Pedal Cadence Research Articles

A Machine Learning Approach for Predicting Pedaling Force Profile in Cycling

Accurate measurement of pedaling kinetics and kinematics is vital for optimizing rehabilitation, exercise training, and understanding musculoskeletal biomechanics. Pedal reaction force, the main external force in cycling, is essential for musculoskeletal modeling and closely correlates with lower-limb muscle activity and joint reaction forces. However, sensor instrumentation like 3-axis pedal force sensors is costly and requires extensive postprocessing. Recent advancements in machine learning (ML), particularly neural network (NN) models, provide promising solutions for kinetic analyses. In this study, an NN model was developed to predict radial and mediolateral forces, providing a low-cost solution to study pedaling biomechanics with stationary cycling ergometers. Fifteen healthy individuals performed a 2 min pedaling task at two different self-selected (58 ± 5 RPM) and higher (72 ± 7 RPM) cadences. Pedal forces were recorded using a 3-axis force system. The dataset included pedal force, crank angle, cadence, power, and participants’ weight and height. The NN model achieved an inter-subject normalized root mean square error (nRMSE) of 0.15 ± 0.02 and 0.26 ± 0.05 for radial and mediolateral forces at high cadence, respectively, and 0.20 ± 0.04 and 0.22 ± 0.04 at self-selected cadence. The NN model’s low computational time suits real-time pedal force predictions, matching the accuracy of previous ML algorithms for estimating ground reaction forces in gait.

Intensive Aerobic Cycling Is Feasible and Elicits Improvements in Gait Velocity in Individuals With Multiple Sclerosis: A Preliminary Study.

Aerobic exercise (AEx) has many potential benefits; however, it is unknown whether individuals with multiple sclerosis (MS) can attain the optimal intensity and duration to harness its effects. Forced-rate exercise (FE) is a novel paradigm in which the voluntary pedaling rate during cycling is supplemented to achieve a higher exercise intensity. The aim of this pilot trial was to investigate the feasibility and initial efficacy of a 12-week FE or voluntary exercise (VE) cycling intervention for individuals with MS. Twenty-two participants with MS (Expanded Disability Severity Scale [EDSS] 2.0-6.5) were randomly assigned to FE (n = 12) or VE (n = 10), each with twice weekly 45-minute sessions at a prescribed intensity of 60% to 80% of maximum heart rate (HR). Eighteen individuals (FE = 11; VE = 7) completed the intervention, however, adaptations were required in both groups to overcome barriers to cycling. Overall, participants exercised for an average of 42.2 ± 2.3 minutes at an aerobic intensity of 65% ± 7% of maximum HR and a pedaling cadence of 67.3 ± 13.3 RPM. Cycling led to improved treadmill walking speed (0.61 to 0.68 m/sec, P = .010), with somewhat greater improvement with FE compared to VE (increase of 0.09 vs 0.03 m/s, respectively, P = .17) post intervention. Notably, the participant with the highest disability level (EDSS 6.5) tolerated FE but not VE. Aerobic exercise is feasible for individuals with MS, although those with increased disability may require novel paradigms such as FE to achieve targeted intensity. Further trials are warranted to investigate the effects of FE across the MS disability spectrum.

Torque-Cadence Profile and Maximal Dynamic Force in Cyclists: A Novel Approach.

