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Cadence, power, and muscle activation in cycle ergometry
Abstract
Based on the resistance-rpm relationship for cycling, which is not unlike the force-velocity relationship of muscle, it is hypothesized that the cadence which requires the minimal muscle activation will be progressively higher as power output increases.
To test this hypothesis, subjects were instrumented with surface electrodes placed over seven muscles that were considered to be important during cycling. Measurements were made while subjects cycled at 100, 200, 300, and 400 W at each cadence: 50, 60, 80, 100, and 120 rpm. These power outputs represented effort which was up to 32% of peak power output for these subjects.
When all seven muscles were averaged together, there was a proportional increase in EMG amplitude each cadence as power increased. A second-order polynomial equation fit the EMG:cadence results very well (r2 = 0.87- 0.996) for each power output. Optimal cadence (cadence with lowest amplitude of EMG for a given power output) increased with increases in power output: 57 +/- 3.1, 70 +/- 3.7, 86 +/- 7.6, and 99 +/- 4.0 rpm for 100, 200, 300, and 400 W, respectively.
The results confirm that the level of muscle activation varies with cadence at a given power output. The minimum EMG amplitude occurs at a progressively higher cadence as power output increases. These results have implications for the sense of effort and preferential use of higher cadences as power output is increased.
... Cyclists typically choose to pedal at a rate, or self-selected cadence (SSC) that is higher than that which minimizes metabolic power (Coast and Welch, 1985;Lucia et al., 2002). In contrast, cyclists tend to choose a SSC that minimizes muscle excitation (measured using electromyography − EMG) across each cycle under submaximal conditions (MacIntosh et al., 2000;Marsh and Martin, 1995;Takaishi et al., 1996;Neptune et al., 1997;Riveros-Matthey et al., 2023). Although this evidence suggests that minimizing muscle excitation might be an important control strategy, the evidence is limited by technical issues such as the potential for EMG crosstalk, cancellation artefact and an inability to capture deep muscles. ...
... We found a clear minimum in the relationship between individual active muscle volumes and cadence for the GMAX, VL, ST, TA and GM muscles (Fig. 3), while the summed muscle active volume clearly captured a curvilinear relationship irrespective of power demands (Fig. 4A). Our results are in line with studies showing that the muscle activation across muscles is minimized at cadences of ~90 rpm (MacIntosh et al., 2000;Takaishi et al., 1996), and that this muscle activation minimum is close to self-selected cadences in both simulated (Neptune and Hull, 1999) and experimental cycling . Muscle activation minimization has been attributed to a nervous system strategy to reduce fatigue, whereas a minimization of summed active muscle volume has been previously referred to as a proxy for energy expenditure. ...
... Our results suggest that minimizing active muscle volume does not necessarily minimize energy during cycling, and therefore active muscle volume may be a poor proxy of energy use during this largely concentric, power generating task. Given the large number of muscles for which active volume was minimized near the selfselected cadence, it is perhaps not surprising that additional weighting for muscle sizes in the current study did not alter the relationship between cadence and summed average active muscle volume compared to previous work (MacIntosh et al., 2000;Takaishi et al., 1996) using muscle activation (EMG-RMS) without considering muscle size. However, further work is required to test the generalizability of the results across different cycling conditions, including those that may deviate from the optimal and other locomotor conditions. ...
... Hansen et al. (2021) claimed self-chosen cadence to depend on the preceding cadence, such as a previous trial. To complicate matters further, both optimal and preferred cadences increase with rising power outputs (Ansley and Cangley 2009;Coast and Welch 1985;MacIntosh et al. 2000). The different cadences, whether self-selected or imposed, present different cycling efficiencies (Ansley and Cangley 2009;Coast and Welch 1985;Driss and Vandewalle 2013;Francescato et al. 1995;Foss and Hallén 2004;MacIntosh et al. 2000), as well as different maximal power outputs (e.g., Beneke and Leithäuser 2017). ...
... To complicate matters further, both optimal and preferred cadences increase with rising power outputs (Ansley and Cangley 2009;Coast and Welch 1985;MacIntosh et al. 2000). The different cadences, whether self-selected or imposed, present different cycling efficiencies (Ansley and Cangley 2009;Coast and Welch 1985;Driss and Vandewalle 2013;Francescato et al. 1995;Foss and Hallén 2004;MacIntosh et al. 2000), as well as different maximal power outputs (e.g., Beneke and Leithäuser 2017). Consequently, non-optimal cadences will always result in lower power outputs, relative to metabolic cost, than could otherwise be produced (see also the distinction between most efficient and most powerful cadences, discussed later under 'Which Optimum?'). ...
... B Calculated internal work (mainly due to leg-mass acceleration-deceleration at increasing cadences) is near zero at the two lowest cadences but grows exponentially greater thereafter Fig. 11 The dropping efficiency of increasing cadence at a fixed power output (235 W), measured at 60, 80, and 100 rpm in 45 cyclists (Sanderson 1991). The drop in efficiency from 80 to 100 rpm is 18.0%, while to the extrapolated 120 and 140 rpm (blue markers) the respective drops are 33.7 and 50.3% and self-selected cadences increase with increasing power outputs (e.g., Ansley and Cangley 2009;Coast and Welch 1985;Dekerle et al. 2003;MacIntosh et al. 2000;Rudsits et al. 2018). The rising cadence makes muscle coordination increasingly more difficult to achieve and is another source of energy loss, particularly so with non-cyclists. ...
The elegant concept of a hyperbolic relationship between power, velocity, or torque and time to exhaustion has rightfully captivated the imagination and inspired extensive research for over half a century. Theoretically, the relationship’s asymptote along the time axis (critical power, velocity, or torque) indicates the exercise intensity that could be maintained for extended durations, or the “heavy–severe exercise boundary”. Much more than a critical mass of the extensive accumulated evidence, however, has persistently shown the determined intensity of critical power and its variants as being too high to maintain for extended periods. The extensive scientific research devoted to the topic has almost exclusively centered around its relationships with various endurance parameters and performances, as well as the identification of procedural problems and how to mitigate them. The prevalent underlying premise has been that the observed discrepancies are mainly due to experimental ‘noise’ and procedural inconsistencies. Consequently, little or no effort has been directed at other perspectives such as trying to elucidate physiological reasons that possibly underly and account for those discrepancies. This review, therefore, will attempt to offer a new such perspective and point out the discrepancies’ likely root causes.
... There is a well-documented link between the rate of force development and muscle activation. During voluntary contractions to a set force, but with an increasing rate of force development, whole muscle activation measured by integrated electromyography (EMG) increases with the increase in force rate (Bigland and Lippold 1954;Sale 1987;MacIntosh et al. 1999;Farina et al. 2004). While some discrepancies on this topic exist (Nelson et al. 1973;Barnes Communicated by Olivier Seynnes. ...
... While some discrepancies on this topic exist (Nelson et al. 1973;Barnes Communicated by Olivier Seynnes. 1980;Komi 1973;MacIntosh et al. 1999), they can mainly be explained by how force or rate was controlled. Accounting for these methodological discrepancies, findings consistently demonstrate that voluntary control of muscle activation must be adjusted to meet the changing mechanical demands of the task. ...
... Therefore, added neural drive during rapid force development is a likely requirement during many daily activities, to compensate for the decline in force-generating capacity induced by even greater fascicle shortening velocities compared to the velocities observed in our experiment. This is supported by the large changes in recruitment threshold with increasing contraction velocities in studies that investigated relatively slow versus very fast movements (Budingen and Freund 1976;Desmedt and Godaux 1977a) as well as by the increases in amplitude of surface EMG recordings, which further suggests additional motor unit recruitment (Bigland and Lippold 1954;Sale 1987;MacIntosh et al. 1999;Farina et al. 2004). ...
When rate of force development is increased, neural drive increases. There is presently no accepted explanation for this effect. We propose and experimentally test the theory that a small increase in rate of force development increases medial gastrocnemius fascicle shortening velocity, reducing the muscle’s force-generating capacity, leading to active motor units being recruited at lower forces and with increased discharge frequencies. Participants produced plantar flexion torques at three different rates of force development (slow: 2% MVC/s, medium: 10% MVC/s, fast: 20% MVC/s). Ultrasound imaging showed that increased rate of force development was related to higher fascicle shortening velocity (0.4 ± 0.2 mm/s, 2.0 ± 0.9 mm/s, 4.1 ± 1.9 mm/s in slow, medium, fast, respectively). In separate experiments, medial gastrocnemius motor unit recruitment thresholds and discharge frequencies were measured using fine-wire electromyography (EMG), together with surface EMG. Recruitment thresholds were lower in the fast (12.8 ± 9.2% MVC) and medium (14.5 ± 9.9% MVC) conditions compared to the slow (18.2 ± 8.9% MVC) condition. The initial discharge frequency was lower in the slow (5.8 ± 3.1 Hz) than the fast (6.7 ± 1.4 Hz), but not than the medium (6.4 ± 2.4 Hz) condition. The surface EMG was greater in the fast (mean RMS: 0.029 ± 0.017 mV) compared to the slow condition (0.019 ± 0.013 mV). We propose that the increase in muscle fascicle shortening velocity reduces the force-generating capacity of the muscle, therefore requiring greater neural drive to generate the same forces.
... The result of the lower cadence during the cognitive task could be explained by the assumption that the mental rotation task might stabilize cadence by serving as a distraction, while our control condition might subjectively be too boring and subsequently lead to increased cadence. While there is a linear relationship between power output and effort measured as heart rate or oxygen uptake (Arts & Kuipers, 1994), there is evidence that this relationship is modulated by pedal cadence (Coast & Welch, 1985;Faria et al., 2005a;MacIntosh et al., 2000). The optimal cadence, i.e. the cadence which produces the lowest effort at a given power output, increases linearly with power output (Coast & Welch, 1985;MacIntosh et al., 2000) but might also be higher for trained cyclists (Faria et al., 2005a). ...
... While there is a linear relationship between power output and effort measured as heart rate or oxygen uptake (Arts & Kuipers, 1994), there is evidence that this relationship is modulated by pedal cadence (Coast & Welch, 1985;Faria et al., 2005a;MacIntosh et al., 2000). The optimal cadence, i.e. the cadence which produces the lowest effort at a given power output, increases linearly with power output (Coast & Welch, 1985;MacIntosh et al., 2000) but might also be higher for trained cyclists (Faria et al., 2005a). Both higher and lower ...
... However, without instruction or sufficient experience, people may be unable to ascertain their optimal pedal cadence and instead choose a higher than optimal cadence. Research from Coast and Welch (1985) and MacIntosh et al. (2000) suggests that cadences of 70 rpm, as adopted on average in our ME condition, become optimal at around 250 W. As 250 W is larger than any power implemented in our experimental conditions, this suggests higher than optimal cadence in both E and ME conditions. Because cadence was even higher in the E condition, one would expect even higher effort, both objectively and subjectively. ...
While the effects of aerobic exercise during a cognitive task on the performance of said cognitive task have been extensively studied, it has not been investigated whether cognitive performance during aerobic exercise influences the physical performance. For this, it is the main goal of the study to investigate the physical and cognitive performance during a simultaneous conduction of aerobic exercise and mental rotation. Forty-one German sport students cycled at 60% intensity while simultaneously performing a mental rotation task. In a within-subject design, both physical and cognitive performances were compared with isolated cycling and mental rotation as control conditions using both objective (heart rate and pedal cadence in the cycling task, reaction time and accuracy in the mental rotation task) and subjective (RPE) cognitive and physical measures. The results analyzed with hierarchical linear modeling revealed no effect of either simultaneous cognitive tasks on objective (heart rate) or subjective (RPE) physical effort, nor of simultaneous exercise on reaction time or accuracy in cognitive performance. However, we have found lower cadence during cognitive tasks, which was also stable in time compared to an increase in cadence during exercise control. Furthermore, our results demonstrated increased cognitive effort during exercise. Our findings suggest that increased effort, both physiological and cognitive, is required during combined physical and cognitive work in support of neurological resource conflicts caused by the differing demands of exercise and executive function.
... These cadence-dependent metabolic differences have been linked to specific muscle fiber activation patterns, particularly the premature recruitment of fast-twitch muscle fibers at higher cadences during lower exercise intensities (Macintosh et al., 2000;Sanderson et al., 2006). These patterns occur due to the distinct biomechanical and metabolic properties of muscle fiber types (I, IIa, IIx). ...
... Additionally, the maximum power of these fibers exceeds that of fast-twitch Type IIa fibers by five times and that of slow-twitch Type I fibers by more than twelve times. These results are consistent with previous (in vitro) observations on the properties of specific fiber types (Hill, 1922;Tesch et al., 1989;Macintosh et al., 2000;Bottinelli et al., 1999;Plomgaard et al., 2006). However, beyond a certain pedaling rate, energy costs for internal work associated with the movement of the lower limbs increase (Francescato FIGURE 5 Optimal pedaling rate as a function of heart rate (A), oxygen uptake (B), blood lactate concentration (C) and metabolic work rate (D). ...
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 (V.O2), 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 (FATmax), maximal lactate steady-state (MLSS) and maximal oxygen uptake (V.O2max), were determined using cadence-specific inverse functions. These data were used to calculate state-specific force-velocity (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, V.O2 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 FATmax, 82.24 ± 2.59 rpm at MLSS, culminating at 84.49 ± 2.66 rpm at V.O2max (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 optimal 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 results 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.
... It has been suggested that perceptive response is a compromise between energetical optimal cadence (i.e., lowest VO 2 ) which appears at relatively low cadences, and neuromuscular optimal cadence (i.e., lowest muscle activation) observed at high cadences (18). Furthermore, optimal cadences tend to increase with power output (19)(20)(21), regardless of the parameters considered. ...
... The present results did not confirm our hypothesis from concentric cycling (16) regarding the effect of power output on optimal cadences. An upward shift in optimal cadence with power in concentric cycling has generally been attributed to the force-velocity properties of muscle fiber types (19) and the proportion of fiber types recruited (43). However, in eccentric cycling, the range of power output available was wider compared to concentric cycling (44); then, it is possible that intensities in the present study were too close to induce a shift through the recruitment of high-threshold motor units. ...
Introduction:
The effect of cadence in eccentric (ECC) cycling on physiological and perceptual responses is, to date, poorly understood. This study aimed to evaluate the impact of cadence during ECC cycling on muscular activation (EMG), oxygen consumption (VO2), and perceived effort (PE) for two different levels of power output.
Methods:
Seventeen participants completed four sessions one week apart: 1) determination of the maximal concentric peak power output (PPO) and familiarization with ECC cycling at five cadences (30, 45, 60, 75, and 90 rpm) ; 2) second familiarization with ECC cycling ; 3) and 4) ECC cycling exercise consisting of 5 min at the five different cadences at either 40 or 60% PPO. PE was reported, and VO2 and EMG of seven muscles were calculated over the exercise's last minute.
