specific modalities of different exercise protocols, are not tailored to the individual, and lack fundamental knowledge about the underlying physiological processes. Recently, we developed a new evidence-based model that enables real-time monitoring of W' during exercise. During this presentation, we will go deeper into the scientific background of the model, and we will illustrate its practical use in elite track cycling.

Comparative Analysis of Effort Tolerance between National Level and Professional Road Cyclists: A Psychological Approach

2024-04-16T10:55:26+02:00

Cycling, as a sport, demands not only physical prowess but also a profound understanding of the psychological factors that influence performance (Ouvrard et al., 2019). Among these factors, effort tolerance and pain management stand out as a crucial determinant of success in competitive cycling. The aim of the present study seeks to elucidate the disparities in effort tolerance between national level and professional road cyclists. By examining various psychological variables such as perceived exertion, pain perception, pleasure, motivational factors, and electroencephalography responses, we aim to uncover the nuanced differences that underpin the performance disparities observed in these two cohorts.

Eleven amateur and 11 professional cyclists participated in a maximal graded test until exhaustion and a 'Finish Race Test'. This test was designed to simulate the final portion of a cycling race, aiming to evaluate both psychological and physiological responses to high-intensity effort.

The ANOVA test revelated a significance group effect for relative MAP but not for maximal oxygen uptake.

During the test, the relative body mass PO (W.kg^-1) was significantly higher for the PRO nevertheless the relative effort (%MAP) was not different between the both groups. PRO revealed a higher mean RPE in comparison to AM group but also for the quads pain and the pleasure was significantly lower for the PRO than AM. Higher neural efficiency was found for the PRO compared to AM.

Compared to amateurs, pros tolerate higher levels of effort and pain with a lower neural efficiency.

Adductors Role in the Pedaling Motion

2024-03-29T17:06:42+01:00

The cycling community has long designated the quadriceps femoris, gluteus maximus and hamstrings as the primary power generators during the propulsive phase of pedaling. The propulsive phase involves the simultaneous synchronized extension at both the hip and knee joints. Historically, the cycling and medical community has generally accepted the gluteus maximus and hamstrings as primary thigh extensors. There has been literature published which has presented evidence that may substantiate the addition of the adductor musculature, specifically the adductor magnus, to this group. This literature has not only theorized the adductor musculature as being biomechanically better positioned to be a major contributor to hip extension. It also has presented empirical evidence including; magnetic resonance imaging and electromyography studies may have substantiated this theory. The purpose of this paper is to elucidate this possible relevant evidence, which may change the perception of the role of the adductor musculature in pedaling.

Exploring Basal Metabolism Insights from Pro Tour Cyclists

2024-04-05T15:32:24+02:00

Introduction: In elite cycling, the alignment between calorie expenditure and calorie intake is crucial to optimize performance. Therefore, an accurate determination of the basal metabolic rate (BMR) holds significant indications for adapting nutrition to training. However, existing equations for estimating BMR are often based on recreational athletes, lacking specificity for elite cyclists. Therefore, this study aimed to determine BMR in elite cyclists using indirect calorimetry and to verify commonly used equations in this population. Methods: Twenty elite cyclists from a UCI Pro Tour team participated. To determine BMR, indirect calorimetry measured oxygen consumption (O2) and carbon dioxide production (CO2) whilst participants had to lay still for at least 15 minutes. Participants did not eat for at least 4 hours and refrained from exercise for a minimum of 10 hours before the start of the test. Pulmonary BMR was calculated (Weir, 1949) and compared with established equations (Spijker-Hoven et al., 2010; Van Horen et al., 2023) and the error was calculated. Results: Mean age, body mass and body length were 25 ± 4y, 75.9 ± 8.5 kg and 174.2 ± 36.7 cm respectively. On average the sum of the 8 skinfolds was 48.3 ± 12.7cm. The mean BMR using the Weir formula was 2019.7 ± 229.3 kcal. Compared to Van Horen (2023) and Spijker-Hoven (2010), the Weir formula differed with 11.79 ± 0.09% and 10.74 ± 0.07 %, respectively. Conclusion: This study provides valuable insights into accurately assessing BMR in elite cyclists and highlights the preference for individual measurement of the BMR as the values deviate from predictive equations. Our findings reveal an underestimation of BMR using standard estimating equations instead of indirect calorimetry. An analysis of the maximal fat oxidation rate during an incremental test was conducted, however results are not yet clear.

Validity of a commercial wearable sensor measuring respiratory frequency in cycling

2024-04-04T14:32:47+02:00

Please refer to the file attached in the previous step.

Female Cycling Movement: how to construct biomechanical digital-twins

2024-03-13T10:49:19+01:00

Cycling witnesses an increasing number of women breaking barriers and inspiring change. Despite these advancements, there remains significant work to achieve full equality and recognition for women cyclists. Key gender gaps persist in:

Ergonomics and performance optimization: The cycling industry largely focuses on tacit and explicit knowledge on male physiology, neglecting the distinct needs of female cyclists. This results in equipment and training regimens that may not be optimal for women's bodies, potentially leading to discomfort and sub-optimal performance.
Understanding and preventing injuries: Research has primarily focused on male cyclists, leaving significant knowledge gaps on prevalence and specific types of injuries in women due to cycling. This lack of understanding hinders the development of appropriate prevention strategies, treatment protocols and performance optimization in elite athletes and recreants.
Inclusive design: From bicycle design to infrastructure development, the industry often overlooks the specific needs and preferences of female cyclists. This creates an environment where women might feel less safe, comfortable, or catered to, potentially perpetuating the existing participation gap.

The biomechanics of women exercising significantly differ from those of men, starting with notable distinctions in skeletal anatomy. Women typically have a wider pelvic region, shorter legs, and an increased femoral angle from hip to knee. Additionally, women generally exhibit greater joint mobility and more flexible ligaments compared to men. Beyond skeletal differences, there are substantial disparities between female and male skeletal muscles, including variations in energy metabolism, fiber type composition, and contractile speed. Additionally, fat storage patterns differ significantly, shifting the center of gravity's location, with women primarily storing fat subcutaneously in the breasts, buttocks, and thighs, while men tend to accumulate visceral fat within the abdomen.

These differences have profound implications for performance, injury risk, and equipment needs. Despite their significance, current biomechanical models often fall short. Many models treat females as scaled-down versions of males, leading to inaccurate assessments and overlooking the unique needs of female athletes. This oversimplification hinders the development of appropriate equipment, limits our understanding of female athletic performance, and potentially contributes to an increased risk of injuries for women in sports.

We aim to analyze specific kinematics and dynamics of female cyclist using 4D movement measurements (3D+time) combined with medical imaging and numerical simulations to achieve accurate biomechanical human models. The research will provide valuable insights into the biomechanics of females both athletes as well as non-athletes presenting with even larger variance in body sizes.

In this paper we outline our scientific methodology that we will use to that end: combining 4D body scanning, medical imaging and numerical simulations to acquire next generation biomechanical models.

Fatigue resistance in road cycling: does the intensity of the accumulated work impact power output ?

2024-03-13T10:46:42+01:00

A single paragraph of 200 to 300 words. The abstract should not contain any undefined abbreviations or unspecified references

The effect of reducing work rate on total work done, and exercise tolerance, during severe intensity exercise.

2024-03-06T09:57:29+01:00

Introduction

The hyperbolic relationship between power output and time to exhaustion during high-intensity exercise can be described by a power asymptote, critical power (CP), and curvature constant, W′. CP demarcates the heavy and severe intensity domains. W′ it is considered a fixed and finite amount of work that can be completed above CP which when depleted exhaustion will occur, or work rate has to be reduced below CP (Fukuba et al. 2003; Morton 2006; Poole et al. 1988)

The assumption that W’ is a fixed parameter has been challenged. Although Fukuba et al. (2003) originally demonstrated that after initially depleting 50% of W’ during severe intensity exercise, subsequently increasing or decreasing the work rate, did not result in any changes to the total work done. In contrast, Dekerle et al. (2015) showed that when work rate was reduced (from 140% to 105% of CP), 20% more work above CP was done than precited. This observation leads to the possibility that W′ may not be fixed which will have implications for predicting exercise tolerance during variable efforts (i.e., pacing), as well as the modelling of W’ depletion/reconstruction.