We aimed to determine the feasibility, test-retest reliability and long-term stability of a novel method for assessing the force (torque)-velocity (cadence) profile and maximal dynamic force (MDF) during leg-pedaling using a friction-loaded isoinertial cycle ergometer and a high-precision power-meter device. Fifty-two trained male cyclists completed a progressive loading test up to the one-repetition maximum (1RM) on a cycle ergometer. The MDF was defined as the force attained at the cycle performed with the 1RM-load. To examine the test-retest reliability and long-term stability of torque-cadence values, the progressive test was repeated after 72 h and also after 10 weeks of aerobic and strength training. The participants' MDF averaged 13.4 ± 1.3 N·kg-1, which was attained with an average pedal cadence of 21 ± 3 rpm. Participants' highest power output value was attained with a cadence of 110 ± 16 rpm (52 ± 5% MDF). The relationship between the MDF and cadence proved to be very strong (R2 = 0.978) and independent of the cyclists' MDF (p = 0.66). Cadence values derived from this relationship revealed a very high test-retest repeatability (mean SEM = 4 rpm, 3.3%) and long-term stability (SEM = 3 rpm, 2.3%); despite increases in the MDF following the 10-week period. Our findings support the validity, reliability and long-term stability of this method for the assessment of the torque-cadence profile and MDF in cyclists.

Sensorimotor adaptation of locomotor synergies to gravitational constraint

This study investigates the impact of gravity on lower limb muscle coordination during pedaling. It explores how pedaling behaviors, kinematics, and muscle activation patterns dynamically adapts to changes in gravity and resistance levels. The experiment was conducted in parabolic flights, simulating microgravity, hypergravity (1.8 g), and normogravity conditions. Participants pedaled on an ergometer with varying resistances. The goal was to identify potential changes in muscle synergies and activation strategies under different gravitational contexts. Results indicate that pedaling cadence adjusted naturally in response to both gravity and resistance changes. Cadence increased with higher gravity and decreased with higher resistance levels. Muscular activities were characterized by two synergies representing pull and push phases of pedaling. The timing of synergy activation was influenced by gravity, with a delay in activation observed in microgravity compared to other conditions. Despite these changes, the velocity profile of pedaling remained stable across gravity conditions. The findings strongly suggest that the CNS dynamically manages the shift in body weight by finely tuning muscular coordination, thereby ensuring the maintenance of a stable motor output. Furthermore, electromyography analysis suggest that neuromuscular discharge frequencies were not affected by gravity changes. This implies that the types of muscle fibers recruited during exercise in modified gravity are similar to those used in normogravity. This research has contributed to a better understanding of how the human locomotor system responds to varying gravitational conditions, shedding light on the potential mechanisms underlying astronauts’ gait changes upon returning from space missions.

Closed-loop Functional Electrical Stimulation (FES) – cycling rehabilitation with phase control Fuzzy Logic for fatigue reduction control strategies for stroke patients

Functional Electrical Stimulation (FES) cycling, or FES-Cycling, holds great therapeutic potential for individuals with paralysis, such as those with Spinal Cord Injury (SCI), traumatic brain injury, or stroke, aiming to restore mobility. However, the nonlinear nature of the musculoskeletal system poses a significant challenge in controlling FES-Cycling. To address this, an integrated closed-loop phase angle fuzzy-based system was developed. This system offers real-time control by adjusting stimulation intensity (pulse width) within the range of 50 to 200μs while maintaining a constant frequency of 35Hz, thereby ensuring precise pedaling trajectory and cadence patterns. An experimental study involved three healthy individuals (Cases A, B, and C) and one individual with hemiplegia stroke (Case D). Results showed that the proposed system consistently reduced average angle trajectory errors for Cases A, B, and C, with values of 2.6945, 3.2958, and 2.9922 degrees, respectively. Case D, affected by hemiplegia stroke, faced greater challenges and exhibited a higher error of 3.4562 degrees. Fatigue resistance, evaluated through fatigue indices, showed promising results for Cases A, B, and C with values of 0.10778, 0.06866, and 0.04603, respectively. However, Case D experienced higher fatigue (0.2304) due to the unique challenges of hemiplegia stroke. These findings highlight the effectiveness of the proposed control system in optimizing FES-Cycling, particularly for healthy individuals. For individuals with paralysis, like Case D, further research is needed to adapt the system to their specific conditions and cycling patterns. This system holds the potential for enhancing FES-Cycling as a therapeutic strategy and warrants additional investigation and customization for different patient populations.