Results:
PE, VO2, and global lower limb muscles activation (EMGALL) showed an effect of cadence (P < 0.001) and followed a curvilinear function. Both low and high cadences increased PE and VO2 responses compared to intermediate cadences. While muscle activation of vastus lateralis follows a U-shape curve with cadence, it was greater at low cadence for rectus femoris and biceps femoris, greater at high cadence for tibialis anterior and gastrocnemius medialis, and was not altered for soleus. The estimated optimal cadence was greater (all P < 0.01) for VO2 (64.5 ± 7.9 rpm) than PE (61.7 ± 9.4 rpm) and EMGALL (55.9 ± 9.3 rpm), but power output had no impact on the optimal cadences.
Conclusions:
The physiological and perceptual responses to changes in cadence during eccentric cycling followed a U-shape curve with an optimal cadence depending on the parameter considered.
... Yürüyüş kinetik, kinematik ve temporal verilere sahiptir. Temporal verilerden birisi olan kadans, yürüyüşü kişiye özel hale getiren kimliksel bir parametredir (12). Kadansın ayarlanması mezensefalon veya spinal düzeydeki lokomotor bölgeler tarafından düzenlenmektedir (13). ...
... Fakat diğer veriler karşılaştırıldığında brain ve ark. elde ettiği veriler yüksektir (12). Ata ve ark. ...
Purpose: Cadence is a value that can vary from person to person and is usually calculated as the number of steps per minute. Baropedometer, on the other hand, provides detailed analysis of foot dynamics by measuring the pressure distribution under the foot. In addition to cadence, it is also used in the evaluation and measurement of foot diseases in clinics and studies.
Methods: In our study, using 2014 model Diasu by Sani Corporate's baropedometer device; Separate cadence
values (step/min) were calculated for the right and left feet. Demographic data such as age, weight and height of 101 individuals included in this study were recorded. The averages of the walks were taken into considerationfrom these recorded data. The obtained data were evaluated with Independent Samples Test in SPSS 25.0 package
program.
Result: Male right and left cadence values were 58,07±23,77 steps/min, 58,18±24,67 steps/min, respectively. while in female individuals, these values were 55,87±22,89 steps/min on the right; on the left 56,75±21,52 steps/min. As a result of the statistical analysis, no significant difference was found between cadence and measurement
data (p>0.05).
Conclusion: When the literature is examined, cadence examines the changes in disease and aging alongwith other gait parameters. The insignificance of cadence change in healthy individuals due to demographicinformation made us think that cadence can only change in healthy individuals when they are diagnosed with the disease. Considering the studies stating that the change in cadence depends on walking speed and stride
distance, it was thought that these parameters of gait should also be evaluated in future studies. There are studies in the literature reporting that cadence increases with age. However, no study has been found in the literature that directly correlates sole pressure with cadence. We think that our study will be a guide for other studies that
reveal the factors affecting cadence.
... Increased muscle force at high workloads could be produced by increasing muscle activation magnitude and contraction timing. [9][10][11][12] Interestingly, with the workload increase, VL's activation time decreased, while SO's muscle activation time increased. 13 Assuming that knee joint extensors act mostly concentrically during the crank cycle, increases in workload might determine a need for decreasing the knee extensors' concentric contribution with an increase in the eccentric's contraction time due to its reduced metabolic cost. 2 Also, although plantar flexor bi-articular muscles' (e.g., gastrocnemius) timing of contraction adapted to changes in saddle height, it is not known if this adaptation also occurs with a workload increase. ...
... Increased muscle force at high workloads could be produced by increasing muscle activation magnitude and contraction timing. [9][10][11][12] Interestingly, with the workload increase, VL's activation time decreased, while SO's muscle activation time increased. 13 Assuming that knee joint extensors act mostly concentrically during the crank cycle, increases in workload might determine a need for decreasing the knee extensors' concentric contribution with an increase in the eccentric's contraction time due to its reduced metabolic cost. 2 showing especial benefits from improvements in aerobic power/capacity, exercise tolerance, strength and muscle mass in clinical populations. ...
Background:
The mechanical energy required to drive the cranks during cycling depends on concentric and eccentric muscle actions. However, no study to date provided clear evidence on how workload levels affect concentric and eccentric muscle actions during cycling. Therefore, the aim of this study was to investigate the workload effects on the timing of lower limb concentric and eccentric muscle actions, and on joint power production.
Methods:
Twenty-one cyclists participated in the study. At the first session, maximal power output (POMAX) and power output at the first (POVT1) and second (POVT2) ventilatory thresholds were determined during an incremental cycling test. At the second session, cyclists performed three trials (2-min/each) in the workloads determined from their POMAX, POVT1 and POVT2, acquiring data of lower limb muscle activation, pedal forces and kinematics. Concentric and eccentric timings were computed from muscles' activations and muscle-tendon unit excursions along with hip, knee and ankle joints' power production.
Results:
Longer rectus femoris eccentric activation (62%), vastus medialis concentric (66%) and eccentric activation (26%) and biceps femoris concentric (29%) and eccentric (133%) activation at POMAX were observed compared to POVT1. Longer positive (12%) and shorter negative (12%) power were observed at the knee joint for POMAX compared to POVT1.
Conclusions:
We conclude that, to sustain higher workload levels, cyclists improved the timing of power transmission from the hip to the knee joint via rectus femoris eccentric, vastus medialis concentric and eccentric and biceps femoris concentric and eccentric contractions.
... The most complicated factor to consider may be exercise intensity. Indeed, it is well known that FCC is intensity-dependent [29] and that, for a given percentage of peak oxygen consumption, shifting from one cadence to another affects power output. Conse-quently, the conclusions from studies testing the effect of pedaling cadences based on different intensity criteria (e.g., given power output or oxygen uptake) should be compared with caution [29]. ...
... Indeed, it is well known that FCC is intensity-dependent [29] and that, for a given percentage of peak oxygen consumption, shifting from one cadence to another affects power output. Conse-quently, the conclusions from studies testing the effect of pedaling cadences based on different intensity criteria (e.g., given power output or oxygen uptake) should be compared with caution [29]. Moreover, the cadences considered as low or high are heterogeneous because some investigators chose absolute and other relative (e.g., ± 20% FCC) cadences below and above the preferred one [11,12]. ...
There is a wide range of cadence available to cyclists to produce power, yet they choose to pedal across a narrow one. While neuromuscular alterations during a pedaling bout at non-preferred cadences were previously reviewed, modifications subsequent to one fatiguing session or training intervention have not been focused on. We performed a systematic literature search of Pub-Med and Web of Science up to the end of 2020. Thirteen relevant articles were identified, among which eleven focused on fatigability and two on training intervention. Cadences were mainly defined as "low" and "high" compared with a range of freely chosen cadences for given power output. However, the heterogeneity of selected cadences, neuromuscular assessment methodology, and selected population makes the comparison between the studies complicated. Even though cycling at a high cadence and high intensity impaired more neuromuscular function and performance than low-cadence cycling, it remains unclear if cycling cadence plays a role in the onset of fatigue. Research concerning the effect of training at non-preferred cadences on neuromuscular adaptation allows us to encourage the use of various training stimuli but not to say whether a range of cadences favors subsequent neuromuscular performance.
... For these reasons, the EMG-based cost functions, computed as the sum or weighted sum of the EMG signals of several muscles, have been used to assess the cost of cycling. EMG-based cost functions have been used, for example, to identify the optimal cadence at a given power output [70,71] or the optimal power output at which the standing position should be adopted [44]. By dividing the power-output by the cost-function a measure similar in essence to mechanical efficiency can also be attained [46,71]. ...
... More precisely, it is lower for individuals with a high percentage of slow-twitch fibers [86]. It is also important to note that (1) the cadence that maximizes the crank power output increases with the intensity of the muscle contraction, which is likely due to the orderly recruitment of the motor units [70], and (2) that in terms of energy consumption (i.e., gross efficiency) the optimal cadence is typically lower than 100 RPM (i.e., 60-70 RPM) [86]. The increase in muscle contraction velocity when increasing cadence also reduces the duration of the cycles, so that they reach less than 600 ms above 100 RPM. ...
Featured Application
This review could help researchers, trainers and cyclists to better understand the complex link between classic biomechanical variables and cycling performance. Thus, it could assist professional and amateur cyclists in extracting relevant information from the laboratory assessments and attaining better performances.
Abstract
State-of-the-art biomechanical laboratories provide a range of tools that allow precise measurements of kinematic, kinetic, motor and physiologic characteristics. Force sensors, motion capture devices and electromyographic recording measure the forces exerted at the pedal, saddle, and handlebar and the joint torques created by muscle activity. These techniques make it possible to obtain a detailed biomechanical analysis of cycling movements. However, despite the reasonable accuracy of such measures, cycling performance remains difficult to fully explain. There is an increasing demand by professionals and amateurs for various biomechanical assessment services. Most of the difficulties in understanding the link between biomechanics and performance arise because of the constraints imposed by the bicycle, human physiology and musculo-skeletal system. Recent studies have also pointed out the importance of evaluating not only output parameters, such as power output, but also intrinsic factors, such as the cyclist coordination. In this narrative review, we present various techniques allowing the assessment of a cyclist at a biomechanical level, together with elements of interpretation, and we show that it is not easy to determine whether a certain technique is optimal or not.
... From Eq. (1) it is determined that, for a given power, there would be a series of cadence-pair combinations with which an individual could reach the desired output power. However, it is unlikely that the level of muscle activation will be able to reach the target power with all possible cadence-pair combinations due to the intrinsic muscle force-velocity relationship [8]. The relationship between speed and muscular strength allows establishing the maximum power output conditions of an individual in a pedaling mechanism [9]. ...
... The magnitude of this power is affected by the pedaling rate [28]. The cadence-pair relationship allows predicting the cadence that minimizes muscle activation at a given power output [8]. This relationship, for certain cadences, has a linear behavior [29]. ...
Pedal energy a clean and sustainable alternative. • Energy harvesters allows the self-sourcing of an exercise bicycle. • The main elements of a pedaling energy harvester are identified. • Transmission and transformation of pedal energy to electrical energy are revised. • A sequence to design a pedaling energy harvester is proposed. A R T I C L E I N F O Keywords: Alternative energy Pedal energy Human energy Energy harvesting Transducer Energy transmission A B S T R A C T Pedaling energy is a clean and sustainable energy source capable of supplying power to a variety of low power electronic devices. Furthermore, pedaling energy has proven to be a sustainable energy solution, in combination with other renewable energy sources for developing communities. However, currently, the use of this energy is still limited. The main contribution of this paper is to present a review of static pedaling technologies that use rotary transducers to convert pedaling energy into electrical energy, to identify current advances and design trends, comparing and classifying the elements that integrate the main stages of energy transmission and transformation, identifying areas of opportunity to improve their functionality, efficiency or other aspects of interest. The review includes information about the human capacity to deliver power in a pedaling mechanism such as the cadence-power ratio, cadence-torque, maximum power, and critical power. As a result of the review are reported geometric structure, transducer type, power converter, transmission ratio, power output, among other of the reviewed systems data. Moreover, a design sequence, which is considered appropriate, is proposed to optimize the pedaling energy harvesters of static mechanisms. Finally, the review results, trends, and challenges are discussed.
... Although the exact physiological and biomechanical mechanisms behind mobility enhancements remain unknown, several hypotheses exist. High cadence cycling, characterized by rapid and repetitive lower body movements, is believed to augment muscle activation, sensory feedback, and motor automaticity [42,43]. These enhancements may facilitate smoother transitions in movements required for the TUG test, such as sitting to standing, walking, and turning maneuvers. ...
Background and Purpose: This pilot randomized controlled trial evaluated the effects of 12 sessions of patient-specific adaptive dynamic cycling (PSADC) versus non-adaptive cycling (NA) on motor function and mobility in individuals with Parkinson’s disease (PD), using inertial measurement unit (IMU) sensors for objective assessment. Methods: Twenty-three participants with PD (13 in the PSADC group and 10 in the NA group) completed the study over a 4-week period. Motor function was measured using the Kinesia™ sensors and the MDS-UPDRS Motor III, while mobility was assessed with the TUG test using OPAL IMU sensors. Results: The PSADC group showed significant improvements in MDS-UPDRS Motor III scores (t = 5.165, p < 0.001) and dopamine-sensitive symptoms (t = 4.629, p = 0.001), whereas the NA group did not improve. Both groups showed non-significant improvements in TUG time. IMU sensors provided continuous, quantitative, and unbiased measurements of motor function and mobility, offering a more precise and objective tracking of improvements over time. Conclusions: PSADC demonstrated enhanced treatment effects on PD motor function compared to NA while also reducing variability in individual responses. The integration of IMU sensors was essential for precise monitoring, supporting the potential of a data-driven, individualized exercise approach to optimize treatment outcomes for individuals with PD.
... Based on the observation that cadence corresponding to the minimum metabolic cost increases with rising work rates, the optimal cadence (PRopt) for maximizing power output at equal metabolic costs appears to increase with exercise intensity (Coast & Welch, 1985;Zoladz et al., 2000). This increase is likely due to the recruitment of faster-twitch muscle fibers (Macintosh et al., 2000;Sanderson et al., 2006). However, the systematic pattern of this relationship across submaximal to maximal intensities remains unclear. ...
Background: The relationship between cadence and cycling performance is a critical yet complex aspect of sports science. This study investigates whether training zone programs should be adjusted to different cadences, addressing a gap in current understanding. Previous research has shown that cadence significantly influences metabolic responses across various exercise intensities, affecting blood lactate concentration, cardiac output, and respiratory measures (Michaelis Beneke et al., 2018). Established parabolic functions describe the relationship between metabolic or cardiopulmonary states and cadence at specific work rates (Böning et al.; 1984; Zoldaz et al., 2000), revealing an inverted U-shaped relationship between power and velocity, even at submaximal intensities. Based on the observation that cadence corresponding to the minimum metabolic cost increases with rising work rates, the optimal cadence (PRopt) for maximizing power output at equal metabolic costs appears to increase with exercise intensity (Coast & Welch, 1985; Zoladz et al., 2000). This increase is likely due to the recruitment of faster-twitch muscle fibers (Macintosh et al., 2000; Sanderson et al., 2006). However, the systematic pattern of this relationship across submaximal to maximal intensities remains unclear. By analyzing force-velocity and power-velocity relationships across different metabolic states, this study aims to elucidate the change in optimal cadence with increasing work rate and examine the optimal pedaling rate at characteristic metabolic thresholds. We hypothesize a systematic increase in optimal cadence with rising work intensity, potentially indicating the progressive recruitment of faster-twitch muscle fibers.
... Further, 50 dB Gaussian random noise is added to mimic real measurement. Surface EMG contraction and relaxation patterns during pedaling cycles were specially considered by setting the firing rate range and the maximum contraction period [40], where the firing rate of the steady contraction period is around 8-40 Hz and the firing rate of the maximum contraction period is 70-90 Hz [31]. For different muscles, the pre-defined muscle activation patterns are estimated according to classical pedaling EMG profiles, including the range of activation ranges and the maximum contraction periods [41]. ...
