The generalized force-velocity relationship explains why the preferred pedaling rate of cyclists exceeds the most efficient one

The most efficient pedaling rate (lowest oxygen consumption) at a workload of 50-300W has been reported to be in the range of 42-60rpm. By contrast, most competitive cyclists prefer a pedaling rate of more than 90rpm. The reason for this difference is still unknown. We assume that the high pedaling rate preferred by cyclists can be explained by the inherent properties of muscle fibers. To obtain statements which do not depend on muscle's cross-section and length, we generalized Hill's characteristic equations where muscle force and heat liberation are related to shortening velocity. A pedaling rate of f ηmax yields to maximal efficiency, whereas the higher pedaling rate f Pmax leads to maximal power. The ratio f Pmax/f ηmax between these two pedaling rates ranges from 1.7 to 2.4, and it depends on the muscle's fiber-type composition. In sprints and competitions of very short duration, f Pmax is more advantageous because energy supply is not the predominant limiting factor. The price to be paid for the most powerful pedaling rate is lower efficiency and higher energy cost. In longer exercises, economy is more important and the optimal pedaling rate shifts toward f ηmax. We conclude that the optimal pedaling rate, representing the fastest race performance, is not fixed but depends on race duration; it ranges between f ηmax and f Pmax. Our results are not only of interest for competitive cyclists but also for investigations using cycle ergometers: maximum power might not be reached by using a pedaling rate near the most efficient on

THE ANALYSIS OF PEDALING FORCE AND LOWER EXTREMITY EMG USING DIFFERENT PEDALING RATES AND LOADS

In cycling, the pedaling rate and load will affect the rider’s performance and the enjoyment of riding. Previous studies usually analyzed the lower extremity EMG with different pedaling posture and pedaling rate, but mostly by professional cyclists (Neptune & Hull, 1999). However, most riders are recreational riders, therefore the results of previous studies are not suitable for the untrained persons, there were no results of lower extremity EMG and pedaling force in the study of pedaling rate and load. The purpose of this study was to analyze the effect of the different pedaling rates and loads on pedaling force and lower extremity EMG

The Effect of Movement Rate and Complexity on Functional Magnetic Resonance Signal Change During Pedaling

We used functional magnetic resonance imaging (fMRI) to record human brain activity during slow (30 RPM), fast (60 RPM), passive (30 RPM), and variable rate pedaling. Ten healthy adults participated. After identifying regions of interest, the intensity and volume of brain activation in each region was calculated and compared across conditions (p \u3c .05). Results showed that the primary sensory and motor cortices (S1, M1), supplementary motor area (SMA), and cerebellum (Cb) were active during pedaling. The intensity of activity in these areas increased with increasing pedaling rate and complexity. The Cb was the only brain region that showed significantly lower activity during passive as compared with active pedaling. We conclude that M1, S1, SMA, and Cb have a role in modifying continuous, bilateral, multijoint lower extremity movements. Much of this brain activity may be driven by sensory signals from the moving limbs

A Novel fMRI Paradigm Suggests that Pedaling-related Brain Activation is Altered after Stroke