Therefore, the aim of this study is to (i) assess changes in total work done above CP when the work rate is reduced during severe intensity exercise (ii) assess if reducing the work rate just prior to exhaustion allows work to continue above CP.

Methods

Twelve healthy participants (8 males, 3 females; age: 21 [2] y, height; 1.80 [0.10] m, body mass; 68.2 [7.6] kg, V̇O_2max; 56.1 [11.07] mL·min^-1·kg^-1, maximal aerobic power (MAP); 361 [76] , W, CP; 253 [56] W, W′ 22.15 [7.57] kJ, mean [SD]) were recruited for this laboratory-based investigation. Participants attended the laboratory on seven separate occasions for the determination of V̇O_2max, MAP, CP, W′ and three severe domain exercise trials involving stepwise reductions in work rate. All tests were performed on an electronically braked ergometer (Lode Excalibur Sport).

The first two trials consisted of exercising at a fixed work rate which would result in the depletion of 70% of W′ in 90 sec and 180 sec. At this point the work rate was reduced to CP + 20 W and the exercise continued until volitional exhaustion. The third trial consisted of exercising at a fixed work rate to achieve volitional exhaustion in 5 minutes (P_5TTE). At this point, when pedal cadence began to reduce (by approximately ~5 rpm which is a typical indication of exhaustion), the work rate was rapidly reduced by a work rate equal to 25% of the difference between CP and P_5TTE. This reduction in work rate was repeated a further two times (three work rate reductions in total) after which exercise continued until volition exhaustion. In each trial, the total work was predicted based on CP/W' (PRED_WORK) which was the same for each condition. Total work above CP was measured during each trial (WORK_90s, WORK_180s, WORK_P5TTE).

A one-way repeated measures ANOVA were used to compare differences between predicted and total work during the three trials. Where a significant effect was observed, Bonferroni-corrected post hoc t-tests were used to locate differences. Statistical significance was accepted at p<0.05 and data are presented as mean [SD].

Results

In all three trials, more work done was completed than predicted. There were no differences in the amount of work done between the three trials (Table 1).

Table 1. Predicted and measure work above CP in the three experimental trials.

Depletion Trial	PRED_WORK(kJ)	Measured_WORK(KJ)	Increase in work (kJ)		Increase in work (%)	P-value
WORK_90s	22.15 [7.57] 22.15 [7.57] 22.15 [7.57]	26.92 [7.84]		4.75 [1.44]	25%	<0.001
WORK_180s		27.64 [10.54]		5.49 [4.34]	22%	<0.01
WORK_P5TTE		24.90 [8.02]		2.75 [1.4]	12%	<0.001

P value is Measured vs. Predicted work

Discussion

W′ has more flexibility than originally conceptualised. Regardless of the initial work rate (~150% and 134% of CP), after 70% of W' has been depleted and work rate is reduced, approximately 25% (WORK_90s) and 22% (WORK_180s) more work can be performed than predicted from the CP model. It is also demonstrated that work above CP is possible (~12%) past predicted volitional exhaustion when reductions in work rate are implement as exhaustion is reached. We term this ‘residual capacity’.

In conclusion, W’ is not a fixed parameter of the power-duration relationship. If the work rate is reduced but still above CP, work can be continued for longer than predicted. It is also possible to continue performing work (above CP) even when theoretically depleted (i.e., W′ reaches 0 kJ) provided the work rate continues to decline.

Implications for applied practitioners

These findings may have implications for pacing strategies, as it appears a positive pacing strategy leads to a greater amount of work above CP. This also may have implications for W′ modelling as work can continue above CP with rapid drops which theoretically means W’_balcan become negative.

Thrifty Reservoir

2024-03-13T09:53:46+01:00

Thrifty Reservoir (TR) is a phenomenological model of field behavior of a rider, both in training and racing. The main component of TR is an energy reservoir; a stream of energy enters the reservoir, and an output stream propels the bike at the will of the rider. A control is exerted on the reservoir level. It is a PID (Proportional, Integral, Derivative) control, as it is usual in process engineering. Generally speaking, the control effect is to reduce the power available to the rider as much as the reservoir content is depleted. This property is a sort of thrift and therefore the model is named thrifty reservoir. This feature of TR, as far as the author knows, is a real novelty in cycling modelling as it imports concepts from process engineering into the cycling field. The model is mathematically described by a couple of equations: a differential equation for the dynamics of the reservoir and an algebraic equation for the control.

TR is easily applied to training session with intermittent exercise or race conditions where intensity of effort is very variable in time as in a race or in a road training session. In this capacity TR differs from models based on explicit formulas, which work only on average values and have difficulties with intermittency. TR differs also from W'bal models which have no control mechanisms on reservoir content, and therefore have difficulties in identifying maximal effort points, while with TR they are easily identified.

TR predictive capacity may be applied day by day to road trining sessions and races without any need to run specific tests to determine its parameters. TR development may lead to a valuable tool available to trainers in their work, for instance in monitoring training progress, in designing more effective training sessions, and race strategy as well.

Incorporating the maximal mean power profile in time trial simulations for more efficient optimal pacing strategy calculations

2024-04-16T10:51:32+02:00

Mathematical modelling in cycling enables retrospective analysis and predictive simulations, crucial for optimizing performance. This study introduces a numerically efficient notation for incorporating a rider’s maximal mean power profile, enhancing computational times for pacing strategy calculations while maintaining physiological relevance. Using exponentially weighted rolling averages (EWM) expedites MMP computation compared to classic averages, with constraints ensuring the accuracy of EWMτ. Applied to the 21st stage of the 2024 Tour de France, the methodology demonstrates its efficacy in optimizing pacing strategies. The proposed solution offers a streamlined alternative to existing models, promising reduced computational costs and enhanced optimization algorithms, thus advancing cycling performance analysis.

The effect of infrared radiation emitting garments on oxygen uptake kinetics and oxygen cost during moderate intensity cycling

2024-03-04T16:40:51+01:00

INTRODUCTION

Oxygen uptake (O₂) kinetics are an important determinant of exercise performance (Burnley & Jones, 2007). Speeding O₂kinetics can spare anaerobic energy stores at the onset of exercise, consequently enhancing exercise performance (Bailey, Vanhatalo, Wilkerson, Dimenna, & Jones, 2009). Both exercise training (Jones, Grassi, Christensen, Krustrup, Bangsbo & Poole, 2011) and dietary interventions (e.g. nitrate supplementation; Vanhatalo, Bailey, Blackwell, DiMenna, Pavey, Wilkerson, Benjamin, Winyard & Jones, 2010) have been shown to alter O₂kinetics.

KYMIRA garments, powered by Celliant, are a novel infrared (IR) emitting fabric that re-emit absorbed body heat as IR. IR emission has been shown to increase blood flow during exercise (Katsuura, Fukuda, Okada, & Kikuchi, 1989) which could increase muscle oxygen delivery, and potentially alter O₂kinetics. Indeed, previous work has shown that IR emission using similar garments reduced the oxygen cost of cycling (Worobets, Skolnik, & Stefanyshyn, 2015), although O₂kinetics have not been systematically investigated.

The aim of this study was to investigate whether KYMIRA garments alter O₂kinetics and oxygen cost during moderate intensity cycling.

METHODS

3 healthy male participants (age: 21 ± 1 yrs; height: 175.4 ± 4.6 cm; body mass: 73.4 ± 3.6 kg; O_2peak50.4 ± 3.1 ml/kg/min) provided written informed consent for this repeated-measures, counter-balanced experiment. Initially, participants performed a ramp test to determine gas exchange threshold (GET) and O_2peak.

Participants visited the laboratory on two further occasions, each separated by at least 14 days. On each occasion, participants donned cycling bib-tights and a t-shirt of either IR emitting fabric (IRF) or similar clothing without any IR emitting technology (SHAM). Garments were worn for 1.5 hours prior to performing standardised bouts of moderate intensity cycling exercise. This consisted of two repeats of a 3-minute 25 W warm-up followed by a square-wave transition to a power eliciting 90% of GET for 6 minutes. Bouts were separated by 5-minutes passive recovery.