An innovative architecture of a three-speed automatic internal shifting hub for regular commuting bicycles: Kinematic analysis and preliminary sizing

Bicycle transmission systems represent a key component in the design of bicycles, as they determine the nature of pedaling effort that riders have to provide. Multi-gear systems enable riders to choose between multiple transmission ratios and are typically divided into external and internal. The present work aims at designing a three-speed automatic internal shifting hub for regular (non-electric) bicycles, starting from an already existing alternative with only two gear ratios (i.e., speeds), which is taken as reference. The complete kinematic design and a preliminary dimensioning are implemented and described in detail. The novelty of the design lays in the number of available gear rations (three), which is an unprecedented result for automatic internal shifting hubs for regular bicycles, as it is unmatched by the models available on the market. The higher number of gear rations increases the number of available combinations of torque and pedaling cadence to achieve a certain velocity, granting more riding flexibility and ultimately enabling easier rides. This is proven through validation by numerical simulation of a driving cycle, which shows that lower and more constant pedaling forces are required when using the novel three-speed automatic internal shifting hub with respect to the two-speed reference model.

Power production strategy during steady-state cycling is cadence dependent

Crank power is produced by extension and flexion of the hip and knee joints during steady-state pedaling below 120 rpm. Despite the pedaling cadence exceeding 120 rpm during track cycling, the power production strategy for lower-limb coordination above 120 rpm is unknown. This study aimed to assess the effects of various pedaling cadences on the power production strategy of lower-limb coordination during steady-state pedaling. Twenty trained collegiate cyclists performed a 30-s steady-state pedaling exercise at 50% of maximal anaerobic power under four different conditions with 90-, 120-, 150- and 180-rpm pedaling cadences. Pedal kinetics and limb kinematics were recorded using a pedal force measurement system and motion capture system, respectively. Positive mechanical work of hip extension significantly decreased with increasing pedaling cadence (P < 0.05). In contrast, the positive mechanical work of the knee joint flexion significantly increased with increasing pedaling cadence (P < 0.05). For contribution to the total mechanical work at 150 or above rpm, the knee joint showed > 70% of the total contribution, whereas the hip joint showed < 40%. Additionally, the positive mechanical work of the hip shifted to negative mechanical work under 180-rpm condition. These results indicate that power production strategy during steady-state pedaling at 180 rpm is different from the general pedaling cadence. Therefore, specific training needs to be conducted at an excessive-high pedaling cadence such as 180 rpm to achieve high performance in track cycling.

Effects of Controlled Supramaximal High-Intensity Interval Training on Cardiorespiratory Fitness and Global Cognitive Function in Older Adults: The Umeå HIT Study-A Randomized Controlled Trial.

This study examined the effects of regulated and controlled supramaximal high-intensity interval training (HIT) adapted for older adults, compared to moderate-intensity training (MIT), on cardiorespiratory fitness; cognitive, cardiovascular, and muscular function; and quality of life. Sixty-eight nonexercising older adults (66-79 years, 44% males) were randomized to 3 months of twice-weekly HIT (20-minute session including 10 × 6-second intervals) or MIT (40-minute session including 3 × 8-minute intervals) on stationary bicycles in an ordinary gym setting. Individualized target intensity was watt controlled with a standardized pedaling cadence and individual adjustment of the resistance load. Primary outcomes were cardiorespiratory fitness (V̇o2peak) and global cognitive function (unit-weighted composite). V̇o2peak increased significantly (mean 1.38 mL/kg/min, 95% CI [0.77, 1.98]), with no between-group difference (mean difference 0.05 [-1.17, 1.25]). Global cognition did not improve (0.02 [-0.05, 0.09]), nor differed between groups (0.11 [-0.03, 0.24]). Significant between-group differences in change were observed for working memory (0.32 [0.01, 0.64]), and maximal isometric knee extensor muscle strength (0.07 N·m/kg [0.003, 0.137]), both in favor of HIT. Irrespective of the group, there was a negative change in episodic memory (-0.15 [-0.28, -0.02]), a positive change in visuospatial ability (0.26 [0.08, 0.44]), and a decrease in systolic (-2.09 mmHg [-3.54, -0.64]) and diastolic (-1.27 mmHg [-2.31, -0.25]) blood pressure. In nonexercising older adults, 3 months of watt-controlled supramaximal HIT improved cardiorespiratory fitness and cardiovascular function to a similar extent as MIT, despite half the training time. In favor of HIT, there was an improvement in muscular function and a potential domain-specific effect on working memory. NCT03765385.