This study examines pedaling asymmetry using the electromyogram (EMG) complexity of six bilateral lower limb muscles for chronic stroke survivors. Fifteen unilateral chronic stroke and twelve healthy participants joined passive and volitional recumbent pedaling tasks using a self-modified stationary bike with a constant speed of 25 revolutions per minute. The fuzzy approximate entropy (fApEn) was adopted in EMG complexity estimation. EMG complexity values of stroke participants during pedaling were smaller than those of healthy participants (p = 0.002). For chronic stroke participants, the complexity of paretic limbs was smaller than that of non-paretic limbs during the passive pedaling task (p = 0.005). Additionally, there was a significant correlation between clinical scores and the paretic EMG complexity during passive pedaling (p = 0.022, p = 0.028), indicating that the paretic EMG complexity during passive movement might serve as an indicator of stroke motor function status. This study suggests that EMG complexity is an appropriate quantitative tool for measuring neuromuscular characteristics in lower limb dynamic movement tasks for chronic stroke survivors.
... In adults, overall muscle activation, as reflected by the surface electromyographic (sEMG) amplitude has been reported to decrease (Barnes 1980;MacIntosh et al. 2000), increase (Aeles et al. 2022), or not change (Farina et al. 2004;Miller et al. 2019a) with increasing contraction rate. Such inconsistencies have also been demonstrated in children, although to a more limited extent Thorstensson 1994, 2000;Gillen et al. 2022). ...
Background
Motor unit (MU) activation during maximal contractions is lower in children compared with adults. Among adults, discrete MU activation differs, depending on the rate of contraction. We investigated the effect of contraction rate on discrete MU activation in boys and men.
Methods
Following a habituation session, 14 boys and 20 men completed two experimental sessions for knee extension and wrist flexion, in random order. Maximal voluntary isometric torque (MVIC) was determined before completing trapezoidal isometric contractions (70%MVIC) at low (10%MVIC/s) and high (35%MVIC/s) contraction rates. Surface electromyography was captured from the vastus lateralis (VL) and flexor carpi radialis (FCR) and decomposed into individual MU action potential (MUAP) trains.
Results
In both groups and muscles, the initial MU firing rate (MUFR) was greater (p < 0.05) at high compared with low contraction rates. The increase in initial MUFR at the fast contraction in the VL was greater in men than boys (p < 0.05). Mean MUFR was significantly lower during fast contractions only in the FCR (p < 0.05). In both groups and muscles, the rate of decay of MUFR with increasing MUAP amplitude was less steep (p < 0.05) during fast compared with slow contractions.
Conclusion
In both groups and muscles, initial MUFRs, as well as MUFRs of large MUs were higher during fast compared with slow contractions. However, in the VL, the increase in initial MUFR was greater in men compared with boys. This suggests that in large muscles, men may rely more on increasing MUFR to generate torque at faster rates compared with boys.
... An intriguing consideration is the alteration in recruitment patterns of muscle fibers with increasing cadences, particularly observed during submaximal intensities [43][44][45]. The increased muscle activity in the lower extremities with higher pedaling frequency suggests a potential shift in fiber recruitment [39,46]. ...
Anaerobic performance diagnostics in athletes relies on accurate measurements of blood lactate concentration and the calculation of blood lactate accumulation resulting from glycolytic processes. In this study, we investigated the impact of pedaling frequency on blood lactate accumulation during 10-second maximal isokinetic cycling sprints. Thirteen trained males completed five 10-second maximal isokinetic cycling sprints on a bicycle ergometer at different pedaling frequencies (90 rpm, 110 rpm, 130 rpm, 150 rpm, 170 rpm) with continuous power and frequency measurement. Capillary blood samples were taken pre-exercise and up to 30 minutes post-exercise to determine the maximum blood lactate concentration.
Blood lactate accumulation was calculated as the difference between maximal post-exercise and pre-start blood lactate concentration. Repeated measurement ANOVA with Bonferroni-adjusted post hoc t-tests revealed significant progressive increases in maximal blood lactate concentration and accumulation with higher pedaling frequencies (p<0.001; η2+>+0.782).
The findings demonstrate a significant influence of pedaling frequency on lactate accumulation, emphasizing its relevance in anaerobic diagnostics. Optimal assessment of maximal lactate formation rate is suggested to require a pedaling frequency of at least 130 rpm or higher, while determining metabolic thresholds using the maximal lactate formation rate may benefit from a slightly lower pedaling frequency.
... Furthermore, cycling overuse injuries can result from excessive mechanical loads on musculoskeletal structures, depending on body position and training load [5][6][7][8]. According to research, cyclists adapt their body positions and muscle activation patterns, as fatigue occurs to maintain performance [9][10][11]. But, the question is whether the pressure asymmetry exists under the ischial tuberosity or the general gluteal area after the cycling exercise at constant intensity. ...
The aim of this study was to compare seat pressure asymmetries before and after 30 min cycling at constant intensity in association with pelvic anthropometric parameters and skeletal muscle fatigue. Twelve male road cyclists aged 18–30 years (mean training experience 9.9 ± 2.5 years) participated. Pelvic anthropometric data and body composition were measured with dual-energy X-ray absorptiometry. Participants performed 30 min cycling at 50% peak power output at constant intensity on a cyclus-2 ergometer. Muscle fatigue during cycling was assessed by surface electromyogram spectral mean power frequency (MPF) for the back, gluteal, and thigh muscles. The pressure mapping system was used to assess sitting symmetry before and after the cycling exercise. At the end of cycling, MPF was decreased (p < 0.05) in the dominant side’s erector spinae muscle and the contralateral gluteal muscle. After the exercise, a significant (p < 0.05) asymmetry in seat pressure was observed under the ischial tuberosity based on the peak pressure right to left ratio, whereas peak pressure decreased under the left ischial tuberosity. After the exercise, the relationship (p < 0.05) between pelvis width and pressure under the ischial tuberosity occurred on the dominant side of the body. In conclusion, an asymmetry was revealed after the constant-load cycling exercise by peak pressure ratio right to left side. Further studies should address the role of seat pressure asymmetries before and after cycling exercises at different intensities and durations.
... Although there is significant inconsistency in the literature regarding preferred and optimal cadence, there is general agreement that cyclists use a comparatively high cadence as they are more efficient [44]. Coast and Welch [45] reported that optimal cadence (minimal oxygen uptake) changes linearly, increasing from just over 40 rpm at 100 W to nearly 80 rpm at 300 W. It is recognized that a given power output can be accomplished at a variety of cadences, so, in effect, there would be a number of cadence-resistance combinations at which an athlete could achieve the target power output [46]. ...
Duathlon consists of two durations of running separated by cycling in a format similar to triathlon. The addition of cycling and the associated loadings on the neuromuscular system can modify spatiotemporal variables in running including trunk motion, which can impact running economy. Changes to trunk motion can be inferred by measuring accelerations of the centre of mass (CoM). However, there is scarce research into trunk dynamics in duathlon. Therefore, the aim of this study was to use an inertial sensor (an accelerometer) to compare acceleration magnitudes of the trunk in the vertical, mediolateral, and anteroposterior directions during a simulated field-based duathlon. Specifically, running performance and magnitudes of trunk acceleration were compared pre and post a cycling load. Ten well-trained duathletes (seven males, three females (mean ± SD; age: 31.1 ± 3.4 years; body mass: 70.9 ± 6.9 kg; body height: 177 ± 5.82 cm; 9.45 ± 1.7 weekly training hours per week; 9.15 ± 5.2 years training experience)) completed a 5 km run performed at a self-selected pace (described as moderate intensity) prior to 20 km of continuous cycling at four varied cadence conditions. This was immediately followed by a 2.5 km run. Mean completion times for the final 2.5 km in running pre-cycling (4.03:05 ± 0.018) compared to the 2.5 km in running post-cycling (4.08:16 ± 0.024) were significantly different. Regarding trunk acceleration, the largest difference was seen in the vertical direction (y axis) as greater magnitudes of acceleration occurred during the initial 1 km of running post-cycling combined with overall significant alterations in acceleration between running pre- and post-cycling (p = 0.0093). The influence of prior cycling on trunk acceleration activity in running likely indicates that greater vertical and mediolateral trunk motion contributes to decremental running performance. In future, further advanced simulation and analysis could be performed in ecologically valid contexts whereby multiple accelerometers might be used to model a more complete set of dynamics.
... However, muscle excitation (measured using electromyography -EMG) measured 28 per cycle has been reported to align approximately with cycling cadence preferences under certain 29 conditions. For example, the average EMG per cycle across different muscles shows a 'U' shaped 30 relationship with cadence at fixed power outputs, and the local minimum shifts between 80 and 31 95rpm as the crank power requirements increase (MacIntosh, Neptune, and Horton 2000;A. P. 32 Marsh and Martin 1995;Takaishi et al. 1996;Neptune, Kautz, and Hull 1997). ...
This study used musculoskeletal modelling to explore the relationship between cycling conditions (power output and cadence) and muscle activation and metabolic power. We hypothesized that the cadence that minimized the simulated average active muscle volume would be higher than that which minimized the simulated metabolic power. We validated the simulation by comparing predicted muscle activation and fascicle velocities from select muscles with experimental records of electromyography and ultrasound images. We found strong correlations for averaged muscle activations and moderate to good correlations for fascicle dynamics. These correlations tended to weaken when analyzed at the individual participant level. Our study revealed a curvilinear relationship between average active muscle volume and cadence, with the minimum active volume being aligned to the self-selected cadence. The simulated metabolic power was consistent with previous results and was minimized at lower cadences than that which minimized active muscle volume across power outputs. Whilst there are some limitations to the musculoskeletal modelling approach, the findings suggest that minimizing active muscle volume may be a more important factor than minimizing metabolic power for self-selected cycling cadence preferences. Further research is warranted to explore the potential of an active muscle volume based objective function for control schemes across a wider range of cycling conditions.
... Experienced unilateral amputee cyclists aim for more symmetrical power delivery, often in exchange for kinematic symmetry [11,15], contradicting the findings in this study. This is owing to better power output symmetry at higher workloads and cadences leading to lower metabolic costs, which affects endurance during the extended practice of cycling [22][23][24][25][26]. Elite amputee cyclists present familiarization with cycling practice and the use of prostheses at competitive levels, and use developed motor strategies and pedaling techniques that enable enhanced power output symmetry [12,14,15,27]. ...
Leg prostheses specially adapted for cycling in patients with transtibial amputation can be advantageous for recreational practice; however, their required features are not fully understood. Therefore, we aimed to evaluate the efficiency of unilateral cycling with a transtibial prosthesis and the characteristics of different attachment positions (middle and tip of the foot) between the prosthetic foot and the pedal. The cycling practice was performed on an ergometer at 40 W and 60 W resistance levels while participants (n = 8) wore custom-made orthoses to simulate prosthesis conditions. Using surface electromyogram, motion tracking, and power meter pedals, biomechanical data were evaluated and compared with data obtained through regular cycling. The results showed that power delivery became more asymmetrical at lower workloads for both orthosis conditions, while hip flexion and muscle activity of the knee extensor muscles in the sound leg increased. While both pedal attachment positions showed altered hip and knee joint angles for the leg wearing the orthosis, the middle of the foot attachment presented more symmetric power delivery. In conclusion, the middle of the foot attachment position presented better symmetry between the intact and amputated limbs during cycling performed for rehabilitation or recreation.
... After VO2 is normalized to HR, the O2pulse becomes a noninvasive proxy of stroke volume, indirectly reflecting myocardial contractility [43,44]. An individually-attained power depends on muscle function and energy metabolism, including oxygen consumption [40,[45][46][47][48][49]. ...
ATPase inhibitory factor 1 is a myokine inhibiting the hydrolytic activity of mitochondrial adenosine triphosphate synthase and ecto-F1-ATPase on the surface of many cells. IF1 affects ATP metabolism in mitochondria and the extracellular space and upregulates glucose uptake in myo-cytes; these processes are essential in physical activity. It is unknown whether the IF1 serum concentration is associated with exercise capacity. This study explored the association between resting IF1 serum concentration and exercise capacity indices in healthy people. IF1 serum concentration was measured in samples collected at rest in 97 healthy amateur cyclists. Exercise capacity was assessed on a bike ergometer at the successive stages of the progressive cardiopulmonary exercise test (CPET). IF1 serum concentration was negatively and significantly correlated with oxygen consumption , oxygen pulse, and load at various CPET stages. A better exercise capacity was associated with lower circulating IF1. IF1 may reflect better cellular/mitochondrial energetic fitness, but there is uncertainty regarding how IF1 is released into the intravascular space. We speculate that lower IF1 concentration may reflect a better cellular/mitochondrial integrity, as this protein is bound more strongly with ATPases in mitochondria and cellular surfaces in people with higher exercise capacity .
... After VO 2 is normalized to HR, the O 2 pulse becomes a noninvasive proxy of stroke volume, indirectly reflecting myocardial contractility [43,44]. An individuallyattained power depends on muscle function and energy metabolism, including oxygen consumption [40,[45][46][47][48][49]. ...
ATPase inhibitory factor 1 is a myokine inhibiting the hydrolytic activity of mitochondrial adenosine triphosphate synthase and ecto-F1-ATPase on the surface of many cells. IF1 affects ATP metabolism in mitochondria and the extracellular space and upregulates glucose uptake in myocytes; these processes are essential in physical activity. It is unknown whether the IF1 serum concentration is associated with exercise capacity. This study explored the association between resting IF1 serum concentration and exercise capacity indices in healthy people. IF1 serum concentration was measured in samples collected at rest in 97 healthy amateur cyclists. Exercise capacity was assessed on a bike ergometer at the successive stages of the progressive cardiopulmonary exercise test (CPET). IF1 serum concentration was negatively and significantly correlated with oxygen consumption, oxygen pulse, and load at various CPET stages. A better exercise capacity was associated with lower circulating IF1. IF1 may reflect better cellular/mitochondrial energetic fitness, but there is uncertainty regarding how IF1 is released into the intravascular space. We speculate that lower IF1 concentration may reflect a better cellular/mitochondrial integrity, as this protein is bound more strongly with ATPases in mitochondria and cellular surfaces in people with higher exercise capacity.
... Relationships between VO 2 (i.e., energy cost) and cycling cadence have been evaluated to determine the lower energy cost at a specific pedal rate (i.e., energetically optimal cadence), demonstrating a range value from 73 to 86 RPM [26,63]. However, the optimal pedaling cadence depends on the level and type of athlete (cyclists have a more efficient pedaling cadence with higher RPM compared to triathletes) [64]. Although the second transition (cycle-to-run) is not part of the current review, and has been debated elsewhere [20], it is worth mentioning that a low cadence during the cycle segment could lead to a lower stride frequency during the subsequent run segment [63]. ...