Breath-by-breath pulmonary gas exchange data were analysed using mono-exponential models with mean response time (MRT) calculated from 0 sec without time delay. Phase II time constant (tau, Ƭ) and amplitude were calculated with the first 20 sec of data deleted. Average O₂over the last 30 (O₂₍₃₀₎) and 60 (O₂₍₆₀₎) sec of exercise was also determined.

Data were analysed by paired sample t-test. Statistical significance was accepted at p<0.05 and data are presented as mean ± SD.

RESULTS

Phase II Ƭ (25.2 ± 2.8 vs 27.1 ± 6.9 sec; p=0.524) and amplitude (788.5 ± 45 vs 842.7 ± 67.7 ml.min^-1; p=0.387) were not different between IRF and SHAM, respectively.O₂₍₃₀₎(1713 ± 29 vs 1822 ± 73 ml.min^-1; p=0.049) and O₂₍₆₀₎(1751 ± 54 vs 1843 ± 40 ml.min^-1; p=0.013) were lower in IRF vs SHAM, respectively. MRT was also lower (40.2 ± 1.9 vs 46.4 ± 0.6 sec; p=0.033) in IRF vs SHAM, respectively.

CONCLUSION

IR exposure using KYMIRA garments appears to have reduced the O₂over the last minute of moderate intensity exercise in these three participants. This was achieved without altering the phase II O₂kinetics but with a reduced overall MRT response.

Mechanisms of action for this reduced oxygen cost remain to be determined, however use of near-infrared spectroscopy will aid our understanding of whether an increased oxygen delivery and/or extraction are possible explanations. Further study will add to the number of participants in this study. Possible implications to cycling performance are also to be determined.

REFERENCES

Bailey, S. J., Vanhatalo, A., Wilkerson, D. P., Dimenna, F. J., & Jones, A. M. (2009). Optimizing the “priming” effect: Influence of prior exercise intensity and recovery duration on O2 uptake kinetics and severe-intensity exercise tolerance. Journal of Applied Physiology, 107(6), 1743–1756. https://doi.org/10.1152/japplphysiol.00810.2009

Burnley, M., & Jones, A. M. (2007). Oxygen uptake kinetics as a determinant of sports performance. European Journal of Sport Science, 7(2), 63–79. https://doi.org/10.1080/17461390701456148

Jones, A. M., Grassi, B., Christensen, P. M., Krustrup, P., Bangsbo, J., & Poole, D. C. (2011). Slow component of V̇o2 kinetics: Mechanistic bases and practical applications. Medicine and Science in Sports and Exercise, 43(11), 2046–2062. https://doi.org/10.1249/MSS.0b013e31821fcfc1

Katsuura, T., Fukuda, S., Okada, A., & Kikuchi, Y. (1989). Effect of ceramic-coated clothing on forearm bloodflow during exercise in a cool environment. The Annals of Physiological Anthropology, 8(1), 53–55. https://doi.org/https://doi.org/10.2114/ahs1983.8.53

Vanhatalo, A., Bailey, S. J., Blackwell, J. R., DiMenna, F. J., Pavey, T. G., Wilkerson, D. P., … Jones, A. M. (2010). Acute and chronic effects of dietary nitrate supplementation on blood pressure and the physiological responses to moderate-intensity and incremental exercise. American Journal of Physiology - Regulatory Integrative and Comparative Physiology, 299(4). https://doi.org/10.1152/ajpregu.00206.2010

Worobets, J. T., Skolnik, E. R., & Stefanyshyn, D. J. (2015). Apparel with Far Infrared Radiation for Decreasing an Athlete’s Oxygen Consumption during Submaximal Exercise. Research Journal of Textile and Apparel, 19(3), 52–57. https://doi.org/10.1108/RJTA-19-03-2015-B007

Heart rate response times measured in the field as indicators for endurance performance in cycling

2024-03-21T10:26:28+01:00

Purpose: To couple power and heart rate data of professional road cyclists collected in the field and study its relationship with performance obtained in controlled settings. Methods: Heart rate and power data during all cycling activities was collected of 23 elite road cyclists for 2 years. Weekly athlete-specific heart rate response times (recuperation, delay and maximal response times) were extracted from models connecting heart rate and power output. Cyclists visited the lab several times to determine performance, defined by a 1- and 10-minute time trial. Linear regression was performed between performance and weekly heart rate response times. Results: No significant relations between heart rate response times and 1 min TT power were found. Averaged per rider, significant (negative) correlations were obtained between the heart rate response times and 10 min TT power. Accuracies (R²) of linear relationships were 0.54 (p < 0.01), 0.49 (p < 0.01) and 0.24 (p = 0.03) for recuperation, heart rate maximal response and delay times, respectively. Moreover, significant (negative) correlations were found between 10 min TT power and heart rate delay and maximal response times within 14 days of the performed lab test. Linear relationships were fit with accuracies (R²) of 0.46 (p = 0.02) and 0.37 (p < 0.01) for delay and heart rate maximal response times, respectively. Conclusion: Heart rate response times seem important physiological indicators concerning endurance performance in cyclists. This suggests a rider’s endurance performance can be assessed periodically by coupling power and heart rate data collected in the field.

The road to olympic failure is paved in poor risk management

2024-03-04T12:03:44+01:00

In recent years there have been numerous high-profile incidents in professional cycling that have endangered the lives of cyclists, fellow competitors, and spectators in track and road disciplines. Yet, there has been little research conducted to ascertain why, and how things can be improved within the sport to improve safety. To illuminate this area, we apply safety culture theory to the now infamous Australian Cycling 2021 Olympic incident that saw their Olympians handlebar snap clean off during the competition. The results show that dimensions of safety culture are apparent in this incident, with distinct parallels between it and high-profile failures in other industries. The lack of adherence to rules, the existence of light-touch regulation, and management safety attitudes are concerning, and suggestive of a need for immediate improvement at a governing level. This research provides a conceptual basis for further research in the area to ensure interventions are effective at preventing future safety critical incidents within the sport.

External and Internal Load Variations in Professional Male Cyclists during a 14-day Training Camp

2024-03-06T11:52:14+01:00

Professional athletes take part in training camps during specified periods of a season aiming to optimize training adaptations and in preparation for competitions. To improve performance and avoid overtraining it is crucial to find the right balance between training and rest. However, an intensified training period may result in overreaching. This study investigates internal and external training load parameters among 26 male professional cyclists during a 14-day training camp. Various metrics, including average power, distance, duration, fatigue, session-RPE, and training load, were measured and compared between the first and the second phase of the training camp. The second part showed increased values for these parameters, indicating heightened training intensity. Interestingly, sleep improved during the latter phase, and overall wellbeing remained unaffected. These findings may contribute to the field of professional cycling with valuable insights into the multifaceted aspect of athletes’ performance and wellbeing during a training camp.

Big Sprockets and Small-Pitch Chains: Advancements in Transmissions for Olympic Track Cycling

2024-03-06T11:50:49+01:00

It is well known that cycling is a sport in which the performance of the equipment is critical to the outcome of competitions. At the elite level, winning margins are often very small. For example in the men’s team pursuit at the Tokyo 2020 summer Olympics, the winning margin was 0.166 seconds against a winning time of 3 minutes 42 secs; in sprint events, the margins can be even smaller, the women’s individual sprint at the Rio 2016 summer Olympics was won by 0.016s and 0.004s in the two races of the final. Considerable effort is made by internationally competitive teams to ensure the best performance from athletes and equipment. The work described herein highlights some recent developments in the field of track bicycle transmissions, specifically related to the sizing and geometry of the chains and sprockets. The impact of these studies was quantified using a very accurate dynamometer and subsequently demonstrated in international competitions.