Pedal cadence does not affect muscle damage to eccentric cycling performed at similar mechanical work.

Purpose: This study aimed to investigate muscle damage when performing equal mechanical work of fast and slow pedaling speed by eccentric muscle actions (ECCs) cycling. Methods: Nineteen young men [mean ± standard deviation (SD) age: 21.0 ± 2.2years; height: 172.7 ± 5.9cm; and body mass: 70.2 ± 10.5kg] performed maximal effort of ECCs cycling exercise with fast speed (Fast) and slow speed trials (Slow). First, subjects performed the Fast for 5min by one leg. Second, Slow performed until the total mechanical work was equal to that generated during Fast other one leg. Changes in maximal voluntary isometric contraction (MVC) torque of knee extension, isokinetic pedaling peak torque (IPT), range of motion (ROM), muscle soreness, thigh circumference, muscle echo intensity, and muscle stiffness were assessed before exercise, and immediately after exercise, and 1 and 4days after exercise. Results: Exercise time was observed in the Slow (1422.0 ± 330.0s) longer than Fast (300.0 ± 0.0s). However, a significant difference was not observed in total work (Fast:214.8 ± 42.4J/kg, Slow: 214.3 ± 42.2J/kg). A significant interaction effect was not observed in peak values of MVC torque (Fast:1.7 ± 0.4 Nm/kg, Slow: 1.8 ± 0.5Nm/kg), IPT, muscle soreness (Fast:4.3 ± 1.6cm, Slow: 4.7 ± 2.9cm). In addition, ROM, circumference, muscle thickness, muscle echo intensity, and muscle stiffness also showed no significant interaction. Conclusion: The magnitude of muscle damage is similar for ECCs cycling with equal work regardless of velocity.

A Novel Approach to the Determination of Time- and Fatigue-Dependent Efficiency during Maximal Cycling Sprints.

During maximal cycling sprints, efficiency (η) is determined by the fiber composition of the muscles activated and cadence-dependent power output. To date, due to methodological limitations, it has only been possible to calculate gross efficiency (i.e., the ratio of total mechanical to total metabolic work) in vivo without assessing the impact of cadence and changes during exercise. Eliminating the impact of cadence provides optimal efficiency (ηopt), which can be modeled as a function of time. Here, we explain this concept, demonstrate its calculation, and compare the values obtained to actual data. Furthermore, we hypothesize that the time course of maximal power output (Pmax) reflects time-dependent changes in ηopt. Twelve elite track cyclists performed four maximal sprints (3, 8, 12, 60 s) and a maximal-pedaling test on a cycle ergometer. Crank force and cadence were monitored continuously to determine fatigue-free force-velocity profiles (F/v) and fatigue-induced changes in Pmax. Respiratory gases were measured during and for 30 min post-exercise. Prior to and following each sprint, lactate in capillary blood was determined to calculate net blood lactate accumulation (ΔBLC). Lactic and alactic energy production were estimated from ΔBLC and the fast component of excess post-exercise oxygen consumption. Aerobic energy production was determined from oxygen uptake during exercise. Metabolic power (MP) was derived from total metabolic energy (WTOT). ηopt was calculated as Pmax divided by MP. Temporal changes in Pmax, WTOT, and ηopt were analyzed by non-linear regression. All models showed excellent quality (R2 > 0.982) and allowed accurate recalculation of time-specific power output and gross efficiency (R2 > 0.986). The time-constant for Pmax(t) (τP) was closely correlated with that of ηopt (τη; r = 0.998, p < 0.001). Estimating efficiency using τP for τη led to a 0.88 ± 0.35% error. Although efficiency depends on pedal force and cadence, the latter influence can be eliminated by ηopt(t) using a mono-exponential equation whose time constant can be estimated from Pmax(t).