Triathlon is a multisport composed of swim, cycle, and run segments and two transition periods. The swim-to-cycle transition is considered a critical period for the change in body position and the modifications in physiological (heart rate, VO2, lactate) and biomechanical parameters (cycling power and cadence, swimming stroke rate). Therefore, the aim of this review was to summarize the current evidence regarding the physiological and biomechanical changes and their interlink during the swim-to-cycle transition hinting at practical recommendations for coaches and athletes. The influence of the swim segment on cycle one is more evident for short-distance events. Greater modifications occur in athletes of lower level. The modulation of intensity during the swim segment affects the changes in the physiological parameters (heart rate, blood lactate, core temperature), with a concomitant influence on cycling gross efficiency. However, gross efficiency could be preserved by wearing a wetsuit or by swimming in a drafting position. A higher swim leg frequency during the last meters of the segment induces a higher cadence during the cycle segment. Training should be directed to the maintenance of a swimming intensity around 80–90% of a previous maximal swim test and with the use of a positive pacing strategy. When athletes are intended to train consecutively only swim and cycle segments, for an optimal muscle activation during cycling, triathletes could adopt a lower cadence (about 60–70% of their typical cadence), although an optimal pedaling cadence depends on the level and type of athlete. Future research should be focused on the combined measurements of physiological and biomechanical parameters using an intervention study design to evaluate training adaptations on swim kick rate and their effects on cycling performance. Coaches and athletes could benefit from the understanding of the physiological and biomechanical changes occurring during the swim-to-cycle transition to optimize the overall triathlon performance.
... Moreover, the rider must transfer the necessary force on the pedal to generate enough propulsion to move his bike (Macintosh et al., 2000). In that context, there are currently several studies that have analysed the activation of the muscles of the lower limbs in cycling (Hug & Dorel, 2009;Li, 2004;So et al., 2005) according to different aerodynamic postures (Fintelman et al., 2016), depending on the position adopted on the bicycle (Chapman et al., 2008), during a maximal test (2006), during a 40 km time trial (Bini et al., 2008), or the grip maintained (Duc et al., 2008). ...
Cycling is a sport where cyclists predominantly adopt a sitting posture, with the trunk tilted forward. This posture requires a high volume of training and duration in several intensities of effort. This study aims to: 1) evaluate the behaviour of the thoracic and lumbar spine flexion and sacral inclination in the sagittal plane, the thoracic and lumbar spine flexion in the frontal plane, and the trunk torsion in the transverse plane; 2) compare the activation of the core muscles as the intensity of effort increases during an incremental test in cycling, and 3) identify which core muscle has a greater activation in each intensity zone. The spinal posture and the activation of the eight core muscles were evaluated in twelve competitive cyclists during incremental cycling intensities. Thoracic and lum-bar spine flexion and sacral inclination statistically increased as the intensity of effort increased (Start < VT1 < VT2 < VO2max). A significant increase in muscle activation was observed in all core muscles evaluated as the intensity increased. The rectus abdominis showed statistically significant greater muscle activation than the other core muscles evaluated. In conclusion, as the intensity of effort in cycling increases, cyclists significantly increase the thoracic and lumbar spine flexion, the sacral inclination in the sagittal plane, the thoracic and lumbar spine flexion in the frontal plane, trunk rotation in the transverse plane, as well as the activation of the core muscles.
... The use of a cost function [1,4,5] allows to quantify the movement cost by a single value obtained by substituting the values of several variables in a mathematical expression. Most common cost functions used in the biomechanics of cycling are based on the energy consumption [6][7][8][9], the muscle electrical activity (with electromyography, EMG) [10], the leg joint moments (which bear some relation to the muscular effort) [11][12][13], the negative muscle work [14], neuromuscular fatigue-related quantities [15] and the rating of perceived exertion (RPE) during cycling [16,17]. Seabury [6] and Marsh [7] founded that the oxygen consumption for power outputs less than 200 W is minimized for cadences between 40 and 65 rpm; for power outputs of about 300 W the optimal range for oxygen consumption is between 70 and 80 rpm [15,18]. ...
The article presents the study of the pedalling rates obtained by minimizing a cost function based on a kinetic approach and which can be estimated with more easily achievable experimental data as input than other cost functions. Simulations based on data available in the literature were used to compare the cadences obtained by minimizing well-known joint moment-based cost functions and the proposed cost function. The influence of the power output and of the body mass index on the pedalling rates that minimize the cost function was investigated. Experimental tests performed by four competitive cyclists in the field were used as comparison for the results based on simulations. From simulations emerged that results obtained with the cost function proposed in this work were similar to those based on the absolute average joint moments. We found that the upper limit of the more convenient pedalling rate range decreases linearly with the body mass index, while it increases non-linearly with power output. Furthermore, a polynomial regression of the correlation of the pedalling rate obtained through the method and body mass index and power was found. Experimental results confirmed that the proposed model, finding an approximation of the minimum of muscular effort (not including negative muscular work), is able to estimate the upper limit of an optimal range of cadence. All tested cyclists freely choose to pedal at a cadence under this limit.
... Beyond the fact that our results revealed a significant cerebral involvement during MICT, we also observed that HHb concentration changes might be modulated by increasing intensities (resistance) during cycling. This finding is further strengthened by previous studies demonstrating that higher cadences (MacIntosh et al. 2000) and intensities (Macdonald et al. 2008) during a cycling task are associated with a higher leg muscle activation. Hence, it is reasonable to assume that an increased recruitment of muscle fibers requires higher levels of neural resources in motor-related brain areas not only on a regional but also on a network level . ...
It is well known that endurance exercise modulates the cardiovascular, pulmonary, and musculoskeletal system. However, knowledge about its effects on brain function and structure is rather sparse. Hence, the present study aimed to investigate exercise-dependent adaptations in neurovascular coupling to different intensity levels in motor-related brain regions. Moreover, expertise effects between trained endurance athletes (EA) and active control participants (ACP) during a cycling test were investigated using multi-distance functional near-infrared spectroscopy (fNIRS). Initially, participants performed an incremental cycling test (ICT) to assess peak values of power output (PPO) and cardiorespiratory parameters such as oxygen consumption volume (VO2max) and heart rate (HRmax). In a second session, participants cycled individual intensity levels of 20, 40, and 60% of PPO while measuring cardiorespiratory responses and neurovascular coupling. Our results revealed exercise-induced decreases of deoxygenated hemoglobin (HHb), indicating an increased activation in motor-related brain areas such as primary motor cortex (M1) and premotor cortex (PMC). However, we could not find any differential effects in brain activation between EA and ACP. Future studies should extend this approach using whole-brain configurations and systemic physiological augmented fNIRS measurements, which seems to be of pivotal interest in studies aiming to assess neural activation in a sports-related context.
... This lack of ergogenic effect may be explained because it could be exclusive to athletes with high levels of performance, as there are other studies with poorly trained subjects where there have been no significant differences between caffeine and placebo conditions [46][47][48][49]. More deeply, MacIntosh et al. [50] and Lucia et al. [27] studied this neuromuscular efficiency in cycle ergometry with active healthy subjects and professional elite cyclists, respectively. Both showed that at high power outputs (i.e. ...
Background:
this study examined the effects of caffeine supplementation on anaerobic performance, neuromuscular efficiency and upper and lower extremities fatigue in Olympic-level boxers.
Methods:
Eight male athletes, members of the Spanish National Olympic Team, were enrolled in the study. In a randomized double-blind, placebo-controlled, counterbalanced, crossover design, the athletes completed 2 test sessions after the intake of caffeine (6 mg·kg-1) or placebo. Sessions involved initial measures of lactate, handgrip and countermovement jump (CMJ) performance, followed by a 30-seconds Wingate test, and then final measures of the previous variables. During the sessions, electromiography (EMG) data were recorded on the gluteus maximus, biceps femoris, vastus lateralis, gastrocnemius lateral head and tibialis anterior.
Results:
caffeine enhanced peak power (6.27%, p < 0.01; Effect Size (ES) = 1.26), mean power (5.21%; p < 0.01; ES = 1.29) and reduced the time needed to reach peak power (-9.91%, p < 0.01; ES = 0.58) in the Wingate test, improved jump height in the CMJ (+2.4 cm, p < 0.01), and improved neuromuscular efficiency at peak power in the vastus lateralis (ES = 1.01) and gluteus maximus (ES = 0.89), and mean power in the vastus lateralis (ES = 0.95) and tibialis anterior (ES = 0.83).
Conclusions:
in these Olympic-level boxers, caffeine supplementation improved anaerobic performance without affecting EMG activity and fatigue levels in the lower limbs. Further benefits observed were enhanced neuromuscular efficiency in some muscles and improved reaction speed.
... At the individual muscle level, cadences faster than 120 rpm are related to increased excitation (2,12) and constant burst durations that, coupled with the shorter pedal cycle durations, result in longer duty cycles (2). In some muscles cadences above 120 rpm also lead to preferential recruitment of faster motor unit populations (13,14) and early derecruitment of slower motor unit populations in each excitation burst (15). ...
Purpose:
A key determinant of muscle coordination and maximum power output during cycling is pedalling cadence. During cycling the neuromuscular system may select from numerous solutions that solve the task demands while producing the same result. For more challenging tasks fewer solutions will be available. Changes in the variability of individual muscle excitations (EMG) and multi-muscle coordination, quantified by entropic half-life (EnHL), can reflect the number of solutions available at each system level. We therefore ask whether reduced variability in muscle coordination patterns occur at critical cadences and if they coincide with reduced variability in excitations of individual muscles.
Methods:
Eleven trained cyclists completed an array of cadence-power output conditions. EnHL of EMG intensity recorded from 10 leg muscles and EnHL of principal components describing muscle coordination were calculated. Multivariate adaptive regressive splines were used to determine the relationships between each EnHL and cycling condition or excitation characteristics (duration, duty cycle).
Results:
Muscle coordination became more persistent at cadences up to 120 r.p.m., indicated by increasing EnHL values. Changes in EnHL at the level of the individual muscles differed from the changes in muscle coordination EnHL, with longer EnHLs occurring at the slowest (< 80 r.p.m.) and fastest (>120 r.p.m.) cadences. EnHL of the main power producing muscles however reached a minimum by 80 r.p.m. and did not change across the faster cadences studied.
Conclusions:
Muscle coordination patterns, rather than the contribution of individual muscles, are key to power production at faster cadences in trained cyclists. Reductions in maximum power output at cadences above 120 r.p.m. could be a function of the time available to coordinate orientation and transfer of forces to the pedals.
... For example, swimming velocity decreases, if the stroke rate increases over a certain (optimal) value (Craig & Pendergast, 1979;Garland, Hiobs, & Kleshnev, 2009) and an optimal cadence allows the maximum power outputs in cycling competition (Van Soest & Casius, 2000). During cycling, each power output can be linked to a specific (optimal) cadence, which is characterised by minimal muscle activations (MacIntosh, Neptune, & Horton, 2000). It is however unclear, whether relevant SSC movement-parameters in rowing, such as stroke rate, gearing and drag factor, have to be maximised to obtain maximum power output or if an optimum relation emerges. ...
Each stretch-shortening-cycle (SSC) in elite sports (e.g. jumping, cycling), is characterised by utilising optimal movement-parameters (e.g. muscle shortening velocity), for maximum power (jump height, cycle velocity). It is however unclear if relevant SSC movement-parameters in rowing, such as stroke rate and gearing, have to be maximised to obtain maximum power output or if an optimum relation emerges. Thus, we measured rowing-power (Prow), leg-power (Pleg) and work-per-stroke (WPS) at of varying stroke rates (20–45 spm), gearings (lever-changes 0.87–0.90 m) and drag factors (100–180 Ws³/m³) during rowing. Experienced sub-elite young athletes performed sprint-series on (single scull, n = 69, 20 ± 2 years, 186 ± 7 cm, 84 ± 9 kg) and off the water (rowing-ergometer, n = 30, 19 ± 3 years, 185 ± 11 cm, 77 ± 19 kg). Prow increased with stroke rate for ergometer-test (r = 0.97, p < 0.001) and boat measurement (r = 0.98, p < 0.001) by 2.7%/stroke and 4.4%/stroke, respectively. Interestingly, stroke rate had a high impact on WPS (r = 0.79, p < 0.001) during boat measurement, compared to no (or specifically no high) impact on WPS (r = −0.10, p = 0.166) during ergometer-measurements. Drag factor (ergometer: r = 0.83, p < 0.001) and gearing (boat: r = 0.60, p < 0.001) yielded moderate to high correlations to Prow. These results indicate that no optimum stroke rate, gearing and drag factor exist for maximum power in rowing (sprint-measurement-range). Accordingly, the measurements yielded maximum power for maximum stroke rate, gearing, and drag factor.
... The effect of cadence on cycling performance has been studied extensively with a majority of studies focusing on cycling energetics [1]. A number of studies have also focused on the effect of cadence on cycling technique and coordination [2][3][4]. These studies show that changing cadence leads to numerous technical responses, such as changes in muscle activation and force effectiveness [1,5,6]. ...
Background
The effect of cadence and work rate on the joint specific power production in cycling has previously been studied, but research has primarily focused on cadences above 60 rpm, without examining the effect of low cadence on joint contribution to power.
Purpose
Our purpose was to investigate joint specific power production in recreational and elite cyclists during low- and moderate cycling at a range of different cadences.
Methods
18 male cyclists (30.9 ± 2.7 years with a work rate in watt at lactate threshold of 282.3 ± 9.3 W) performed cycling bouts at seven different pedalling rates and three intensities. Joint specific power was calculated from kinematic measurements and pedal forces using inverse dynamics at a total of 21 different stages.
Results
A main effect of cadence on the relative to the total joint power for hip-, knee- and ankle joint power was found (all p < 0.05). Increasing cadence led to increasing knee joint power and decreasing hip joint power (all p < 0.05), with the exception at low cadence (<60 rpm), where there was no effect of cadence. The elite cyclists had higher relative hip joint power compared to the recreational group (p < 0.05). The hip joint power at moderate intensity with a freely chosen cadence (FCC) was lower than the hip joint power at low intensity with a low cadence (<60 rpm) (p < 0.05).
Conclusion
This study demonstrates that there is an effect of cadence on the hip- and knee joint contribution in cycling, however, the effect only occurs from 60 rpm and upward. It also demonstrates that there is a difference in joint contribution between elite- and recreational cyclists, and provide evidence for the possibility of achieving higher relative hip joint power at low intensity than moderate intensity by altering the cadence.
... Most of the studies used to evaluate GME have been in cycling test, and cycle pedaling mainly involves concentric muscle actions (11). Various factors affect efficiency and fatigue during exercise, including muscle properties (22), the type of muscle contraction, the type of muscle action, and the exercise methodology (maximal vs. submaximal force generation and duration) (26). Studies comparing GME of the cycle ergometer and resistance exercise are needed to sustain such claims. ...