Development and validation of cycling self-efficacy scale

2024-03-13T09:58:51+01:00

N/A

Gender Difference in Functional Threshold Power Testing Among Triathletes: A Comparative Analysis

2024-04-05T15:30:19+02:00

This study investigated the performance differences in Functional Threshold Power (FTP) tests between male and female triathletes. The results revealed that males exhibited significantly higher FTP values and average power output compared to females, reflecting physiological differences in muscular strength that have been intensively documented. Meanwhile, despite the slower FTP value, female triathletes reached identical performance in terms of average cadence or speed revealed by the none significant gender effect. Since FTP serves as a crucial basis for training and competition strategies, its relationship with other intrinsic and extrinsic factors should be continuously monitored to enhance athletic performance.

The effects of gender on the association between oxygen consumption and electromyography during Cycling Maximal Capacity Testing in Triathletes

2024-03-06T09:56:03+01:00

N/A

2024-03-01T19:17:11+01:00

N/A

Maximum Power Available: An important concept for prediction of task failure and improved estimation of training loads in cycling

2024-03-21T10:25:05+01:00

Predicting cycling performance requires accurate quantification of the parameters of the power-duration relationship and detailed understanding of the training load-performance relationship. Existing models simplify training stress into single metrics, overlooking diverse responses to intensities and their time-dependency. The theoretical framework for the concept of Maximum Power Available (MPA) is described in this presentation. MPA is used to quantify instantaneous training stress and predict task failure in cycling. It employs a modified 3-parameter critical power model capable of fitting intermittent data while relying solely on the W’ balance differential model. Rather than W’ balance = 0, task failure is defined as MPA reaching the task work rate. Additionally, MPA may be used to derive more valid training load metrics when compared with other training load metrics. By acknowledging the multidimensional nature of exercise stress, this model provides a more comprehensive model for the power-duration and the training load-performance relationship, with the potential to facilitate more effective training program design and performance optimization.

GENDER EFFECT ON LOWER LIMB KINEMATICS DURING CYCLING

2024-03-06T09:32:03+01:00

本研究的目的是調查騎車過程中下肢運動學的性別差異。共有 15 名參與者參與了這項研究，其中男性 8 名，女性 7 名。每位參與者以 150W 的恆定阻力、90rpm 的踏頻完成 1 分鐘的騎乘試驗。進行運動分析以捕捉取樣頻率為 200Hz 的運動學參數。進行配對抽樣 t 檢定來比較性別之間的差異，顯著水準設定為 α = 0.05。結果顯示，與男性相比，女性在騎自行車時髖關節和膝關節的最大和最小角度都更大。總之，目前的自行車組裝方法似乎更適合男性而不是女性。

Investigating Anxiety in Highly Trained and Elite Cyclists

2024-03-01T17:42:04+01:00

A research study is being performed which has a three-phase approach. The research study’s overall aim is to explore whether debilitative performance anxiety exists in highly trained and elite cyclists. If it did exist, then the researcher would explore if Eye Movement Desensitisation (EMDR) may be an appropriate treatment approach. The research study has now in the final stages of phase two which is a pilot study of EMDR with six highly trained and elite cyclists.

Machine learning models to predict kinetic variables in cycling

2024-03-06T09:37:08+01:00

This study aimed to predict index of effectiveness based on lower limb joint kinematics in the sagittal plane and four additional metrics (individual’s mass, power output, pedalling cadence, and horizontal knee position). Seventeen cyclists performed nine submaximal tests of 1 min. Joint kinematics were recorded using a three-dimensional motion capture system and pedalling kinetics were assessed via the pedalling force. After min-max normalization, several predictor selection methods were applied. The performance of all models was evaluated by 10-cross validation. A neural network-based model was developed with high accuracy (Adjusted R² = 0.95). Seven multiple linear regression models were developed highlighting a model of 11 predictors (Adjusted R² = 0.86). With this model, the most important predictors that influence the index of effectiveness are known. These models can be integrated into 2D or 3D motion capture systems, which could be useful for bike fitting professionals and trainers to evaluate cyclist's pedalling technique.

Experimental determination of transmission performance: sensitivities to hardware design and test implementation

2024-03-21T11:30:59+01:00

The performance of bicycle transmissions is of interest to the cycling sector for both elite racers and amateur hobbyists. Great efforts are made by pro teams and individual cyclists to maximise the performance of transmission through equipment choices, gearing selection, and choice of lubrication. Correct selection can both increase the power efficiency of the transmission, improve the cycling experience, and improve the longevity of components.

Transmission performance for cycling applications can be assessed practically by different methods. Test equipment may measure decay due to friction, or be continuously driven against resistance; chain components may be tested in isolation, or tested as a complete loop at a system level; and transmission movement may be continuous or reciprocating in nature. Literature on various apparatus was reviewed by both Aubert, Roizard, Grappe, and Lallemand (2023), and Author (2023).

Different test methods come with associated loading and boundary conditions, resulting in nuanced differences in contact mechanics and lubricant behaviours in the articulating links of chains under test. Consequently, comparing results from different testing methods, and extrapolating the applicability of results to real-world circumstances, is a non-trivial task.

Dynamometer tests can offer the best direct measurement of performance in cycling applications by testing at a system level with broadly accurate transmission boundary conditions. There are two categories of dynamometer test apparatus used in industry and academia: Transmitted Power Measurement (TPM) and Frictional Power Measurement (FPM) dynamometers, as described by TPM type dynamometers prioritise realism of loading (Author, 2002; Spicer et al., 2001) while FPM prioritises precision of measurement (Friction Facts, 2012; Muc-Off, n.d.). These are also known as Full Load Test (FLT) and Full Tension Test (FTT) apparatus respectively.

In this study, analytical models from Author (2002) are adapted to illustrate the effect of the different boundary and loading conditions between these dynamometer types. Furthermore, empirical results from a TPM dynamometer are presented which demonstrate the dependency of cycling specific loading conditions on the test measurand. Sophisticated control of the electric machines with variable frequency drives is exploited to deliver a cyclist’s pedalling torque profile to the driving sprocket of the transmission, and average performance determined over a shaft revolution.

Boundary conditions and loading conditions are shown both analytically and empirically to affect the measured performance of a transmission under test where previously conditions have been assumed to be nominally alike. This demonstrates that measured performance is sensitive to the testing conditions and care should be taken in comparing similar, but not identical, test environments as well as extrapolating results to real-world use cases.

A PREVENTION, REHABILITATION, AND BIOMECHANICAL ASPECTS IN CASE OF F.L.I.A. (Flow Limited Iliac Artery) IN HIGH-LEVEL CYCLISTS

2024-03-06T09:29:35+01:00

BACKGROUND:

Obstructive pathology of the iliac artery is a professional disease associated with the mileage covered on a bicycle, especially with racing bikes. The lesion is localized at the level of the iliac arterial axis, where a fibrous process (endofibrosis) occurs, which narrows the artery until it completely obstructs it.

The pathogenesis of endofibrosis or FLIA (Flow Limitation of Iliac Artery) is to be found in the bending of the artery linked to the particular posture and the consequent "shear stress" (wall damage) of the high-speed blood wave, together with the flow turbulence. From an epidemiological point of view, it is estimated that the pathology may affect 5-10% of high-level cyclists.

The literature suggests that the likely cause of this pathology is attributed to repeated direct mechanical stress, leading to the development of fibrous tissue and subsequent narrowing within the artery.

The external iliac artery would be the one most commonly damaged due to its anatomical position and attachment to the psoas muscle during hip flexion; in fact, in all diagnosed cases of FLIA, a more or less significant hypertrophy of the iliopsoas muscle has been found (the main silent cause of this pathology).

In the most recent studies, it has been found that not only the arterial vessel suffers from continuous mechanical stress, but both, the venous vessel can also become a victim of the process, and deep vein thrombosis (DVT) is the direct consequence of compression of the common iliac vein between the hypertrophic psoas muscle and the L5 vertebral body.

The symptoms reported by the subject are thigh pain with subsequent irradiation to the leg when pedaling under maximum effort. The pain is unilateral in most cases, with a drastic reduction in muscle power and sports performance.

The rarity of the disease in endurance athletes, particularly in young cyclists, and the presence of symptoms common to other musculoskeletal pathologies prevalent in the world of sports, lead even the best doctors, physiotherapists, or kinesiologists astray, prompting athletes to undergo redundant tests and visits. For this reason, the diagnosis is usually delayed in the majority of cases.