The purpose of this study was to examine the feasibility of using functional magnetic resonance imaging (fMRI) to measure pedaling-related brain activation in individuals with stroke and age-matched controls. We also sought to identify stroke-related changes in brain activation associated with pedaling. Fourteen stroke and 12 control subjects were asked to pedal a custom, MRI-compatible device during fMRI. Subjects also performed lower limb tapping to localize brain regions involved in lower limb movement. All stroke and control subjects were able to pedal while positioned for fMRI. Two control subjects were withdrawn due to claustrophobia, and one control data set was excluded from analysis due to an incidental finding. In the stroke group, one subject was unable to enter the gantry due to excess adiposity, and one stroke data set was excluded from analysis due to excessive head motion. Consequently, 81% of subjects (12/14 stroke, 9/12 control) completed all procedures and provided valid pedaling-related fMRI data. In these subjects, head motion was ≤3 mm. In both groups, brain activation localized to the medial aspect of M1, S1, and Brodmann’s area 6 (BA6) and to the cerebellum (vermis, lobules IV, V, VIII). The location of brain activation was consistent with leg areas. Pedaling-related brain activation was apparent on both sides of the brain, with values for laterality index (LI) of –0.06 (0.20) in the stroke cortex, 0.05 (±0.06) in the control cortex, 0.29 (0.33) in the stroke cerebellum, and 0.04 (0.15) in the control cerebellum. In the stroke group, activation in the cerebellum – but not cortex – was significantly lateralized toward the damaged side of the brain (p = 0.01). The volume of pedaling-related brain activation was smaller in stroke as compared to control subjects. Differences reached statistical significance when all active regions were examined together [p = 0.03; 27,694 (9,608) μL stroke; 37,819 (9,169) μL control]. When individual regions were examined separately, reduced brain activation volume reached statistical significance in BA6 [p = 0.04; 4,350 (2,347) μL stroke; 6,938 (3,134) μL control] and cerebellum [p = 0.001; 4,591 (1,757) μL stroke; 8,381 (2,835) μL control]. Regardless of whether activated regions were examined together or separately, there were no significant between-group differences in brain activation intensity [p = 0.17; 1.30 (0.25)% stroke; 1.16 (0.20)% control]. Reduced volume in the stroke group was not observed during lower limb tapping and could not be fully attributed to differences in head motion or movement rate. There was a tendency for pedaling-related brain activation volume to increase with increasing work performed by the paretic limb during pedaling (p = 0.08, r = 0.525). Hence, the results of this study provide two original and important contributions. First, we demonstrated that pedaling can be used with fMRI to examine brain activation associated with lower limb movement in people with stroke. Unlike previous lower limb movements examined with fMRI, pedaling involves continuous, reciprocal, multijoint movement of both limbs. In this respect, pedaling has many characteristics of functional lower limb movements, such as walking. Thus, the importance of our contribution lies in the establishment of a novel paradigm that can be used to understand how the brain adapts to stroke to produce functional lower limb movements. Second, preliminary observations suggest that brain activation volume is reduced during pedaling post-stroke. Reduced brain activation volume may be due to anatomic, physiology, and/or behavioral differences between groups, but methodological issues cannot be excluded. Importantly, brain action volume post-stroke was both task-dependent and mutable, which suggests that it could be modified through rehabilitation. Future work will explore these possibilities

Brain Activation During Passive and Volitional Pedaling After Stroke

Background: Prior work indicates that pedaling-related brain activation is lower in people with stroke than in controls. We asked whether this observation could be explained by between-group differences in volitional motor commands and pedaling performance. Methods: Individuals with and without stroke performed passive and volitional pedaling while brain activation was recorded with functional magnetic resonance imaging. The passive condition eliminated motor commands to pedal and minimized between-group differences in pedaling performance. Volume, intensity, and laterality of brain activation were compared across conditions and groups. Results: There were no significant effects of condition and no Group × Condition interactions for any measure of brain activation. Only 53% of subjects could minimize muscle activity for passive pedaling. Conclusions: Altered motor commands and pedaling performance are unlikely to account for reduced pedaling-related brain activation poststroke. Instead, this phenomenon may be due to functional or structural brain changes. Passive pedaling can be difficult to achieve and may require inhibition of excitatory descending drive

Time course of learning to produce maximum cycling power

Journal ArticleThe purpose of this investigation was to determine the time course and magnitude of learning effects associated with repeated maximum cycling power tests and to determine if cycle-trained men exhibit different learning effects than active men who are not cycle-trained. Cycle-trained (N = 13) and active men (N = 35) performed short maximal cycling bouts 4 times per day for 4 consecutive days. Inertial load cycle ergometry was used to measure maximum power and pedaling rate at maximum power. Maximum power of the cycle-trained men did not differ across days or bouts. Maximum power of the active men increased 7% within the first day and 7% from the mean of day one to day three. Pedaling rate at maximum power did not differ across days or bouts in either the cycle-trained or active men. These results demonstrate that valid and reliable results for maximum cycling power can be obtained from cycle-trained men in a single day, whereas active men require at least 2 days of practice in order to produce valid and reliable values

Maximizing Performance in Human Powered Vehicles: A Literature Review and Directions for Future Research

If the limits of performance in human powered vehicles (HPV) are to be reached, designers of HPVs need to understand how the body interacts with the vehicle to maximize propulsive forces, and how the vehicle interacts with the environment to minimize resistive forces. This paper will review, compare and summarize the various research literature on both upright and recumbent cycling positions regarding how systematic changes in external mechanical variables (seat-tube-angle, seat-to-pedal distance, crank arm length) interact with internal biomechanical factors (hip, knee, and ankle angles) to affect power production and cycling performance. Conclusions for future research will also be also presented