Effect of Gear Ratio and Cadence on Gross Efficiency and Pedal Force Effectiveness during Multistage Graded Cycling Test Using a Road Racing Bicycle.

Gross efficiency (GE) and the index of pedal force effectiveness (IFE) are important factors that enhance cyclists' performance; however, the effects of changing pedal force (gear ratio) and cadence on these indices while riding on a road racing bicycle are poorly investigated. This study aimed to examine the effect of changing gear ratio or cadence on GE and IFE using a road racing bicycle. Nine male cyclists completed graded submaximal cycling tests (five stages of 4 min submaximal cycling sessions with 1 min passive rest intervals). The work rate of each stage was determined using two principles: changing gear ratio at a fixed cadence and changing cadence at a fixed gear ratio. We determined GE and IFE using respiratory variables and pedal reaction forces, respectively. Increasing the gear ratio improved GE, and was associated with the IFE. Although increasing the cadence slightly improved GE from the initial level, the increased values then mostly maintained. IFE was almost stable even when cadence increased. Moreover, no significant correlation was observed between the changes in GE and IFE accompanied by increasing cadence. Our data indicate that an increasing gear ratio, but not cadence, may affect GE and IFE while riding on a road racing bicycle.

A Novel Functional Electrical Stimulation-Induced Cycling Controller Using Reinforcement Learning to Optimize Online Muscle Activation Pattern

This study introduces a novel controller based on a Reinforcement Learning (RL) algorithm for real-time adaptation of the stimulation pattern during FES-cycling. Core to our approach is the introduction of an RL agent that interacts with the cycling environment and learns through trial and error how to modulate the electrical charge applied to the stimulated muscle groups according to a predefined policy and while tracking a reference cadence. Instead of a static stimulation pattern to be modified by a control law, we hypothesized that a non-stationary baseline set of parameters would better adjust the amount of injected electrical charge to the time-varying characteristics of the musculature. Overground FES-assisted cycling sessions were performed by a subject with spinal cord injury (SCI AIS-A, T8). For tracking a predefined pedaling cadence, two closed-loop control laws were simultaneously used to modulate the pulse intensity of the stimulation channels responsible for evoking the muscle contractions. First, a Proportional-Integral (PI) controller was used to control the current amplitude of the stimulation channels over an initial parameter setting with predefined pulse amplitude, width and fixed frequency parameters. In parallel, an RL algorithm with a decayed-epsilon-greedy strategy was implemented to randomly explore nine different variations of pulse amplitude and width parameters over the same stimulation setting, aiming to adjust the injected electrical charge according to a predefined policy. The performance of this global control strategy was evaluated in two different RL settings and explored in two different cycling scenarios. The participant was able to pedal overground for distances over 3.5 km, and the results evidenced the RL agent learned to modify the stimulation pattern according to the predefined policy and was simultaneously able to track a predefined pedaling cadence. Despite the simplicity of our approach and the existence of more sophisticated RL algorithms, our method can be used to reduce the time needed to define stimulation patterns. Our results suggest interesting research possibilities to be explored in the future to improve cycling performance since more efficient stimulation cost dynamics can be explored and implemented for the agent to learn.

Pedalling Cadence Affects V̇ o2 Kinetics in Severe-Intensity Exercise.