After clinical suspicion, the diagnosis of iliac artery endofibrosis is made by measuring the Winsor index (ratio between the blood pressure of the leg and that of the arm - Ankle-Brachial Index ABI) on both sides after a dynamic test. Winsor index measurement at rest is indeed normal. Ultrasound and color Doppler ultrasound can document an endoluminal thickening of the iliac of a few millimeters, but often ultrasound and color Doppler velocimetric images are normal. By using angio-CT, it is possible to demonstrate the steno-obstructive lesion by performing accurate measurements of the diameter of the various arterial segments.

Until this moment, the best intervention modality, according to the literature, remains surgical operation, primarily for individuals who wish to continue competing at a high level or who want to maintain a sporty lifestyle.

OBJECTIVE:

The aim of this work is to raise awareness within the cycling community about this lesser-known pathology, both among athletes and especially among coaches, as well as to offer a non-surgical treatment for this condition. Treatment begins with investigating the root cause of iliopsoas muscle hypertrophy through kinesiological and osteopathic tests. Thanks to teamwork, this information will be crucial for adjusting the athlete's riding position, addressing any muscle imbalances, and designing a targeted gym exercise program.

The other ongoing project by Paolo Raugei, a vascular surgeon who has been evaluating cyclists from around the world for over 15 years, involves the use of thermography, a precise and reproducible technique that allows the visualization of reduced blood flow signs in vivo and it facilitates the diagnostic process.

Thermography is a non-invasive diagnostic method based on the acquisition of images resulting from the differentiated emission of infrared radiation by the body, with the corresponding thermal variations resulting from a reduced influx of arterial blood. The instrumentation is capable of detecting temperature variations up to 0.05°C.

METHODS:

First of all, by modifying the bike's biomechanics, can reduce the conditions that favor the progression of the pathology, whose persistence during constant top sports activity may lead to the need for surgical solution.

The aim of bike's biomechanics is to modify the position of the cyclist in such a way as to widen the trunk-lower limb angle of the athlete and the only parameter directly affecting the maximum hip flexion value is the length of the crank arm.

The other fundamental intervention is represented by postural re-education with targeted exercises in the gym with the aim of strengthening the gluteal muscles, the main antagonists of the psoas muscle, reinforcing the abdominal muscles, stabilizers par excellence and keeping the iliopsoas muscle elongated and relaxed with appropriate stretching exercises.

Finally, based on the osteopathic assessment, it will be necessary to intervene on any other dysfunctional systems.

RESULTS:

During the second follow-up visit after 6 months from the initial diagnosis, Paolo Raugei, the vascular surgeon at the Prato (Italy) hospital, observed in the case study a decrease in pressure drop between the arm and ankle, specifically from 50mmHg in the initial diagnosis to 20mmHg.

Finally, exactly 9 months after the initial diagnosis, for the first time in his life and after checking and verifying multiple times, overturned the initial FLIA diagnosis and confirmed the absence of any fibrotic buildup in the right artery and the pressure drop parameter within limits.

DISCUSSION:

Despite the significant diagnostic achievement, it is worth noting that the symptoms of the young cyclist have not completely disappeared.

A 12-month follow-up is necessary to verify if the symptoms also completely disappear, clearly continuing with the targeted exercise program and follow-up visits by various professionals in the field.

Fortunately, in recent years, this pathology has become the focus of many studies by leading experts in the field. However, further research is needed regarding precise guidelines for conservative rehabilitation, especially to avoid costly and risky surgical operations or the cessation of competitive sports practice.

Developing training intelligence in interdisciplinary performance teams: perspectives from elite track cycling

2024-03-04T09:32:20+01:00

Introduction

The effectiveness of sport scientists and performance staff in elite cycling often depends on their ability to complement the wider performance team – consisting of the cyclists, coaches, and other interdisciplinary practitioners – to support athlete development. A practitioner’s impact on athlete development and performance may be moderated by their ability to implement their knowledge and expertise, which itself can be constrained by several factors within the high performance sport environment. The aim of this study was to qualitatively examine elite track cycling coaches’ perspectives of how practitioners can best support cyclists and their coaches through the implementation of sport science and research in practice to optimise training and performance.

Methods

Elite track cycling coaches (n = 8) who had been working at Olympic or UCI World Championships competition level participated in one-off semi-structured interviews. The ~1-hour long interviews included several questions related to their engagement with sport science, practitioners’ effectiveness in contributing to track cyclist development, and how sport science and research can impact training and performance. Reflexive thematic analysis was conducted to identify common themes in the coaches’ perspectives.

Results

Coaches’ experiences of engaging with sport science to support practice were generally positive, and several important factors were identified that may enhance the effectiveness of practitioners within interdisciplinary performance teams to develop collective training intelligence. Three principal themes were identified from the data: ‘conversation & the information dynamic’, highlights the value of information and feedback within the performance team to influence decision making; ‘integrating performance components for the individual’, details the importance of individualised and integrated approaches to address athlete needs; and, ‘science to complement the vision’, examines the limitations of research and data in practice.

Conclusion

The development of collective training intelligence within the performance team may increase the ability to develop a more holistic understanding of athletes’ performance needs, and plan and prescribe training to more effectively address them. Within these findings, two key contributors were identified by elite track cycling coaches as central to this process: athletes deeply invested in, and actively contributing to, the development process; and, performance staff identifying and filtering research and data to impact decision making and athlete development. These findings allowed for the development of a model outlining the potential contexts and mechanisms that contribute to training and performance outcomes that, through their interaction, contribute to the development of training intelligence within interdisciplinary performance teams.

Competitive demand and training characteristics of international level paracyclists

2024-03-24T11:41:01+01:00

Introduction: Para-cycling remains relatively unexplored in the scientific literature. By analogy, training of high-level para-cyclists is based on able-bodied cyclists’ scientific knowledge. Training data and identification of competitive loads in different events provide valuable information for athlete preparation and assist practitioners in the specific preparation (Van Erp & al, 2020). A need for investigation of elite para-cyclists has recently been highlighted (Gee et al., 2021). No study has been conducted on the identification of competitive demand in para-cycling. The aim of this study is first to determine whether external load and internal load in competition differ according to paracycling classifications. Then, to investigate the link between competitive load and training load in a group of international level paracyclists.

Methods: Training and competitive data from 17 international level paracyclists (5 B, 1 C5, 3 C4,2 C3, 2 C2, 1 H5, 1 H4, 2 H3) were collected during the 2023 season. Participants underwent physiological testing sessions at beginning and at end of 2023 season. In each session, athletes performed an intermittent step test (IPT) on an ergometer (Cyclus 2; MSE Medical) to determine physiological zones according to a 3-zone model delineated by metabolic thresholds (Seiler & al, 2012). For training and competitions, external load data was measured from the mechanical power output (PO) in left and right pedals (Favero Assioma Duo pedals, Favero Electronics SRL). Internal load was measured using heart rate (HR) sensors (Polar H10, Polar Electro Oy). To measure competitive load, time spent in each physiological zone based on an indicator of external load (PO) and internal load (HR) and compared according to classification groups (C/ B / H). Training characteristics were compared through internal training load (based on HR data) and external training load (based on power output data).

Results: Our results show a significant difference in time spent in zone 1 and zone 3 in internal and external load between classification (p < 0.01). This may be explained by the density of the race, which induces more individual racing in the H group than tactical group racing in the C classification. These differences could imply different specific preparations. In time trials, all classifications spent a mean of 90,6% of the race in zone 3 without statistical differences between them (p > 0.05). Training load data revealed differences in training volume and intensity distribution between classifications (p < 0.05). C classification spent more time in zone 1 than B and H classification (p < 0.05). This could be explained by material and training environment conditions (lots of home trainers’ sessions for handbikers and visually impaired athletes).

Conclusion :

The study revealed a specific model of intensity distribution in road race events between para-cycling classifications. It also highlights difference in training intensity distribution model between classification. These results have an impact on training specific preparation according to the athletes' classification and could help practitioners.