Garnacho-Castaño, MV, Albesa-Albiol, L, Serra-Payá, N, Gomis Bataller, M, Pleguezuelos Cobo, E, Guirao Cano, L, Guodemar-Pérez, J, Carbonell, T, Domínguez, R, and Maté-Muñoz, JL. Oxygen uptake slow component and the efficiency of resistance exercises. J Strength Cond Res XX(X): 000-000, 2018-This study aimed to evaluate oxygen uptake slow component (V[Combining Dot Above]O2sc) and mechanical economy/efficiency in half squat (HS) exercise during constant-load tests conducted at lactate threshold (LT) intensity. Nineteen healthy young men completed 3 HS exercise tests separated by 48-hour rest periods: 1 repetition maximum (1RM), incremental-load HS test to establish the %1RM corresponding to the LT, and constant-load HS test at the LT. During the last test, cardiorespiratory, lactate, and mechanical responses were monitored. Fatigue in the lower limbs was assessed before and after the constant-load test using a countermovement jump test. A slight and sustained increase of the V[Combining Dot Above]O2sc and energy expended (EE) was observed (p < 0.001). In blood lactate, no differences were observed between set 3 to set 21 (p > 0.05). A slight and sustained decrease of half squat efficiency and gross mechanical efficiency (GME) was detected (p < 0.001). Significant inverse correlations were observed between V[Combining Dot Above]O2 and GME (r = -0.93, p < 0.001). Inverse correlations were detected between EE and GME (r = -0.94, p < 0.001). Significant losses were observed in jump height ability and in mean power output (p < 0.001) in response to the constant-load HS test. In conclusion, V[Combining Dot Above]O2sc and EE tended to rise slowly during constant-load HS exercise testing. This slight increase was associated with lowered efficiency throughout constant-load test and a decrease in jump capacity after testing. These findings would allow to elucidate the underlying fatigue mechanisms produced by resistance exercises in a constant-load test at LT intensity.
... Hence, much of our understanding of human and animal movement, and the effects of clinical conditions and interventions, are based on their predictions (MacIntosh et al. 2000;Hutchinson and Garcia 2002;Holzbaur et al. 2005;Hamner et al. 2010;Arnold et al. 2013;Steele et al. 2013;Hutchinson et al. 2015). ...
Biological movement is an inherently dynamic process, characterized by large spatiotemporal variations in force and mechanical energy. Molecular level interactions between the contractile proteins actin and myosin do work, generating forces and transmitting them to the environment via the muscle's and supporting tissues' complex structures. Most existing theories of muscle contraction are derived from observations of muscle performance under simple, tightly controlled, in vitro or in situ conditions. These theories provide predictive power that falls off as we examine the more complicated action and movement regimes seen in biological movement. Our early and heavy focus on actin and myosin interactions have lead us to overlook other interactions and sources of force regulation. It increasingly appears that the structural heterogeneity, and micro-to-macro spatial scales of the force transmission pathways that exist between actin and myosin and the environment, determine muscle performance in ways that manifest most clearly under the dynamic conditions occurring during biological movement. Considering these interactions, along with the dynamics of force transmission tissues, actuators, and environmental physics have enriched our understanding of biological motion and force generation. This symposium brings together diverse investigators to consolidate our understanding of the role of spatial scale and structural heterogeneity role in muscle performance, with the hope of updating frameworks for understanding muscle contraction and predicting muscle performance in biological movement.
... A band-pass Butterworth filter (50-1000 Hz) and a root mean square (RMS) envelope with a window of 20 ms were applied to the EMG signals. The RMS data of each muscle were normalized to the highest peak of the average RMS curve of ten consecutive crank revolutions registered in any of the three workloads [19,20]. The mean normalized EMG RMS over the whole crank cycle was then calculated and averaged over the 10 crank revolutions. ...
The purpose of this study was to describe the effect of increasing workload on individual thigh muscle activation during a 20 minute incremental cycling test. Intramuscular electromyographic signals were recorded from the knee extensors rectus femoris, vastus lateralis, vastus medialis and vastus intermedius and the knee flexors semimembranosus, semitendinosus, and the short and long heads of the biceps femoris during increasing workloads. Mean activation levels were compared over the whole pedaling cycle and the crank angles at which onset and offset of activation and peak activity occurred were identified for each muscle. These data were compared between three workloads. EMG activation level significantly increased (p<0.05) with increasing workload in the rectus femoris, vastus medialis, vastus lateralis, vastus intermedius, biceps femoris long head, semitendinosus and semimembranosus but not in the biceps femoris short head. A significant change in activation timing was found for the rectus femoris, vastus lateralis, vastus medialis and semitendinosus. Of the knee flexors only the short head of the biceps femoris had its peak activity during the upstroke phase at the two highest workloads indicating a unique contribution to knee flexion.
Introduction
The impact of cycling at different cadences on cardiopulmonary exercise test (CPET) measurements is poorly understood. We aimed to investigate whether higher cadences of pedalling led to meaningful changes in physiological endpoints.
Methods
Study participants were recruited from healthy staff members working within three NHS trusts across England. At baseline, all participants completed a CPET at 60 rpm and then subsequently completed CPETs at cadences of 70, 80 and 90 rpm, allocated in a random order. To evaluate the mean differences in CPET measurements across the cadences, we used a one-way repeated measures analysis of variance. We then performed post hoc pairwise comparisons with Tukey correction to account for multiple testing.
Results
Data collection took place between the 19 September 2023 and 9 April 2024. 25 participants had complete data at each cadence. 48% (12 of 25) were female, with a median (IQR) age of 30 years (27-41). There was no significant difference in peak V̇O 2 across the cadences. Maximum achieved work rate was significantly different across the cadences (p=<0.001). The highest wattage was achieved at 60 rpm (221.2 watts±71.4) and lowest at 90 rpm (210.4 watts, ±77.2). End exercise ventilation increased with increasing cadence (p=0.013), with a mean of 97.6 L/min (±28.3) at 60 prm and 107.0 L/min (±33.9) at 90 prm. Breathing reserve decreased with increasing cadence (p=0.009), with a mean of 45.6 L/min (±28.8) at 60 rpm and 35.1 L/min (±23.5) at 90 rpm. There were minimal differences in other CPET parameters.
Conclusion
In a healthy population, higher cycling cadences increased ventilatory demand and reduced maximum work rate. This could have implications for CPETs in the clinical setting, where physiological responses to higher cadences may be more exaggerated.
Background
The lack of a standardized starting cadence for the acceleration phase makes comparing results challenging, in non-elite participants.
Objective
The aim of this study was to determine the impact of different starting cadences on the Wingate Anaerobic Test (WAnT) indices.
Methods
Twenty-four recreationally active males participated in the study. WAnT protocols consisting of different starting cadences of 60 (WAnT 60rpm ), 80 (WAnT 80rpm ), 100 (WAnT 100rpm ), and 120 rpm (WAnT 120rpm ) were randomly applied on different days. Differences between variables were determined using repeated measures ANOVA (LSD) analysis. An alpha value of p < 0.05 was considered significant. The effect size (ES) was calculated using Cohen's d.
Results
WAnT 80rpm trial produced significantly higher peak power output (PPO) in comparison to WAnT 100rpm (WAnT 80rpm vs. WAnT 100rpm = 948 ± 129 W vs. 888 ± 112 W, p = 0.002, ES = 0.50) and WAnT 120rpm (WAnT 80rpm vs. WAnT 120rpm = 948 ± 129 W vs. 878 ± 139 W, p = 0.000, ES = 0.51) trials. The average power output (AvPO) values in the WAnT 60rpm and WAnT 80rpm trials were significantly higher than those in WAnT 100rpm (WAnT 60rpm vs. WAnT 100rpm = 592 ± 76.4 W vs. 574 ± 76.5 W, p = 0.001, ES = 0.23; WAnT 80rpm vs. WAnT 100rpm = 589 ± 83.9 W vs. 574 ± 76.5 W, p = 0.007, ES = 0.17) WAnT 120rpm (WAnT 60rpm vs. WAnT 120rpm = 592 ± 76.4 W vs. 573 ± 85.3 W; p = 0.002, ES = 0.23; WAnT 80rpm vs. WAnT 120rpm = 589 ± 83.9 W vs. 573 ± 85.3 W, p = 0.007, ES = 0.18).
Conclusions
This study suggests that starting the WAnT test when 60 or 80 rpm reached by recreationally active participants during the acceleration phase may be more suitable to achieve higher peak power and average power outputs. This study emphasizes the need to reconsider the standard starting cadence for the WAnT in anaerobically untrained individuals.
This study examined differentiated rating of perceived exertion (RPE), heart rate, and heart-rate variability during light cycle ergometry exercise at two different pedal rates. 30 healthy men (22.6 ± 0.9 yr.) were recruited from a student population and completed a continuous 20-min. cycle ergometry exercise protocol, consisting of a 4-min. warm-up (60 rev./min., 30 Watts), followed by four bouts of 4 min. at different combinations of pedal rate (40 or 80 rev./min.) and power output (40 or 80 Watts). The order of the four combinations was counterbalanced across participants. Heart rate was measured using a polar heart-rate monitor, and parasympathetic balance was assessed through time series analysis of heart-rate variability. Measures were compared using a 2 (pedal rate) × 2 (power output) repeated-measures analysis of variance. RPE was significantly greater (p < .05) at 80 versus 40 rev./min. at 40 W. For both power outputs heart rate was significantly increased, and the high frequency component of heart-rate variability was significandy reduced at 80 compared with 40 rev./min. These findings indicate the RPE was greater at higher than at lower pedalling rates for a light absolute power output which contrasts with previous findings based on use of higher power output. Also, pedal rate had a significant effect on heart rate and heart-rate variability at constant power output.
In this Review, we explore the state of the art of biomechanical models for estimating energy consumption during terrestrial locomotion. We consider different mechanical models that provide a solid framework to understand movement energetics from the perspective of force and work requirements. Whilst such models are highly informative, they lack specificity for predicting absolute metabolic rates across a range of species or variations in movement patterns. Muscles consume energy when they activate to generate tension, as well as when they shorten to generate positive work. Phenomenological muscle models incorporating steady-state parameters have been developed and are able to reproduce how muscle fibre energy consumption changes under different contractile conditions; however, such models are difficult to validate when scaled up to whole muscle. This is, in part, owing to limited availability of data that relate muscle dynamics to energetic rates during contraction of large mammalian muscles. Furthermore, factors including the compliance of tendinous tissue, dynamic shape changes and motor unit recruitment can alter the dynamics of muscle contractile tissue and potentially improve muscle efficiency under some locomotion conditions. Despite the many challenges, energetic cost estimates derived from musculoskeletal models that simulate muscle function required to generate movement have been shown to reasonably predict changes in human metabolic rates under different movement conditions. However, accurate predictions of absolute metabolic rate are still elusive. We suggest that conceptual models may be adapted based on our understanding of muscle energetics to better predict the variance in movement energetics both within and between terrestrial species.
A methodology for determining maximal anaerobic power and optimal pedaling cadence in sprint cyclists is presented, which is a key factor in track cycling performance. The study examines the impact of pedaling cadence on performance and emphasizes the importance of gear ratio selection for sprints. The research involved 10 professional sprint cyclists aged 15–19 years. Participants performed three maximal sprints with increasing resistance on a cycle ergometer equipped
with an electronic braking system and sensors for precise measurement of left and right leg forces and pedaling cadence. This setup enabled the recording of force-cadence and power-cadence relationships. Data analysis was conducted using linear and quadratic regressions. Morphological assessments were conducted, including calculations of fat and muscle mass percentages using anthropometric methods. The study revealed significant interindividual differences in key performance parameters. Maximal power was achieved at an individual-specific optimal cadence, which varied by 20–40 %. The results validate the effectiveness of the proposed methodology for tailoring training processes to individual needs. The power-cadence relationship facilitates the determination of the optimal cadence at which maximal power is attained. The findings underscore that adjusting the gear ratio to achieve the optimal pedaling cadence during sprints enables maximum
performance and optimizes effort distribution during critical moments of track competition. The methodology provides tools for analyzing fatigue and other factors affecting performance. It enables precise evaluation of track cyclists' physical capabilities, optimizes training plans, enhances outcomes, and supports personalized tactical strategies, making it valuable for coaches and researchers in biomechanics and sports physiology.
Unlike walking and running, people do not consistently choose cadences that minimize energy consumption when cycling. Assuming a common objective function for all forms of locomotion, this suggests either that the neural control system relies on indirect sensorimotor cues to energetic cost that are approximately accurate during walking but not cycling, or that an alternative objective function applies that correlates with energy expenditure in walking but not cycling. This study compared how objective functions derived as proxies to 1) energy cost or 2) an avoidance of muscle fatigue predicted self-selected cycling cadences (SSC) at different saddle heights. Saddle height systematically affected SSC, with lower saddles increasing SSC and higher saddles decreasing SSC. Both fatigue-avoidance and energy-expenditure cost functions derived from muscle activation measurements showed minima that closely approximated the SSCs. By contrast, metabolic power derived from VO2 uptake was minimal at cadences well below the SSC across all saddle height variations. The mismatch between the cadence versus muscle activation and the cadence versus metabolic energy relations is likely due to additional energy costs associated with performing mechanical work at higher cadences. The results suggest that the nervous system places greater emphasis on muscle activation than on energy consumption for action selections in cycling.
Objective
One of the main objectives of practicing indoor cardiovascular exercise is to maximize caloric expenditure. This study aimed to compare energy expenditure (EE), oxygen consumption (VO2), and heart rate (HR) recorded in middle-aged adults while exercising on seven different indoor cardiovascular machines at self-selected maximal and submaximal intensity.
Method
Thirty recreational-active adult males (Age: 41.69 ± 4.64) performed 12-min bouts at RPE (Rate of perceived exertion) 17 and maximum intensity (MAX INT) on the following indoor cardio machines: Recumbent bike (r_BIKE), upright bike (u-BIKE), spin bike (s-BIKE), rowing machine (ROW), elliptical trainer (ELLIP), stair climber (STAIR), and treadmill (TMILL). Heart rate (HR) and oxygen consumption (VO2) were measured during exercise, whereas EE (energy expenditure) was calculated indirectly.
Results
Overall, TMILL induced the highest levels of EE, VO2, and HR, followed by STAIR, ELLIP, s_BIKE, u_BIKE, ROW, and r_BIKE. RPE was reliable across exercise modalities (r_BIKE, u-BIKE, s-BIKE, ROW, ELLIP, STAIR, and TMILL) and intensities (RPE 17 and MAX INT) for EE, HR, and VO2 measurements.
Conclusion
To maximize EE while performing indoor cardiovascular exercise for recreational active middle-aged male participants, the TMILL is the best option, followed by the STAIR and the ELLIP. The least recommended options are, respectively, s_BIKE, u_BIKE, ROW, and r_BIKE. Beyond caloric expenditure considerations, promoting exercises that participants genuinely enjoy can enhance adherence, fostering sustained health benefits. Furthermore, RPE is a reliable tool for assessing EE, VO2, and HR across different exercise modalities and intensities.