Hill, DW and Vingren, JL. Pedalling cadence affects V̇ o2 kinetics in severe-intensity exercise. J Strength Cond Res 37(6): 1211-1217, 2023-The purpose was to investigate the effects of pedalling cadence on V̇ o2 kinetics in severe-intensity cycling exercise. This question is pertinent to exercise testing, where cadence is an important (and often confounding) variable, and to performance, where V̇ o2 kinetics determines the initial reliance upon anaerobic reserves. Eighteen university students performed tests to exhaustion at 241 ± 31 W, using cadences of 60, 80, and 100 rev·min -1 . V̇ o2 data were fitted to a 2-component model (primary phase + slow component). Responses during the 3 tests were compared using a repeated-measures analysis of variance, with significance at p < 0.05. The mean response time of the primary phase of the V̇ o2 response (time to reach 63% of the response) was progressively smaller (response was faster) at higher cadences (37 ± 4 seconds at 60 rev·min -1 , 32 ± 5 seconds at 80 rev·min -1 , 27 ± 4 seconds at 100 rev·min -1 ), and there was a concomitantly faster heart rate response. In addition, the time delay before the slow component was shorter, the amplitude of the primary phase was greater, and the amplitude of the slow component was smaller at the higher cadence. The results suggest that pedalling cadence itself-and not just the higher metabolic demand associated with higher cadences-may be responsible for differences in temporal characteristics (time delays, time constants) of the primary and slow phases of the V̇ o2 response. Exercise scientists must consider, and coaches might apply, the relationship between V̇ o2 kinetics and pedalling cadence during exercise testing.

On optimal gear shifting in city bicycles

Standard and electric bicycles are expected to become the principal mean of transport for future short-range mobility. Solving the comfort problem is thus becoming more and more urgent, nonetheless it is known to be a hard task, especially because the cyclist is an active agent while pedaling. As far as we are aware, this is the first paper addressing the comfort problem during the gear shifting phase. Under non-restrictive assumptions, an algorithmic solution is developed providing an estimate for the best instant for comfort shifting. This problem is formulated as a local minimum acceleration point seeking. To solve it, the pedaling cadence is estimated from the rear wheel speed, after learning the gear ratios. Experiments performed on a real testing set-up are finally provided to assess the performance of the proposed approach.

The relationship between pedal force application technique and the ability to perform supramaximal pedaling cadences.

This study aimed to examine the relationship between the pedal force application technique under a specific competitive condition and the ability to perform steady-state pedaling at a supramaximal cadence during a special pedaling test. A total of 15 competitive male cyclists and 13 active, healthy men (novice cyclists, hereafter, novices) performed the pedaling technique test. The test imitated a road cycling competition condition (80% VO2 peak and a cadence of 90 rpm). Additionally, they performed a supramaximal cadence test that evaluated the ability to perform steady-state pedaling for an ultra-high cadence (range of 160–220 rpm) of 30 s stably with a 0.1 kgf. For the pedaling technique test, kinetic data were obtained by the pedal-shaped force platform at 1,000 Hz, and the pedaling technique was determined by the index of force effectiveness (IFE). For the supramaximal cadence test, kinematic data were obtained using a motion capture system at 200 Hz. The supramaximal pedaling cadence (Cmax) was determined by measuring exercise time and targeted pedaling cadence. The IFE was 48.0 ± 9.7% in cyclists and 32.0 ± 5.9% in novices. The Cmax was 215.5 ± 8.8 rpm in cyclists and 192.2 ± 13.0 rpm in novices. These values were significantly higher for cyclists than for novices. Cmax was moderately correlated with IFE (r = 0.64). No significant correlation was observed between Cmax and IFE for cyclists only; in contrast, a moderate correlation was observed between these parameters for novices only (r = 0.67). In conclusion, the pedal force application technique under a specific competitive condition is related to the ability to perform steady-state pedaling for supramaximal cadence during the test. Therefore, Cmax may be able to explain pedal force application techniques without the need for expensive devices for novices.