Preliminary data: The effect of creatine supplementation on power output, lactate accumulation following 15-s all-out sprint test

2024-03-04T09:26:15+01:00

Abstract: Introduction: vLa_max is traditionally tested in a 15-s all-out sprint test. The variable is based on Mader’s model of energy system contributions and acts as a surrogate for the maximal glycolytic rate. On this foundation, vLa_max is not only used as a predictor for sprint performance but for endurance efforts as well. The aim of this study was to determine the effect of creatine supplementation on the results of testing procedure. Methods: 12 amateur cyclists (more forthcoming) were recruited. Participants performed a 15-s all-out sprint test on a Cyclus2-ergometer. Capillary blood lactate was sampled in the 8 minutes following the test. Participants underwent the testing procedure four times under different conditions in this order: a familiarization trial, baseline, placebo (4x5 g/d maltodextrin for 5 d) and creatine supplementation (4x5 g/d creatine monohydrate for 5 d). Weight and body composition was determined using BIA on each visit. Results: At present state, ANOVA revealed significant a significant increase in fat-free mass under the creatine condition compared to all other conditions. For all other measures (peak and mean power output, ∆La, calculated total body lactate production), no differences were found between different conditions. Discussion: Based on the data at hand, a loading phase of creatine supplementation increases fat-free mass. Tendencies of mean values across groups show an increase in mean power output over the 15-s all-out sprint test under the creatine condition while simultaneously decreasing ∆La compared to baseline and placebo condition. However, no statistical significance was reached. Further research is needed to determine the influence of a popular ergogenic aid on metabolic testing of glycolytic rate.

Estimation of Heart Rate Recovery from Field Rides

2024-03-06T10:29:26+01:00

Heart rate recovery (HRR) is a measure of time required for the heart to resume its resting heart rate (HR) after a maximal intensity exercise load. Quicker recovery has been associated with better cardiorespiratory fitness (CRF). Therefore, HRR can be regarded as a fitness indicator and may serve as a tool to monitor the performance potential of an athlete as well as to optimize the training schedule.

To reliably measure HRR requires the athlete to enter a controlled laboratory setup with an ergometer or a treadmill. There is no standard or generally agreed upon protocol to measure HRR. One common approach is to measure the drop of heart rate during the first 30, 60, or 120 seconds following the cessation of maximal exercise load. However, such laboratory testing interrupts training schedules and may not always be available in practice. In this work, we propose ways to estimate HRR from data collected with power meters and heart rate sensors during field rides. This allows for continuous and automatic tracking of HRR without the burden of regular lab tests.

Our general approach is as follows. Given power and HR data we estimate linear and dynamical systems that serve as accurate mathematical models to predict the heart rate from power data. These models can also predict the decay of HR after a bout of maximal exercise intensity and thereby yield a way to estimate the HRR.

The first model assumes a linear function that defines the HR equilibrium for given (constant) power demands. An ordinary differential equation (ODE) rules that the HR derivative is proportional to the difference of the HR equilibrium for the current power demand and the present HR. For constant power demands this model prescribes exponential solutions for the HR that asymptotically approach the corresponding equilibrium HR. The inverse constant of proportionality in the ODE can be interpreted as the time duration required for the HR to drop 63% towards the resting HR after a presumed constant exercise load. This time constant therefore can take up the role of HRR.

The second model is a Wiener system, given by the sum of the convolution of the uniformly sampled power signal and the resting HR. The (one-sided) convolution kernel accounts for the accumulated influence of the past power demand on the current heart rate and also models the delayed effect of changes in power on the heart rate. Again, the 63% drop towards the resting HR after a constant exercise load can be read off the model; it is given by the 63^rdpercentile of the convolution kernel.

Our models are extended and improved versions of previously proposed models for HR prediction from power data. We discuss, validate, and compare the HRR from the two models on a large dataset consisting of all recorded training and racing activities of three professional world class cyclists and three ambitious hobby riders collected over three consecutive years.

Pedaling Variability in Cycling: A Nonlinear Approach

2024-03-21T10:23:21+01:00

Human movement is a complex phenomenon that varies across different levels and scales. Variability is often seen as a source of error or noise to be reduced or eliminated, especially in motor learning and rehabilitation. However, recent advances in nonlinear dynamics have challenged this view and suggested that variability is not only unavoidable, but also essential for healthy and functional movement (Stergiou & Decker, 2011). According to this perspective, variability reflects the adaptability and flexibility of the neuromuscular system to changing demands. Moreover, variability has a specific structure and organization that can be quantified by nonlinear measures of complexity, such as entropy, fractal dimension, largest Lyapunov exponent (LyE). These measures can reveal an optimal state of variability, characterized by a balance between stability and flexibility, order and disorder, predictability and unpredictability. This state is associated with mature motor skills and healthy conditions, while deviations from this state can indicate rigidity or instability, lack of coordination or control, pathology or impairment (Stergiou, Harbourne & Cavanaugh, 2006). Therefore, studying variability and its nonlinear properties can provide new insights into the mechanisms and principles of human movement, as well as novel tools for assessment and intervention. This can have important implications for various fields and disciplines that deal with movement generation, such as robotics, psychology, cognitive science, and neuroscience. To illustrate the potential of this approach, we conducted a study on the relationship between human and bicycle as a human-machine system, as an example of applying these concepts to a real-world scenario. We started from the study of Wurdeman et al. (2013). They investigated how the LyE of different lower-limb joints related to the preference of prosthetic devices in individuals with transtibial amputation. They found that the LyE of the prosthetic ankle was strongly correlated with the preference, suggesting that the patients preferred the prosthesis that allowed them to maintain an optimal level of variability in their gait. This implies that the LyE can be used as an objective measure to evaluate the suitability and effectiveness of prosthetic devices for gait rehabilitation. Based on this finding, we hypothesized that a similar analysis of variability and LyE can be applied to study the human-bicycle system. For example, the optimal saddle height is generally determined by the Holmes static method with a knee flexion angle (KFA) between 25° and 35° (Swart & Holliday, 2019). We measured the joint angles of the knee on the sagittal plane during 5 minutes of cycling with a resistance that allowed the subject to maintain a comfortable cadence (about 90rpm). Four different conditions were tested, varying the saddle height. The measurements were performed using an optoelectronic system. The variability of the time series was analyzed with linear measures such as the standard deviation and nonlinear measures such as the LyE. The results show that the highest values of LyE correspond to the only condition that allows a KFA between 25° and 35°. We propose that the variability and LyE of the joint angles can reveal the level of coordination and control between the human and the bicycle, as well as the adaptability and efficiency of the system to different conditions. This could provide new insights into the biomechanics and ergonomics of cycling, as well as the design and optimization of bicycles.

Durability is associated with higher resistance to fatigue in elite vs recreational cyclists.

2024-03-06T09:53:17+01:00

Introduction — In road cycling, the ability to perform maximum intensity efforts after hours of racing, or durability, can make a difference between winning and losing [1]. Specifically, differences between World Class and Continental-level athletes are best observed in the fatigued state [2][3][4], yet the reasons behind these level-dependent variations remain unclear. The aim of this study was to clarify the effect of prolonged duration exercise with interspersed maximal efforts on performance and fatigability in recreationally-trained and elite cyclists.

Subjects — Eighteen male cyclists from different levels have completed the study, among which twelve recreational (Age : 25 ± 3.1, Height : 180 ± 7.3 cm , Weight : 70 ± 8.8 kg, %Fat mass: 13 ± 3.2 % , VO2max : 61.9 ± 7.3 mL/min/kg, Critical Power (CP) : 298 ± 31 W) and six elite-level cyclists (Age : 23 ± 1.9, Height : 179 ± 5.0 cm , Weight : 71 ± 8.6 kg, %Fat mass: 12 ± 1.3%, VO2 max : 75.8 ± 5.4 mL/min/kg, CP : 378 ± 62 W).