Dietary nitrate (NO 3 ⁻ ) is a widely used supplement purported to provide beneficial effects during exercise. Most studies to date include predominantly males. Therefore, the present study aimed to investigate if there is a sex-dependent effect of NO 3 ⁻ supplementation on exercise outcomes. We hypothesised that both sexes would exhibit improvements in exercise economy and exercise capacity following NO 3 ⁻ supplementation, but males would benefit to a greater extent. In a double-blind, randomized, crossover study, twelve females (24±4 years) and fourteen males (23±4 years) completed two 4-minute moderate-intensity (MOD) exercise bouts followed by a time-to-exhaustion (TTE) task after following 3-days of NO 3 ⁻ supplementation (BRJ) or NO 3 ⁻ -depleted placebo (PL). Females were tested during the early follicular phase of the menstrual cycle. During MOD exercise, BRJ reduced the steady-state VO 2 by ~5% in males (M: ∆ -87 ± 115 mL.min ⁻¹ ; p < 0.05) but not in females (F: ∆ 6 ± 195 mL.min ⁻¹ ). Similarly, BRJ extended TTE by ~15% in males ( p < 0.05) but not in females. Dietary NO 3 ⁻ supplementation improved exercise economy during moderate-intensity exercise and exercise capacity during severe-intensity TTE in males but not in females. These differences could be related to estrogen levels, antioxidant capacity, nitrate reducing bacteria or a variety of know physiologic differences such as skeletal muscle calcium handling, and/or fiber type. Overall, our data suggests the ergogenic benefits of oral NO 3 ⁻ supplementation found in studies predominantly on male subjects may not be applicable to females.
Whilst people typically chose to locomote in most economical fashion, during bicycling they will, unusually, chose cadences that are higher than metabolically optimal. Empirical measurements of the intrinsic contractile properties of the vastus lateralis (VL) muscle during submaximal cycling suggest that the cadences that people self-selected (SSC) might allow for optimal muscle fascicle shortening velocity for the production of knee extensor muscle power. It remains unclear, however, whether this is consistent across different power outputs where the SSC varies. We examined the effect of cadence and external power requirements on muscle neuromechanics and joint powers during cycling. VL fascicle shortening velocities, muscle activations and joint-specific powers were measured during cycling between 60 and 120rpm (including SSC), while participants produced 10%, 30%, and 50% of peak maximal power. VL shortening velocity increased as cadence increased but was similar across the different power outputs. Although no differences were found in the distribution of joint powers across cadence conditions, the absolute knee joint power increased with increasing crank power output. Muscle fascicle shortening velocities increased in VL at the SSC as pedal power demands increased from submaximal towards maximal cycling. A secondary analysis of muscle activation patterns showed minimized activation of VL and other muscles near the SSC at the 10% and 30% power conditions. Minimization of activation with progressively increasing fascicle shortening velocities at the SSC may be consistent with the theory that the optimum shortening velocity for maximizing power increases with intensity of exercise and recruitment of fast twitch fibers.
Hill, DW and Vingren, JL. Pedalling cadence affects V̇o2 kinetics in severe-intensity exercise. J Strength Cond Res XX(X): 000-000, 2022-The purpose was to investigate the effects of pedalling cadence on V̇o2 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 V̇o2 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. V̇o2 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 V̇o2 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 V̇o2 response. Exercise scientists must consider, and coaches might apply, the relationship between V̇o2 kinetics and pedalling cadence during exercise testing.
PurposeThe combined approach of electromyography (EMG) and mechanomyography (MMG) in cyclic exercise, such as pedaling, is not completely understood. The aim of this study was to investigate the effect of changes in cadence and work rate during pedaling on EMG and displacement MMG (dMMG) of the vastus medialis (VM) measured simultaneously using our developed MMG/EMG simultaneous measurement device.Methods
The primary endpoints were the change in EMG and dMMG for each cadence and load conditions (9 patterns) during pedaling. The study participants were 15 healthy men. EMG and dMMG of the right VM were measured at 1 kHz sampling for 30 s with a cadence of 30, 60, and 90 rpm and a work rate of 30, 60, and 90 W. Total powers were calculated based on the time domain waveforms of EMG and dMMG.ResultsThe effect of increased work rate responded only to EMG (p < 0.001), but with increasing cadence, EMG (increase) and dMMG (decrease) showed a contrasting relationship. Additionally, dMMG and theoretical pedaling torque had a significant strong positive correlation (p < 0.001).Conclusion
The results of this study revealed that the dMMG measured during cyclic exercise with different loads and cadence reflect the mechanical properties and states of net muscle strength during pedaling. Accordingly, the dMMG may be considered as a biological index for representing the transmission mechanical force on the cyclist's pedals, that is, the net muscle strength during pedaling.
1 Whilst people typically chose to locomote in most economical fashion, during cycling on a bicycle 2 they will, unusually, chose cadences that are higher than metabolically optimal. Empirical 3 measurements of the intrinsic contractile properties of the vastus lateralis (VL) muscle during 4 submaximal cycling suggest that the cadences that people prefer (i.e., self-selected cadences: SSC) 5 allow for optimal muscle fascicle shortening velocity for the production of knee extensor muscle 6 power. It remains unclear, however, whether this is consistent across different power outputs 7 where SSC is known to might be affected. We examined the effect of cadence and external power 8 requirements on muscle neuromechanics and joint powers during cycling. VL fascicle shortening 9 velocities, muscle activations and joint-specific powers were measured during cycling between 60 10 and 120rpm (and the SSC), while participants produced 10%, 30%, and 50% of peak maximal 11 power. VL shortening velocity increased as cadence increased but was similar across the different 12 power outputs. Although no differences were found in the distribution of joint powers across 13 cadence conditions, the absolute knee joint power increased with increasing crank power output. 14 Muscle fascicle shortening velocities increase in VL at the SSC as pedal power demands increase 15 from submaximal to maximal cycling. It therefore seems highly unlikely that preferred cadence is 16 primarily driven by the desire to maintain "optimal" muscle fascicle shortening velocities. A 17 secondary analysis of muscle activation patterns revealed that minimizing muscle activation is 18 likely more important when choosing a cadence for given pedal power demand.
The purpose of this study was to determine how tibiofemoral joint compressive forces and knee joint-spanning muscle forces during uphill walking change compared to level walking in patients with total knee arthroplasty (TKA). A musculoskeletal model capable of resolving total (TCF), medial (MCF), and lateral (LCF) tibiofemoral compressive forces was used to determine compressive forces and muscle forces during level and uphill walking on a 10° incline for twenty-five post TKA patients. A 2?2 (slope: level and 10° ? limb: replaced and non-replaced) repeated measures ANOVA was used to detect differences in knee contact forces between slope and limb conditions and their interaction. Peak loading-response TCF, MCF, and LCF were greater during uphill walking than level walking for non-replaced limbs. During uphill walking, peak loading-response TCF was smaller in the replaced limb compared to non-replaced limbs with no change in MCF or LCF. Peak knee extension moment and knee extensor muscle force were smaller in replaced limbs compared to non-replaced limbs during uphill walking. During level walking, replaced and non-replaced limbs experienced rather equal joint loading, however replaced limb experienced reduced joint loading during uphill walking. Differences in joint loading between replaced and non-replaced limbs were not present during level walking, suggesting compensation from the replaced limb during the more difficult task. Uphill walking following TKA promotes more balanced loading of replaced limbs during stance, however these benefits may come at the expense of increased loading on non-replaced limbs.
L'objectif de ce travail a été d'approfondir la connaissance des choix spontanés effectués par les humains dans le but de réaliser des tâches locomotrices simples, avec un focus sur le mouvement de pédalage. L'analyse de la transition spontanée de la position assise vers celle en danseuse en cyclisme a été le thème central de ces travaux. Peu étudiée en comparaison de la transition marche-course, cette transition est pourtant digne d'intérêt du fait des quelques possibilités de contraindre le mouvement de pédalage, et par sa nature abrupte facilitant ainsi la mise en valeur des critères optimisés lors du mouvement. Les analyses cinématiques, par électromyographie de surface, et par méthode de dynamique inverse du corps complet, ainsi que la mesure des efforts exercés en chacun des points d'appui du cycliste sur un ergocycle entièrement instrumenté ont permis l'analyse du pédalage sous un nouvel angle. La combinaison de ces procédés offre de nouvelles perspectives pour comprendre les choix spontanés effectués pour pédaler sous contrainte incrémentale de production de puissance.
Objectives:
The aim of this study was to investigate whether vibration significantly affected the efficiency of off-road cyclists.
Patients and methods:
Eight male mountain cyclists (mean age 21.1±1 years; range, 19 to 22 years) between August 2017 and November 2017 were included. The experimental protocol included four testing sessions with a one-day interval between testing sessions: a familiarization session; performance of submaximal tests; performance of maximal graded exercise test; and a 30-min mountain bike trial performed with vibration or without vibration. Physiological measures including volume of oxygen uptake (VO2), volume of 2), VO2, VCO2, heart rate, respiratory exchange ratio, rating of perceived exertion, and gross efficiency (GE) were compared between the trials performed with vibration or without vibration.
Results:
There was a significant increase in the GE with the addition of intermittent vibration, particularly over the last 15 min of the cycling trial (p<0.05). There were no significant effects of vibration on other parameters.
Conclusion:
This study demonstrates that addition of intermittent vibration may provide positive benefits in improving GE during a 30-min submaximal cycling trial.
Power output is considered one of the best tools to control external loads in cycling, but the relationship between a target power output and the physiological responses may suffer from the effects of road gradient, which is also affected by cyclist specialization. The objective of this study was to determine the effects of cyclist specialization on effort perception and physiological response (heart rate and lactate concentration) while sustaining efforts at similar power output but riding on two different road gradients. Nineteen male competitive road cyclists performed two randomized trials of 10 min at 0% (velodrome) and 10 min at 6% road gradient (field uphill), at an intensity of 10% ±3% below the individual’s functional threshold power. Cadence was kept between 75-80 in both trials and posture remained unchanged during the tests. Heart rate, speed, cadence, power output, blood lactate, and rate of perceived effort were measured for each trial. K-means cluster analyses differentiate uphill (n=10) and flat specialists (n=9) according to lactate responses. Flat specialists presented lower heart rate (p<0.001 and ES=0.2), perceived exertion (p<0.01 and ES=0.7), and blood lactate concentration (p<0.001 and ES=0.7) riding on the flat than uphill. Uphill specialists presented lower perceived exertion (p<0.01 and ES=0.8) and blood lactate concentration (p<0.01 and ES=0.5) riding uphill than on the flat. In conclusion, the combination of cyclist specialization and road gradient affects physiological and effort perception parameters in response to a similar power output demand. These factors deserve attention in training schedules and monitoring performance using power output data.
Im Radsport erfordern vor allem hohe Trittfrequenzen eine hohe kortikale Aktivität. Daher ist dies möglicherweise ein effizienter Stimulus für die Provokation längerfristiger Anpassungen auf zentralnervöser Ebene. In einer Laborstudie konnte gezeigt werden, dass sich bei höheren Trittfrequenzen die zentralnervöse Ermüdung verzögert. Diese Studie überprüft, inwieweit sich diese für die Trainingspraxis wichtige Erkenntnis im Feld replizieren lässt.
Relying on a five-bar linkage model of the lower limb/bicycle system, intersegmental forces and moments are computed over a full crank cycle. Experimental data enabling the solution of intersegmental loads consist of measured crank arm and pedal angles together with the driving pedal force components. Intersegmental loads are computed as a function of pedaling rate while holding the average power over a crank cycle constant. Using an algorithm that avoids redundant equations, stresses are computed in 12 lower limb muscles. Stress computations serve to evaluate a muscle stress-based objective function. The pedaling rate that minimizes the objective function is found to be in the range of 95–100 rpm. In solving for optimal pedaling rate, the muscle stresses are examined over a complete crank cycle. This examination provides insight into the functional roles of individual muscles in cycling.
The purpose of this study was to estimate the differences in neuromuscular fatigue among prolonged pedalling exercises performed at different pedalling rates at a given exercise intensity. The integrated electromyogram (iEMG) slope defined by the changes in iEMG as a function of time during exercise was adopted as the measurement for estimating neuromuscular fatigue. The results of this experiment showed that the relationship between pedalling rate and the means of the iEMG slopes for eight subjects was a quadratic curve and the mean value at 70 rpm [1.56 (SD 0.65) Vmin–1] was significantly smaller (P < 0.01) than that at 50 and 60 rpm [2.25 (SD 0.54), and 2.22 (SD 0.68), respectively]. On the other hand, the mean value of oxygen consumption obtained simultaneously showed a tendency to increase linearly with the increase in pedalling rate, and the values at 70 and 80 rpm were significantly higher than those at 40 and 50 rpm. In conclusion, it was demonstrated that the degree of neuromuscular fatigue estimated by the iEMG changes for five periods of prolonged pedalling exercise at a given exercise intensity was different among the different pedalling rates, and that the pedalling rate at which minimal neuromuscular fatigue was obtained was not coincident with the rate at which the minimal oxygen consumption was obtained, but was coincident with the rate which most subjects preferred. These findings would suggest that the reason why most people prefer a relative higher pedalling rate, even though higher oxygen consumption is required, is closely related to the development of neuromuscular fatigue in the working muscles.
The purpose of this study was to clarify the reason for the difference in the preferred cadence between cyclists and noncyclists.
Male cyclists and noncyclists were evaluated in terms of pedal force, neuromuscular activity for lower extremities, and oxygen consumption among the cadence manipulation (45, 60, 75, 90, and 105 rpm) during pedaling at 150 and 200 W. Noncyclists having the same levels of aerobic and anaerobic capacity as cyclists were chosen from athletes of different sports to avoid any confounding effect from similar kinetic properties of cyclists for lower extremities (i.e., high speed contraction and high repetitions in prolonged exercise) on both pedaling performance and preferred cadence.
The peak pedal force significantly decreased with increasing of cadence in both groups, and the value for noncyclists was significantly higher than that for cyclists at each cadence despite the same power output. The normalized iEMG for vastus lateralis and vastus medialis muscles increased in noncyclists with rising cadence; however, cyclists did not show such a significant increase of the normalized iEMG for the muscles. On the other hand, the normalized iEMG for biceps femoris muscle showed a significant increase in cyclists while there was no increase for noncyclists. Oxygen consumption for cyclists was significantly lower than that for noncyclists at 105 rpm for 150 W work and at 75, 90, and 105 rpm for 200 W work.
We conclude that cyclists have a certain pedaling skill regarding the positive utilization for knee flexors up to the higher cadences, which would contribute to a decrease in peak pedal force and which would alleviate muscle activity for the knee extensors. We speculated that pedaling skills that decrease muscle stress influence the preferred cadence selection, contributing to recruitment of ST muscle fibers with fatigue resistance and high mechanical efficiency despite increased oxygen consumption caused by increased repetitions of leg movements.
To study the effect of growth upon maximal anaerobic power of the upper and lower limbs, the maximal power developed during a cranking force-velocity test was correlated with the height of a vertical jump in different age groups of young swimmers. The youngest swimmers were significantly less powerful than the oldest. Differences in body size partly accounted for the differences in maximal power during cranking exercise (Wmax = 0.31 + 0.048 age; r = 0.526; P less than 0.01; where Wmax was expressed in W.kg BM-1 and age in months; n = 103). The effect of growth upon vertical jump is similar to the effect upon maximal cranking power: the lowest values were similar to those which concerned Wmax.kg-1. There was a very significant correlation between Wmax in cranking (in W.kg-1) and the height of the vertical jump (VJ in cm) (Wmax = 1.15 + 0.145 VJ; r = 0.728; n = 103, P less than 0.01).