Virtual reality application for real-time pedalling cadence estimation based on hip ROM tracking with inertial sensors: a pilot study

Virtual reality (VR) applications on rehabilitation a home-base exercise experiences have boomed in the last decade. This is mainly because their entertainment capacity creates a sense of immersion in the users, which enhances adherence to their use. In addition, offering body-related visual feedback is a proven approach to the physical training towards a goal. Recent literature showed the exercise of pedalling has the potential to provide a high number of flexion and extension repetitions of the lower limb in reasonable therapeutic time periods to improve muscle activity, strength and balance in elders, but also motor improvements in patients with neurological injuries. The objective of this work is to present a low-cost wireless application in virtual reality (VR) for pedalling exercises. The platform developed consists of a VR headset and an inertial measurement unit (IMU). The VR headset processes the kinematic information of the IMU to estimate the cadence of the pedalling, while the IMU sensor tracks the angle of hip flexion/extension movement of the user. In order to confirm the suitability of this cadence estimation system, our approach is confronted with a cycling platform developed and validated in a previous study. In the present study, we carried out two repeated sessions with 13 subjects at 3 set speeds: slow (30 rpm), medium (60 rpm) and fast (90 rpm). The Spearman’s correlation (PC) between both systems for the 3 speeds and sessions shows high correlation values for low and medium speeds and moderate correlation for high speed. The SEM results for each system show low measurement error (about 1 cycle) for both systems at every target speed, except for the virtual cycling platform at the highest speed (SEM of VCP at 90 rpm = 3.24 cycles). The repeatability analysis based on ICC (3, 1) absolute agreement shows consistency in all measurements for both systems at high speed and also reflects the irregularity in measurements at low and medium speeds, where participants were less stable during testing due to entertainment from the VR system. All in all, it is concluded the validity of the cadence estimation system for pedalling exercises with low intensity. This development allows us to control the virtual environment by adapting the visual stimulus to cycling cadence. The proposed system can generate sensitive inputs to influence the user’s pedalling cadence.

Intra-cycle analysis of muscle vibration during cycling

ABSTRACT Cyclists are exposed for a long period to continuous vibrations. When a muscle is exposed to vibration, its efficiency decreases, the onset of fatigue occurs sooner, and the comfort of the cyclist is reduced. This study characterised the vastus lateralis (VL) soft tissue vibrations for different input frequencies and different pedalling phases. Ten cyclists were recruited to pedal at 55, 70, 85, and 100 rpm on a vibrating cycle ergometer that induced vibrations at frequencies ranging from 14.4 Hz (55 rpm) to 26.3 Hz (100 rpm). The VL vibration amplitude was quantified with a continuous wavelet transform and expressed as a function of the crank angle. The pedalling cycle was split into four phases (downstroke, backstroke, upstroke, and overstroke) to express the mean vibration amplitude and frequency of each phase. Statistical analysis depicted that VL vibration frequency increased with the pedalling cadence and that the VL was exposed to up to 50% more vibration amplitudes during the downstroke phase at a slow cadence. The increase in the pedal vibration frequency, a higher vibration transmission due to greater normal force on the pedal, and strong activation of the VL during the downstroke phase were discussed to explain these results.

Do Adolescents With Insulin Resistance Demonstrate Impaired Heart Rate Recovery From Exercise?