Methodology—Participants rode on cycle ergometer (Cyclus2, RBM electronics, Germany) in the moderate intensity domain (90% VT1) interspersed with three exhausting bouts destined to deplete W’ (3-min-all-out test, 3AOT) [5] at 0, 90 and 180min elapsed. Power and heart rate (HR) were continuously monitored (Garmin HRM-Dual monitor). Blood lactate (Lactate scout, EFK Diagnostics), expired gases exchanges (Ultima CCM^TM) and ratings of perceived exertion (RPE, 6-20 Borg scale) were recorded every 30 min during moderate intensity bouts. Expired gases were measured during, and lactate concentration measured 30-s after each 3AOT. Knee extensor maximal voluntary contractions (MVC) were measured after warm-up, immediately after each 3AOT, and again 10 minutes post each 3AOT (Strain Gauge, Tedea Huntleigh).

Statistics — The normality of the distribution was assessed using a Shapiro-Wilk test, followed by an evaluation of variance homogeneity using a Levene test. Time and group effects in CP, W’, Peak power, VO2max and lactate concentration were assessed using analysis of variance models (ANOVAs). Significant main effects were followed-up by Bonferroni post-hoc procedures. Significance was set at p < 0.05.

Results — Elite cyclists were characterised by higher CP (378 ± 62 vs 298 ± 31 W), VO2max (75.8 ± 5.4 vs 61.9 ± 7.3 mL/min/kg), peak power (721 ± 96 vs 591 ± 98 W) and VT1 (244 ± 45 vs 199 ± 29W) than recreational cyclists. During moderate intensity cycling, there were no significant group or time differences in VO2, [La], RPE and HR. There were also no group differences in carbohydrate (CHO) consumption (2.3 ± 0.5 vs 2.2 ± 0.4 g/min) despite the higher absolute intensity and energy cost (20 ± 3 vs 17 ± 2 kcal.min^-1) in the elite group. There were significant alterations from 1^st to 3^rd 3AOT, in total work (elite: 75 ± 9 vs 81 ± 10 kJ; recreational : 59 ± 10 vs 62 ± 9 kJ) and [La] (elite: 13.4 ± 3.2 vs 8.0 ± 2.9 mmol.L^-1 ; recreational: 9.2 ± 3.9 vs 7.6 ± 2.9 mmol.L^-1). However, W' decreased significantly only in recreational cyclists (10.1 ± 1.4 vs 12.4 ± 9.1 kJ). There were no significant changes in CP or VO2peak during the three 3AOT for both groups. Knee extensor MVC decreased notably only in recreational group at the end of the session (122 ± 29 vs 104 ± 32 Nm) and after each all-out test. No differences in relative voluntary activation were found in either group.

Conclusion — The main finding of this study highlighted the increased fatigue experienced by recreational athletes compared to elite cyclists during extended exercise. These results are consistent with prior research [6], indicating a decrease in W' among recreational-trained cyclists. However, this decline is not observed in elite athletes, who demonstrate superior ability to repeat all-out efforts. This heightened fatigability is characterized by a greater degree of peripheral fatigue among recreational cyclists. Despite elite athletes demonstrating higher total work, greater work output during each 3AOT, and expending more of their W' reserve during each 3AOT, there were no differences in initial force and W' between the groups afterward. Moreover, elite cyclists exhibited similar CHO consumption but a greater contribution of fat to total energy expenditure at moderate intensity compared to recreational athletes.

Measuring the Aerodynamic Drag Reduction Effects of Jerseys in Road Riding Experiments

2024-03-06T11:49:09+01:00

Drag Coefficient (CD) has always been a crucial indicator for assessing the
aerodynamic characteristics of cyclists. In most experiments, measurements are conducted in a
wind tunnel. Despite the advantages of wind tunnel experiments featuring a controllable
environment compared to road test, the latter provide the data sought eventually. The main
objective of this study is to measure the aerodynamic drag reduction effects of jerseys on a cyclist
in road riding experiments. The equation for calculating the cycling power without the
consideration of the effect of crosswind was provided by Whitt and Wilson in 1974 [1]. In 1998,
Martin et al. [2] detailed the calculation methods for various factors with a certain level of
accuracy. In the literature, it is identified that Total Aerodynamic Power (PAT) consumption is
one of the primary sources of power loss during free bicycle motion; PAT typically is based on
the factors in terms of cycling speed, air density, and riding posture. In 2014, Osman [3] referred
the value measured by power meters as Direct Force Power Meters (DFPMs) against Opposing
Force Power Meters (OFPMs) which consist of the components of air resistance, slope, speed
changes, rolling resistance, and mechanical performance losses. Corrections were made for the
impact of crosswinds on the drag area (CDA) in outdoor environments.
This study is consisted of two parts. First, a crank-based power meter and a set of Look Keo
SRM EXAKT Power Pedals were installed on a bike for comparison. In addition, a three-hole
Pitot tube anemometer capable of measuring wind speed and the yaw angle relative to the
riding direction was employed. Secondly, through a power-based calculation method, a
comparison on the CDA values corresponding to two jerseys worn by a cyclist in two
experiments (A and B) was made. The road test experiments were conducted separately in
December 2022 and March 2023.
In this study, the power related to air resistance are calculated with the relative wind speed (Urel)
in the riding direction. As shown on figure 1, Urel is a sum of the riding ground speed (Vgs) and
the component of the wind speed (Vhw) in the riding direction. Urel was reduced from the
measurements by the three-hole Pitot tube, which included a measured wind speed U∞ and a
yaw angle β. Vgs was reduced from the GPS signals received by the power meters. Conceivably,
as Vgs increases, the relative importance of Vhw decreases, leading to a reduction in the impact of
crosswinds.
In figure 2-a, the CDA values of jerseys I and II on the same cyclist reduced from the
measurements of the crank power meter in two experiments A and B are presented. According
to the calculated CDA values, the aerodynamic performance of jersey II surpasses that of jersey
I. In figure 2-b, the CDA values reduced from the measurements of the pedal power meter in
Experiment B also indicate that jersey II outperforms jersey I. Moreover, these differences are
consistently substantial, with an approximate margin of 10%. The results exhibit a high level of
repeatability. Although the calculated CDA values may vary with different types of power
meters, distinct difference in the aerodynamic performance of two cycling jerseys can be
discerned.

Multi-sensor based Analysis of the Changeovers in Team Pursuit

2024-03-04T09:30:08+01:00

More and more data is getting collected in sports. Also on the cycling track, a lot of rider data is available to be analyzed, such as timing data from measurement loops, sensor data of the cyclists’ wearables and video data recorded by coaches. During BOSA 2024, the Becoming Outstanding in Sports Analytics winter school in Ghent, our participants were asked to develop a multimodal team pursuit analysis demo that can facilitate the work of the track cycling coaches of Cycling Vlaanderen. The proposed multimodal data analysis give coaches insights into how well the changeover between riders was performed by visualizing the key features of the change: the riding lines of the riders, the duration of the change, and the trends of the power data (which was collected using the WCN Wireless Cycling Network set-up). The video clips, in which the riding lines are visualized, are automatically generated using a change detection method that analyzes the Mylaps measurement loops data. Next, state-of-the-art object detection and tracking methods are used to show each rider’s trajectory. For each changeover, we visualize the results in an interactive dashboard. These visualizations should provide coaches the necessary insights to better coach and improve their athletes.

Aerobars Position Effect: What is the Interaction Between Aerodynamic Drag and Power Production?

2024-03-06T11:47:25+01:00

Extensive research has been dedicated to optimizing the cyclist's position on the bike to enhance aerodynamic performance. This study aims to further investigate the aerobars position modification impact on cycling speed. Drawing from previous work (Fintelman et al. 2015), a connection is established between position adjustments and hip angle, a critical determinant of power output. Based on a 3D scan of an elite athlete on his Time Trial (TT) bike, a digital twin with upper body mobility is created. Utilizing inverse kinematics with aerobars as a root, adjustments to the aerobars position translate into alterations in the cyclist's upper body posture. These changes influence both aerodynamic drag -quantified by Computational Fluid Dynamics method (CFD)- and hip angle, directly affecting the athlete's capacity for power generation. The interplay between aerodynamic efficiency and power output is analyzed, with varying parameters such as speed and slope angle considered to ascertain the optimal aerobar position for individual athletes in a specific cycling context. Results show impactful variations in cycling speed as a function of the aerobars position, the latter having a strong influence on aerodynamic drag and theoretical power production.