The force-velocity relationship on a Monark ergometer and the vertical jump height have been studied in 152 subjects practicing different athletic activities (sprint and endurance running, cycling on track and/or road, soccer, rugby, tennis and hockey) at an average or an elite level. There was an approximately linear relationship between braking force and peak velocity for velocities between 100 and 200 rev.min-1. The highest indices of force P0, velocity V0 and maximal anaerobic power (Wmax) were observed in the power athletes. There was a significant relationship between vertical jump height and Wmax related to body mass.
The mechanical efficiency of mouse fast- and slow-twitch muscle was determined during contractions involving sinusoidal length changes. Measurements were made of muscle length, force production and initial heat output from bundles of muscle fibres in vitro at 31 degrees C. Power output was calculated as the product of the net work output per sinusoidal length cycle and the cycle frequency. The initial mechanical efficiency was defined as power output/(rate of initial heat production+power output). Both power output and rate of initial heat production were averaged over a full cycle of length change. The amplitude of length changes was +/- 5% of muscle length. Stimulus phase and duration were adjusted to maximise net work output at each cycle frequency used. The maximum initial mechanical efficiency of slow-twitch soleus muscle was 0.52 +/- 0.01 (mean +/- 1 S.E.M. N = 4) and occurred at a cycle frequency of 3 Hz. Efficiency was not significantly different from this at cycle frequencies of 1.5-4 Hz, but was significantly lower at cycle frequencies of 0.5 and 1 Hz. The maximum efficiency of fast-twitch extensor digitorum longus muscle was 0.34 +/- 0.03 (N = 4) and was relatively constant (0.32-0.34) over a broad range of frequencies (4-12 Hz). A comparison of these results with those from previous studies of the mechanical efficiency of mammalian muscles indicates that efficiency depends markedly on contraction protocol.
A group of 15 untrained male subjects pedalled on a friction-loaded cycle ergometer as fast as possible for 5-7 s to reach the maximal velocity (vmax) against different braking forces (FB). Power was averaged during a complete crank rotation by adding the power dissipated against FB to the power necessary to accelerate the flywheel. For each sprint, determinations were made of peak power output (Wpeak), power output attained at vmax (Wvmax) calculated as the product of vmax and FB and the work performed to reach vmax expressed in mean power output (Wvmax). The relationships between these parameters and FB were examined. A biopsy taken from the vastus lateralis muscle and tomodensitometric radiographs of both thighs were taken at rest to identify muscle metabolic and morphometric properties. The Wpeak value was similar for all FB. Therefore, the average of values was defined as corrected maximal power (Wmax). This value was 11% higher than the maximal power output uncorrected for the acceleration. Whereas the Wmax determination did not require high loads, the highest Wvmax value (Wmax) was produced when loading was heavy, as evidenced by the Wvmax-FB parabolic relationship. For each subject, the braking force (FB,Wmax) giving Wmax was defined as optimal. The FB,Wmax, equal to 0.844 (SD 0.108) N.kg-1 bodymass, was related to thigh muscle area (r = 0.78, P < 0.05). The maximal velocity (vm,Wmax) reached against this force seemed to be related more to intrinsic fibre properties (% fast twitch b fibre area and adenylate kinase activity). Thus, from the Wmax determination, it is suggested that it should be possible to predict the conditions for optimal exercise on a cycle ergometer.
Based on the spline software of Lyche et al., a subroutine package is presented in which the amount of smoothing on a set of n noisy datapoints is determined from the data by means of the Generalized Cross-Validation (GCV) or predicted Mean-Squared Error (MSE) criteria of Wahba and her collaborators. Following an idea of Hutchinson and de Hoog, an efficient O (m2n) algorithm is used for calculating the criterion functions, where 2m is the order of the spline function. In this fashion, earlier O (n3) approaches based on the singular value decomposition can be avoided.
Five voluntee subjects held isometric handgrip contractions at specific submaximal tensions until the required tension could no longer be maintained. At the start of those contractions, the amplitude of the surface electromyogram (EMG) was linearly related to the tension exerted; the amplitude of the EMG increased linearly throughout these substained contractions by a constant amount--about 30% of the maximum. During sustained contractions, brief, intermittent maximal efforts showed that strength declined linearly at all tensions. At 25% maximal voluntary contraction (MVC), there was a linear fall in the EMG amplitude associated with the brief maximal efforts, but the fall in strength was more rapid than the fall in EMG amplitude. At 70% MVC, there was no fall in the EMG amplitude in response to the brief maximal efforts, while the muscle strength fell linearly.
After review of previous studies, it seemed desirable to investigate further the interrelationships between pedalling rate, power output, and energy expenditure, using bicycle ergometry as a model for recreational bicycling. Three young adult male subjects rode a Monark ergometer at eight pedalling rates (30-120 rev min ) and four power outputs (‘ 0 ’ 81-7. 163-4. and 1961 W) [vdot] o2 determinations were made, and using measured R, gross energy expenditure was derived. When these values were combined with the results of other researchers using similar protocol but different power outputs, it was found that: (I) a ‘ most efficient’ pedalling rate exists for each power output studied: (2) the ( most efficient ) pedalling rate increases with power output from 42 rev min at 40-8 W to 62 rev min at 326-8 W: and (3) the increase in energy expenditure observed when pedalling slower than‘ most efficient’ is more pronounced at high power outputs than at low outputs, while the increase in response to pedalling faster than “lsquo; most efficient’ is less pronounced at high power outputs than at low outputs. Thus, there is appreciable interaction between pedalling rate and power output in achieving the ‘ most efficient ’ rate in bicycle ergometry. The ‘ most efficient’ pedalling rate observed at high power outputs in the present study is considerably lower than that reported for racing cyclists by others. This discrepancy may well be related to the difference in swing weights between the ergomeler' s heavy steel flywheel and crankset, and that of the lightweight wheel and crankset used on racing bicycles.
Electromyographic (EMG) activity of m. rectus femoris muscle was registered from young male and female subjects during maintained isometric knee extension at 60% of maximal voluntary contraction. The following EMG parameters were analyzed for the entire fatigue time: integrated EMG (IEMG), averaged motor unit potential (AMUP) and power spectral density function (PSDF). The results indicated a slight but continuous rise of IEMG during the fatigue period. AMUP showed sensitivity to fatigue with increase in amplitude, rise time, and number of spikes counted. PSDF was also easily affected by fatigue so that the total power density curve was shifted towards lower frequencies with a high frequency decay. The mean power frequency decreased linearily as a function of fatigue time. The findings suggest that in addition to natural recruitment of new motor units the fatigue is characterized by marked reduction in the conduction velocities of action potential along the used muscle fibers.
This study was conducted to determine whether the pedaling frequency of cycling at a constant metabolic cost contributes to the pattern of fiber-type glycogen depletion. On 2 separate days, eight men cycled for 30 min at approximately 85% of individual aerobic capacity at pedaling frequencies of either 50 or 100 rev.min-1. Muscle biopsy samples (vastus lateralis) were taken immediately prior to and after exercise. Individual fibers were classified as type I (slow twitch), or type II (fast twitch), using a myosin adenosine triphosphatase stain, and their glycogen content immediately prior to and after exercise quantified via microphotometry of periodic acid-Schiff stain. The 30-min exercise bout resulted in a 46% decrease in the mean optical density (D) of type I fibers during the 50 rev.min-1 condition [0.52 (0.07) to 0.28 (0.04) D units; mean (SEM)] which was not different (P > 0.05) from the 35% decrease during the 100 rev.min-1 condition [0.48 (0.04) to 0.31 (0.05) D units]. In contrast, the mean D in type II fibers decreased 49% during the 50 rev.min-1 condition [0.53 (0.06) to 0.27 (0.04) units]. This decrease was greater (P < 0.05) than the 33% decrease observed in the 100 rev.min-1 condition [0.48 (0.04) to 0.32 (0.06) units). In conclusion, cycling at the same metabolic cost at 50 rather than 100 rev.min-1 results in greater type II fiber glycogen depletion. This is attributed to the increased muscle force required to meet the higher resistance per cycle at the lower pedal frequency.(ABSTRACT TRUNCATED AT 250 WORDS)
We determined that the variability in the oxygen cost and thus the caloric expenditure of cycling at a given work rate (i.e., cycling economy) observed among highly endurance-trained cyclists (N = 19; mean +/- SE; VO2max, 4.9 +/- 0.1 l.min-1; body weight, 71 +/- 1 kg) is related to differences in their % Type I muscle fibers. The percentage of Type I and II muscle fibers was determined from biopsies of the vastus lateralis muscle that were histochemically stained for ATPase activity. When cycling a Monark ergometer at 80 RPM at work rates eliciting 52 +/- 1, 61 +/- 1, and 71 +/- 1% VO2max, efficiency was determined from the caloric expenditure responses (VO2 and RER using open circuit spirometry) to steady-state exercise. Gross efficiency (GE) was calculated as the ratio of work accomplished.min-1 to caloric expenditure.min-1, whereas delta efficiency (DE) was calculated as the slope of this relationship between approximately 50 and 70% VO2max. The % Type I fibers ranged from 32 to 76%, and DE when cycling ranged from 18.3 to 25.6% in these subjects. The % Type I fibers was positively correlated with both DE (r = 0.85; P less than 0.001; N = 19) and GE (r = 0.75; P less than 0.001; N = 19) during cycling. Additionally, % Type I fibers was positively correlated with GE (r = 0.74; P less than 0.001; N = 13) measured during the novel task of two-legged knee extension; performed at a velocity of 177 +/- 6 degrees.s-1 and intensity of 50 and 70% of peak VO2 for that activity.(ABSTRACT TRUNCATED AT 250 WORDS)
The aim of the study was to quantify the activity as recorded by electromyography during ergometer cycling in eleven different muscles of the lower extremity. Eleven healthy subjects rode in twelve different ways at different work-load, pedalling rate, saddle height and pedal foot position. Vastus medialis and lateralis, gastrocnemius medialis and lateralis and the soleus muscle were the most activated muscles. Changes in muscle activity during different calibrations were studied in eight of the eleven muscles. An increase in work-load significantly increased the mean maximum activity in all the eight muscles investigated. An increase of the pedalling rate increased the activity in the gluteus maximus, gluteus medius, vastus medialis, medial hamstring, gastrocnemius medialis and soleus muscles. An increase of the saddle height increased the muscle activity in the gluteus medius, medial hamstring and gastrocnemius medialis muscles. Use of a posterior pedal foot position increased the activity in the gluteus medius and rectus femoris muscles, and decreased the activity in the soleus muscle.
This experiment was designed to estimate the optimum pedal rates at various power outputs on the cycle ergometer. Five trained bicycle racers performed five progressive maximal tests on the ergometer. Each rode at pedal rates of 40, 60, 80, 100, and 120 rev X min-1. Oxygen uptake and heart rate were determined from each test and plotted against pedal rate for power outputs of 100, 150, 200, 250, and 300 W. Both VO2 and heart rate differed significantly among pedal rates at equivalent power outputs, the variation following a parabolic curve. The low point in the curve was taken as the optimal pedal rate; i.e., the pedal rate which elicited the lowest heart rate or VO2 for a given power output. When the optimum was plotted against power output the variation was linear. These results indicate that an optimum pedal rate exists in this group of cyclists. This optimum pedal rate increases with power output, and when our study is compared to studies in which elite racers, or non-racers were used, the optimum seems to increase with the skill of the rider.
Moving average electromyography (MA) of quadriceps muscle bellies has been recorded during bicycling at different rates (30-70 cycles/min) or forces (1-3 kg). For power increments (50-100%) achieved by increasing force at constant rate, MA during pedal downstroke always increased. For similar power increments achieved by increasing the rate at constant force, MA did not increase (37% of cases), increased less (37%), or increased similarly (26%). Investigations by others on the rat suggest that the lack of increase of MA despite power increment was not compensated by other muscle activity; hence it indicates a shift from slow to fast fibers, which provide greater power per unit stimulus. Smaller increase of MA with increasing rate rather than force at isopower could depend on this shift or on muscle properties, if operating on ascending limb of power-velocity curve. This, however, does not seem the case for slow fibers, which should develop peak power at about 25 cycles/min. Hence, fibers of quadriceps muscle of humans seem selectively activated according to movement speed, as previously found in inspiratory muscles of rabbits.
A cycle ergometer has been designed to measure the force exerted on the pedal cranks during maximum effort at a variety of constant velocities. Preset crank velocities of 13-166 rpm are established by a controlled 3-hp motor and cannot be overcome by the subject. Torque is measured by strain gauges bonded to the crank shafts; peak torque, peak power, work, and average power are derived for each pedal cycle. Studies in 30 healthy male subjects established reproducibility and normal standards. During exercise for 45 s at a constant velocity of 60 rpm, there was a wide intersubject variation in both maximal torque (118-226 N . m) and the percentage decline in torque (27.2-52.0%). The decline in torque was inversely related to maximal O2 intake (r = 0.84). During short (10-s) periods of exercise at six crank velocities between 60-160 rpm, a linear inverse relationship between maximal peak torque and pedal crank velocity was observed. The peak torque-velocity relationship and the percentage decline in peak torque during 30 s exercise at 60, 100, and 140 rpm were reproducible within a given subject, the coefficient of variation was less than 10%.
This investigation was undertaken to determine the effect of pedal frequency on submaximal exercise responses. Seven well-trained competitive cyclists were studied riding their road-racing bicycles on a motor-driven treadmill at 80% of maximum O2 consumption (VO2 max) using different gear ratios. Cyclists were also studied during a series of unloaded trials to assess the effects of varying rates of limb movements independent of external work load. Heart rate (HR) increased, whereas net HR (after subtracting the HR during unloaded cycling) decreased with increasing pedal frequency during loaded cycling. Expiratory flow (VE), O2 consumption (VO2), blood lactate, net VO2 (after subtracting the VO2 of unloaded cycling), and net VE (after subtracting the VE during unloaded cycling) were quadratically related to pedal frequency. The quadratic relationships evident after corrections were made for the additional work needed to move the legs more frequently may be explained at the lower pedaling rates by a less uniform pattern of blood flow caused by increasing the force requirement per pedal stroke and, at the higher pedal frequencies, by the recruitment of additional musculature to stabilize the trunk. The average of preferred frequency for the group, which was also the most economical pedaling rate judged by most of the variables was 91 rpm, although the preferred pedaling rate for each subject ranged from 72 to 102 rpm.
In nine male volunteers, the endurance time for sustained isometric exercise (right-angle elbow flexion) and dynamic exercise (continuous concentric and eccentric elbow flexions) was measured at different contraction levels. Intermittent isometric exercises were also performed by four of the subjects in whom surface electromyographic elbow flexor recordings were obtained during the three types of exercise. A rapid decrease of the endurance time was seen at contraction levels above 15-20% of the maximum voluntary contraction for both the sustained isometric and dynamic exercise. There were no significant difference between the regression of the endurance time vs. the contraction level for the sustained isometric exercise and that of the dynamic exercise. However, the endurance time was enhanced in the intermittent isometric exercise compared with the sustained isometric exercise. The development of muscle fatigue was well correlated to change of the myoelectric rootmean-square amplitude and the mean power frequency. Differences in exercise did not significantly affect the relation between the time constant of the mean power frequency decrease and the endurance time.