Heart rate recovery (HRR) following maximal aerobic exercise can serve as a noninvasive method of analyzing the risk for cardiovascular diseases. Inability to recover heart rate to pre‐exercise values can indicate parasympathetic nervous system dysfunction. Poor HRR could also be an indicator of early mortality, as decreased ability to recover heart rate is linked to decreases in vagal tone. Insulin resistance (IR) has also been linked to diabetes, obesity, and parasympathic nervous system dysfunction in adults, through an increased ratio of sympathetic to parasympathetic nerve activity. However, it remains unknown if adolescents with IR exhibit similar parasympathetic dysfunction. Therefore, it was hypothesized that increased IR would be associated with decreased HRR in adolescents.Data were collected from adolescents aged 12‐18. Insulin resistance was quantified as HOMA‐IR using fasting glucose and insulin. Subjects underwent maximal aerobic exercise testing on a cycle ergometer pedaling at 60‐70 RPM, starting at 25 W and increasing 25 W every two minutes. The test was terminated when subjects could no longer maintain the pedaling cadence for 5 consecutive seconds. Following cessation of exercise, subjects remained seated without movement for a two‐minute recovery period. Heart rate (HR) was collected via three lead ECG. Data was filtered and resampled to 1 Hz. A linear regression model was applied to the first 30s of HRR data for each subject, with the resulting slope used as the output variable in a subsequent linear regression model with HOMA‐IR as the predictor. Significance was set p&lt;0.05.Subjects were 15 ± 2 years old with a HOMA‐IR 2.08 ± 1.92. The average HRR slope was ‐0.63 ± 0.13 BPM (r=‐0.91). The slope of HRR vs. HOMA‐IR was ‐0.02 ± 0.02 (r=‐0.32, p=0.18). The slope of HRR vs. fasting glucose was ‐0.001 ± 0.003 (r=‐0.07, p=0.8). The slope of HRR vs. fasting insulin was ‐0.008 ± 0.004 (r=‐0.42, p=0.08).Poor HRR has been linked to early mortality, and insulin resistance causes diabetes. However, IR and HRR were not found to have a statistically significant relationship. The relationships between HRR and fasting glucose and insulin levels were also not statistically significant. These data suggest there is no relationship between HRR and IR post exercise in adolescents.

Analysing Cycling Sensors Data Through Ordinal Logistic Regression with Functional Covariates

AbstractWith the emergence of digital sensors in sports, all cyclists can now measure many parameters during their effort, such as speed, slope, altitude, heart rate or pedalling cadence. The present work studies the effect of these parameters on the average developed power, which is the best indicator of cyclist performance. For this, a cumulative logistic model for ordinal response with functional covariate is proposed. This model is shown to outperform competitors on a benchmark study, and its application on cyclist data confirms that pedalling cadence is a key performance indicator. However, maintaining a high cadence during long effort is a typical characteristic of high-level cyclists, which is something on which amateur cyclists can work to increase their performance.

Caveats and Recommendations to Assess the Validity and Reliability of Cycling Power Meters: A Systematic Scoping Review.

A large number of power meters have become commercially available during the last decades to provide power output (PO) measurement. Some of these power meters were evaluated for validity in the literature. This study aimed to perform a review of the available literature on the validity of cycling power meters. PubMed, SPORTDiscus, and Google Scholar have been explored with PRISMA methodology. A total of 74 studies have been extracted for the reviewing process. Validity is a general quality of the measurement determined by the assessment of different metrological properties: Accuracy, sensitivity, repeatability, reproducibility, and robustness. Accuracy was most often studied from the metrological property (74 studies). Reproducibility was the second most studied (40 studies) property. Finally, repeatability, sensitivity, and robustness were considerably less studied with only 7, 5, and 5 studies, respectively. The SRM power meter is the most used as a gold standard in the studies. Moreover, the number of participants was very different among them, from 0 (when using a calibration rig) to 56 participants. The PO tested was up to 1700 W, whereas the pedalling cadence ranged between 40 and 180 rpm, including submaximal and maximal exercises. Other exercise conditions were tested, such as torque, position, temperature, and vibrations. This review provides some caveats and recommendations when testing the validity of a cycling power meter, including all of the metrological properties (accuracy, sensitivity, repeatability, reproducibility, and robustness) and some exercise conditions (PO range, sprint, pedalling cadence, torque, position, participant, temperature, vibration, and field test).