Estimation of LT with dynamic transfer function models with commercial HR and power sensor data

2024-03-21T11:40:05+01:00

The anaerobic threshold (LT) serves as a pivotal marker in cycling training but its regular monitoring is hindered by cost and invasiveness. This study explores a modelling approach for LT estimation using heart rate (HR) and power data collected from wearable technology. Twenty-four cyclists underwent incremental tests while wearing various commercial sensors. A discrete-time transfer function method was employed for modelling, with time-variant parameter (TVP) models showing promising accuracy (average error: 4%) in LT estimation. The adaptability of TVP models to capture HR dynamics contributed to their efficacy. This modelling technique offers a potential alternative for routine LT monitoring, leveraging widely used wearable sensors in cycling. Further validation and adaptation to field data are warranted.

Post-exercise ketone supplementation improves endurance performance and mitochondrial adaptations during an 8-week endurance training intervention

2024-03-06T09:50:29+01:00

Abstract: We previously showed that post-exercise ketone supplementation (PEKS) suppresses the development of overtraining symptoms, stimulates muscular adaptations, and improves endurance performance during endurance overload training. However, it is unclear whether PEKS also improves endurance performance and promotes training adaptations during well-balanced training. Therefore, 28 well-trained active males were enrolled in an 8-week fully supervised cycling training intervention. Throughout the training program, participants received post-exercise and before sleep either 25g of the ketone ester (R)-hydroxybutyl (R)-hydroxybutyrate (KE, n = 14), or an isocaloric placebo drink (CON, n = 14). Outcome parameters included exercise performance, along with muscular and cardiac adaptations and were evaluated before (PRE), after week 3 (MID) and 7 (POST), and following a taper week (POST_+1week). The training intervention improved 30-minute time trial performance (TT_30min), absolute and relative whole-body oxygen uptake (VO₂max), peak power output during the VO₂max test (PPO_VO2max), citrate synthase activity, and peak cardiac output (all p < 0.05 for PRE vs. POST). However, TT_30min (CON: 291 ± 27 W vs. KE: 302 ± 28 W, p < 0.001) and PPO_VO2max(CON: 457 ± 43 W vs. KE: 473 ± 41 W, p = 0.091) were 3.5% higher in KE compared to CON at POST. Furthermore, the relative VO₂max showed a greater increase in KE (+12%) compared to CON (+ 6%, Δp < 0.001). Citrate synthase activity was at POST 14% higher in KE (9.37 ± 1.36 mol.h^-1.kg protein^-1) compared to CON (8.21 ± 0.97 mol.h^-1.kg protein^-1, p = 0.035), and OXPHOS complex II muscle protein content increased only significant in KE (+25%, p = 0.032 vs. PRE). In conclusion, these data indicate that PEKS is a potent nutritional strategy to improve endurance performance and mitochondrial adaptations during regular training.

Ultrasound assessment of subcutaneous adipose fat in cyclists of different categories

2024-03-22T09:58:35+01:00

Body composition has a large impact on cycling performance. Successful cyclists aim to maintain body adipose tissue as low as possible. This study seeks to investigate the subcutaneous adipose tissue (SAT) thickness and body fat percentage (BF%) in cyclists of different categories. Thirteen junior cyclists, eighteen U23 cyclists and nineteen professional cyclists underwent B-mode ultrasound assessment of subcutaneous adipose tissue at seven ISAK anatomical sites. Professional riders showed the smallest sum of SAT thickness, ISAK, and BF%, in comparison of the junior and U23 (p< 0.001). The current study provides information of SAT thickness and BF% assessment through ultrasound B-mode in different categories of cyclists.

Validation of Body Rocket on-bike wind-tunnel technology: drag measurement accuracy and aerodynamic gains sensitivity

2024-03-06T11:45:55+01:00

While body aerodynamics plays a major role in cycling performance, athletes can only measure their coefficient of aerodynamic drag (CdA) in wind tunnel sessions, i.e. far from actual racing conditions, or via methods that can infer CdA, but do not actually measure all the components of CdA. We present a novel device (Body Rocket) that, by using the same load cell technology as a wind tunnel, directly measures and displays in real time the drag force due to a rider’s body only. We compare drag force measurements carried out simultaneously on a wind tunnel balance and the BR device. On average, the Body Rocket system agrees within 2.3% with the wind tunnel data, under different wind speed, yaw angles and body positions, and reliably detects aerodynamics gains due to positional/equipment changes. As a byproduct of its design, it also enables monitoring of cycling positions, providing valuable feedback otherwise not available to the athlete.

Effect of lubrication nature on chain drive efficiency

2024-03-21T11:33:33+01:00

Chain drive efficiency has been proved to depend on numerous factors such as power output, pedaling cadence, the number of teeth of the rings or lubrication [1,2]. Indeed, actual chain lubricants rely on different technologies. Oils are widely used because they are easy to apply, protective against corrosion and wear, and efficient for decreasing friction in the chain. However, they tend to attract dust and metal elements from the chain, resulting in a pollution of the lubrication. Recently, many manufacturers have developed wax-based lubricants. Wax-based lubricants can be either solid (ready to be melt) or dissolved in an aqueous solution. As for oils, these lubricants protect the chain against the corrosion as a layer of wax isolates the metal from the elements. Moreover, independent reports have measured high wear resistance [3] and efficiency [4], and a very good contamination resistance. Even though the application is more complicated, wax-based lubricants are therefore a serious alternative to oils for lubricating a cycling chain drive. The aim of this study is to assess the difference of efficiency that exists between top-end lubricants available on the market. Four oils, two liquid wax-based lubricants and two solid wax-based lubricants were compared in a time-trial simulation on a motorised testing rig. Power output (450W), pedaling cadence (100 rpm) gear ratio (60-16) were fixed. Each lubricant was tested twice, each measure for one hour. Torque and angular velocity were measured using torquemeters (T40B, HBM, Germany) between the motor and the chainring (input) and between the cassette and the magnetic brake (output). Mechanical power was therefore calculated, allowing to determine the efficiency of the whole transmission. Results were pooled by typology of lubrication. Differences in efficiency could be explained by the physical state of the lubricants, as well as their chemical composition.

Comparison of indoor and outdoor riding ability

2024-03-06T10:27:33+01:00

Indoor and outdoor environments profoundly influence cycling performance, highlighting the significance of riding ability assessment. Functional Threshold Power (FTP) captures peak performance while comparing indoor and outdoor settings reveals crucial distinctions. Therefore, this study seeks to compare FTP test results obtained from outdoor and laboratory settings, aiming to gain a deeper understanding of whether environmental settings influence cycling performance. Methods: Each participant underwent a 20-minute FTP test both in a laboratory setting and while exerting maximum effort on an outdoor ride. Subsequently, their FTP results were collected and subjected to correlation analysis. Results: The FTP values obtained from indoor and outdoor tests demonstrated moderate to high correlation (r = 0.83). Despite the presence of unavoidable variables that may influence participants' riding performance, these variables could potentially represent real-world riding conditions with higher ecological validity. The outdoor FTP protocol employed in this study may serve as a viable indicator for evaluating outdoor cycling abilities.

Gender Differences in Cycling Cadence and Related Physiological Responses for Amateur Cyclists

2024-03-06T09:45:18+01:00

Abstract: The aim of this study was to investigate the gender differences in pedaling rate and various physiological responses during cycling. Methods: Thirty-eight cyclists in both gender (N=19 for both gender) were recruited. Each participant completed two tests, which were the functional thresholds power (FTP) test, and a multi-cadence cycling test. Result: Male cyclists showed significant higher pedaling power output, VO₂ (L/min) (p<0.05), lower gross efficiency (GE, %)(p<0.05), higher mean power output (watts) (p<0.05) and numerically higher pedaling cadence (rpm)(p=0.068). Both genders showed similar trend of cadence rate vs. GE relationship. Conclusions: Male and female cyclists revealed physiological and mechanical capacity while conducting cycling exercise. At consistent cycling power output, the downward relationship between cadence rate and GE were similar between males and females.