Male cyclists (N = 8) and noncyclists (N = 8) pedaled under six randomly ordered cadences (50, 65, 80, 95, 110 rpm and the preferred cadence) at 200 W to test the hypothesis that electromyographic activity of selected lower limb muscles is minimized at the preferred cadence. Average preferred cadences for cyclists (85.2 +/- 9.2 rpm) and noncyclists (91.6 +/- 10.5 rpm) were not statistically different. Only gastrocnemius EMG was affected substantially and systematically by cadence changes, increasing linearly with cadence increases. Rectus femoris and vastus lateralis EMG displayed significant quadratic and linear relationships with cadence, respectively, but EMG differences between cadences were small for both muscles. Noncyclists did not exhibit significantly different patterns of muscle activity from cyclists, although there was a trend for soleus and gastrocnemius EMG to be higher in noncyclists. The results did not support our hypothesis that lower extremity muscle activation is minimized at an individual's preferred pedaling cadence. Thus, preferred cadence selection does not appear to be related to minimization of muscle activation. Given the nonlinear relationships between muscle mechanical properties, force, and EMG it is unlikely that a simple relationship exists between EMG and muscle stress.
In human locomotion the ability to generate and sustain power output is of fundamental importance. This review examines the implications for power output of having variability in the metabolic and contractile properties within the population of muscle fibres which comprise the major locomotory muscles. Reference is made to studies using an isokinetic cycle ergometer by which the global power/velocity relationship for the leg extensor muscles can be determined. The data from these studies are examined in the light of the force velocity characteristics of human type I and type II muscle fibres. The 'plasticity' of fibre properties is discussed with reference to the 'acute' changes elicited by exercise induced fatigue and changes in muscle temperature and 'chronic' changes occurring following intensive training and ageing.
The purpose of this study was to compare 1) the preferred cadences and 2) the aerobic demand response to cadence manipulation of highly fit, experienced cyclists and equally fit noncyclists. Eight cyclists (C) and eight non-cyclists (NC) pedaled at 200 W under six randomly ordered cadence conditions (50, 65, 80, 95, 110 rpm and preferred cadence) on a Velodyne trainer. The VO2 responses of C and NC to cadence manipulation were similar. Both groups displayed lower VO2 values at lower cadences. VO2 differences between C and NC across cadences were not significant. Mean preferred pedaling cadence surprisingly was somewhat higher for NC (91.6 +/- 10.5 rpm) than C (85.2 +/- 9.2 rpm), but the difference was not significant. The most economical cadence was significantly lower for C (56.1 +/- 6.9 rpm) than NC (62.9 +/- 4.7 rpm). Thus, cycling experience did not substantially influence preferred cadence nor economy during moderate intensity cycling by highly fit athletes. We speculate that preferred cadence and economy similarities between C and NC are associated with similarities in the dynamic muscular training of the groups.
1. In this study, the efficiency of energy conversion in skeletal muscles from the mouse was determined before and after a series of contractions that produced a moderate level of fatigue. 2. Initial mechanical efficiency was defined as the ratio of mechanical power output to the rate of initial enthalpy output. The rate of initial enthalpy output was the sum of the power output and rate of initial heat output. Heat output was measured using a thermopile with high temporal resolution. 3. Experiments were performed in vitro (25 degrees C) using bundles of fibres from fast-twitch extensor digitorum longus (EDL) and slow-twitch soleus muscles from mice. Muscles were fatigued using a series of thirty isometric tetani. Initial mechanical efficiency was determined before and again immediately after the fatigue protocol using a series of isovelocity contractions at shortening velocities between 0 and the maximum shortening velocity (Vmax). Efficiency was determined over the second half of the shortening at each velocity. 4. The fatigue protocol significantly reduced maximum isometric force Vmax, maximum power output and flattened the force-velocity curve. The magnitude of these effects was greater in EDL muscle than soleus muscle. In unfatigued muscle, the maximum mechanical efficiency was 0.333 for EDL muscles and 0.425 for soleus muscles. In both muscle types, the fatiguing contractions caused maximum efficiency to decrease. The magnitude of the decrease was 15% of the pre-fatigue value in EDL and 9% in soleus. 5. In a separate series of experiments, the effect of the fatigue protocol on the partitioning of energy expenditure between crossbridge and non-crossbridge sources was determined. Data from these experiments enabled the efficiency of energy conversion by the crossbridges to be estimated. It was concluded that the decrease in initial mechanical efficiency reflected a decrease in the efficiency of energy conversion by the crossbridges.
A simulation based on a forward dynamical musculoskeletal model was computed from an optimal control algorithm to understand uni- and bi-articular muscle coordination of maximum-speed startup pedaling. The muscle excitations, pedal reaction forces, and crank and pedal kinematics of the simulation agreed with measurements from subjects. Over the crank cycle, uniarticular hip and knee extensor muscles provide 55% of the propulsive energy, even though 27% of the amount they produce in the downstroke is absorbed in the upstroke. Only 44% of the energy produced by these muscles during downstroke is delivered to the crank directly. The other 56% is delivered to the limb segments, and then transferred to the crank by the ankle plantarflexors. The plantarflexors, especially soleus, also prevent knee hyperextension, by slowing the knee extension being produced during downstroke by the other muscles, including hamstrings. Hamstrings and rectus femoris make smooth pedaling possible by propelling the crank through the stroke transitions. Other simulations showed that pedaling can be performed well by partitioning all the muscles in a leg into two pairs of phase-controlled alternating functional groups, with each group also alternating with its contralateral counterpart. In this scheme, the uniarticular hip/knee extensor muscles (one group) are excited during downstroke, and the uniarticular hip/knee flexor muscles (the alternating group) during upstroke. The ankle dorsiflexor and rectus femoris muscles (one group of the other pair) are excited near the transition from upstroke to downstroke, and the ankle plantarflexors and hamstrings muscles (the alternating group) during the downstroke to upstroke transition. We conclude that these alternating functional muscle groups might represent a centrally generated primitive for not only pedaling but also other locomotor tasks as well.
The purpose of the study was to develop an equation to predict the oxygen cost of cycle ergometry. Forty subjects performed an incremental cycle ergometer test on three occasions at 50, 70, or 90 rpm in a counterbalanced order. Work rate was incremented every 5 or 6 min when steady rate values were achieved. To ensure accurate work rates, ergometer resistance was calibrated and flywheel revolutions were electronically measured. Oxygen consumption was measured with a computer interfaced system which provided results every minute. Oxygen consumption (mL.min-1) was the dependent variable, and independent variables were work rate (WR in kgm.min-1), pedal rate (rpm), weight (Kg), and gender (males, 0; females, 1). The following nonlinear equation was selected; VO2 = 0.42.WR1.2 + 0.00061.rpm3 + 6.35.Wt + 0.1136.RPM50.WR-0.10144.RPM90-WR-52-Gender, R2 = 0.9961, Sy.x = 106 mL.min-1, where RPM50: 50 rpm = 1, and RPM90: 90 rpm = 1, else = 0. It was concluded that the oxygen cost of cycle ergometry is nonlinearly related to work rate and pedal rate, linearly related to weight, and that females use less oxygen for a particular work rate.
There are minimal scientific data describing international caliber off-road cyclists (mountain bikers), particularly as they compare physiologically with international caliber road cyclists. Elite female (N = 10) and male (N = 10) athletes representing the United States National Off-Road Bicycle Association (NORBA) Cross-Country Team were compared with elite female (N = 10) and male (N = 10) athletes representing the United States Cycling Federation (USCF) National Road Team. Submaximal and maximal exercise responses were evaluated during the "championship" phase of the training year when athletes were in peak condition. All physiological tests were conducted at 1860 m. Among the female athletes, physiological responses at lactate threshold (LT) and during maximal exercise (MAX) were similar between NORBA and USCF cyclists with two exceptions: 1) USCF cyclists demonstrated a significantly greater (P < 0.05) absolute (16%) and relative (10%) maximal aerobic power, and 2) MAX heart rate was significantly higher (P < 0.05) for the USCF athletes (6%). Among the male athletes, physiological responses at LT and MAX were similar between NORBA and USCF cyclists with two exceptions: 1) USCF cyclists produced significantly greater (P < 0.05) absolute (18%) and relative (16%) power at LT, and 2) USCF cyclists produced significantly greater (P < 0.05) absolute (12%) and relative (10%) power at MAX. These data suggest that, in general, elite off-road cyclists possess physiological profiles that are similar to elite road cyclists.
To determine the effects of cycling experience, fitness level, and power output on preferred and most economical cycling cadences: 1) the preferred cadence (PC) of 12 male cyclists, 10 male runners, and 10 less-trained male noncyclists was determined at 75, 100, 150, 200, and 250 W for cyclists and runners and 75, 100, 125, 150, and 175 W for the less-trained group; and 2) steady-state aerobic demand was determined at six cadences (50, 65, 80, 95, 110 rpm and PC) at 100, 150, and 200 W for cyclists and runners and 75, 100, and 150 W for less-trained subjects. Cyclists and runners (VO2max: 70.7 +/- 4.1 and 72.5 +/- 2.2 mL.kg-1.min-1, respectively) maintained PC between 90 and 100 rpm at all power outputs and both groups selected similar cadences at each power output. In contrast, the less-trained group (VO2max = 44.2 +/- 2.8 mL.kg-1.min-1) selected lower cadences at all common power outputs and reduced cadence from approximately 80 rpm at 75 W to 65 rpm at 175 W. The preferred cadences of all groups were significantly higher than their respective most economical cadences at all power outputs. Changes in power output had little effect on the most economical cadence, which was between 53.3 and 59.9 rpm, in all groups. It was concluded that cycling experience and minimization of aerobic demand are not critical determinants of PC in well-trained individuals. It was speculated that less-trained noncyclists, who cycled at a higher percentage of VO2max, may have selected lower PC to reduce aerobic demand.
A cycle ergometer was modified to measure power (P) with resistance provided solely by the moment of inertia (I) of the flywheel. P was calculated as the product of I, angular velocity (omega), and angular acceleration (alpha). Flywheel omega and alpha were determined by means of an optical sensor and a micro-controller based computer interface which measured time (+/- 1 microsecond) and allowed P to be calculated instantaneously (PI) every 3 degrees of pedal crank rotation or averaged over one complete revolution of the pedal cranks (PREV). Values for maximum P were identified from each bout (PI max and PREV max). Mechanical calibration of torque via a resistive strap proved this method to be both valid and accurate. Thirteen active male subjects performed four bouts of maximal acceleration lasting approximately 3-4 s with 2 min resting recovery. The mean coefficient of variation for PREV max was 3.3 +/- 0.6% and the intraclass correlation was 0.99. PREV max averaged 1317 +/- 66 W at 122 +/- 2 rpm, and PI max averaged 2137 +/- 101 W at 131 +/- 2 rpm. PREV max and PI max were highly correlated (r = 0.86 and r = 0.80 respectively, P < 0.002) with estimated lean thigh volume. Therefore, the inertial-load method provides a valid and reliable determination of cycling power in one short exercise bout.
To further understand lower extremity neuromuscular coordination in cycling, the objectives of this study were to examine the effect of pedaling rate on coordination strategies and interpret any apparent changes. These objectives were achieved by collecting electromyography (EMG) data of eight lower extremity muscles and crank angle data from ten subjects at 250 W across pedaling rates ranging from 45 to 120 RPM. To examine the effect of pedaling rate on coordination, EMG burst onset and offset and integrated EMG (iEMG) were computed. In addition, a phase-controlled functional group (PCFG) analysis was performed to interpret observed changes in the EMG patterns in the context of muscle function. Results showed that the EMG onset and offset systematically advanced as pedaling rate increased except for the soleus which shifted later in the crank cycle. The iEMG results revealed that muscles responded differently to increased pedaling rate. The gastrocnemius, hamstring muscles and vastus medialis systematically increased muscle activity as pedaling rate increased. The gluteus maximus and soleus had significant quadratic trends with minimum values at 90 RPM, while the tibialis anterior and rectus femoris showed no significant association with pedaling rate. The PCFG analysis showed that the primary function of each lower extremity muscle remained the same at all pedaling rates. The PCFG analysis, which accounts for muscle activation dynamics, revealed that the earlier onset of muscle excitation produced muscle activity in the same region of the crank cycle. Also, while most of the muscles were excited for a single functional phase, the soleus and rectus femoris were excited during two functional phases. The soleus was classified as an extensor-bottom transition muscle, while the rectus femoris was classified as a top transition-extensor muscle. Further, the relative emphasis of each function appeared to shift as pedaling rate was increased, although each muscle remained bifunctional.
The purpose of this study was to determine whether mean power output in 30 seconds was greater in a paced effort test or an all-out effort under optimal loading conditions. Nine male athletes volunteered to participate. All testing was done on a Monark cycle ergometer with continuous measurement of velocity and resistance. Power output was calculated (Resistance x Velocity) and corrected for acceleration of the flywheel. For each subject, optimal resistance for peak power output was determined with 5 brief (7-second) tests. Subsequently, 3 all-out 30-second tests using 80, 90 and 100% of this estimated optimal resistance, then 3 paced effort 30-second tests were completed on separate days. Pacing was accomplished with velocity feedback at 80, 100 or 120% of optimal velocity calculated from the all-out tests. Subjects were encouraged to try to exceed the target velocity if possible during the final 10 seconds of the paced effort test. The best all-out test (772 +/- 35 W) was not different (paired t test, p = 0.31) from the best paced effort test (787 +/- 27 W). Furthermore, there was no significant difference between mean power output in the all-out tests at 90% (736 +/- 28 W) and 100% (766 +/- 36 W) of estimated optimal resistance for peak power output (1.16 +/- 0.05 N x kg[-1]), but mean power at 80% of the estimated optimal resistance was lower (722 +/- 31 W; ANOVA for repeated measures, p < 0.05). In conclusion, a paced effort test does not permit greater mean power output over 30 seconds than an all-out test, and there is considerable latitude in apparent optimal resistance for mean power output in a 30-second test.
The purpose of this study was to determine whether the maximum shortening velocity (Vmax) in Hill's mechanical model (A. V. Hill. Proc. R. Soc. London Ser. B. 126: 136-195, 1938) should be scaled with activation, measured as a fraction of the maximum isometric force (Fmax). By using the quick-release method, force-velocity (F-V) relationships of the wrist flexors were gathered at five different activation levels (20-100% of maximum at intervals of 20%) from four subjects. The F-V data at different activation levels can be fitted remarkably well with Hill's characteristic equation. In general, the shortening velocity decreases with activation. With the assumption of nonlinear relationships between Hill constants and activation level, a scaled Vmax model was developed. When the F-V curves for submaximal activation were forced to converge at the Vmax obtained with maximum activation (constant Vmax model), there were drastic changes in the shape of the curves. The differences in Vmax values generated by the scaled and constant Vmax models were statistically significant. These results suggest that, when a Hill-type model is used in musculoskeletal modeling, the Vmax should be scaled with activation.
Paced effort and all-out 30 s power tests The association between cycling experience and preferred and most economical cadences
- B R Macintosh
- P Maceachern Marsh
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