Doctor of Philosophy

dissertationMost cycling power is produced during leg extension with minimal power production occuring during the transition between the extension-flexion phases. A prolonged leg extension phase and reduced transition phase could increase cycling power by allowing muscles to generate power for a greater portion of the cycle. Noncircular chainrings have been designed to prolong the time spent in the powerful leg extension phase by varying crank angular velocity within the pedal cycle. The purposes of this dissertation were to evaluate the extent to which noncircular chainrings influence power, biomechanics, and metabolic cost during maximal and submaximal cycling. In the first study, I investigated the effects of chainring eccentricity (C = 1.0, R = 1.13, O = 1.24) on maximum cycling power (Pmax) and optimal pedaling rate (RPMopt). Chainring eccentricity did not influence Pmax and RPMopt. Despite reasonable theory regarding a prolonged leg extension phase and reduced transition phase, chainring eccentricity did not influence Pmax and RPMopt during maximal cycling. In the second study, I evaluated the influence of noncircular chainrings on joint-specific kinematics and power production during maximal cycling. Ankle angular velocity was significantly reduced (-13±12% and -37±13% at 90 and 120 rpm, respectively) with the O chainring, whereas knee and hip angular velocities were unaffected during the leg extension phase. Further, joint-specific power production was unaffected by chainring eccentricity. These results demonstrate that redundant degrees of freedom (DOF) in the cycling action (i.e., ankle angle) allowed cyclists to negate the effects of eccentricity and maintain their preferred hip and knee actions. In my third study, I evaluated the extent to which chainring eccentricity influenced metabolic cost and biomechanics of submaximal cycling. My study protocol allowed for separate analysis of eccentricity and pedal speed (known to influence metabolic cost). Chainring eccentricity with similarly matched pedal speeds reduced knee (-10%) and hip (-5%) angular velocities, while metabolic cost and cycling efficiency remained unaffected. Despite small but significant alterations in joint-specific kinematics, chainring eccentricity did not influence metabolic cost or cycling efficiency during submaximal cycling. Taken together, these results indicate that commercially available noncircular chainrings do not provide performance benefits over conventional circular chainrings during maximal and submaximal cycling

MULTIVARIABLE OPTIMIZATION OF CYCLING BIOMECHANICS

Introduction: In an activity of conventional cycling where the pedal travels a circular path at constant velocity, a number of variables affect the intersegmental loads in the leg when the power output is constant. As depicted in Figures 1a and 1b, four geometric variables are crank arm length, seat height, seat tube angle, and longitudinal foot position on the pedal. Considering the leg-bicycle to be a five-bar linkage constrained to plane motion (see Figure 2a), it is clear that each of these geometric variables influences the linkage kinematics and hence the intersegmental loads. Because of this influence these variables are termed biomechanical variables. In addition to the four geometric variables, a fifth biomechanical variable is the pedaling rate. Since these variables affect cycling biomechanics and are readily adjusted by a cyclist setting up his equipment, it is useful to determine a method for establishing optimum adjustments

Slowed response to peripheral visual stimuli during strenuous exercise

Recently, we proposed that strenuous exercise impairs peripheral visual perception because visual responses to peripheral visual stimuli were slowed during strenuous exercise. However, this proposal was challenged because strenuous exercise is also likely to affect the brain network underlying motor responses. The purpose of the current study was to resolve this issue. Fourteen participants performed a visual reaction-time (RT) task at rest and while exercising at 50% (moderate) and 75% (strenuous) peak oxygen uptake. Visual stimuli were randomly presented at different distances from fixation in two task conditions: the Central condition (2° or 5° from fixation) and the Peripheral condition (30° or 50° from fixation). We defined premotor time as the time between stimulus onset and the motor response, as determined using electromyographic recordings. In the Central condition, premotor time did not change during moderate (167 ± 19 ms) and strenuous (168 ± 24 ms) exercise from that at rest (164 ± 17 ms). In the Peripheral condition, premotor time significantly increased during moderate (181 ± 18 ms, P < 0.05) and strenuous exercise (189 ± 23 ms, P < 0.001) from that at rest (173 ± 17 ms). These results suggest that increases in Premotor Time to the peripheral visual stimuli did not result from an impaired motor-response network, but rather from impaired peripheral visual perception. We conclude that slowed response to peripheral visual stimuli during strenuous exercise primarily results from impaired visual perception of the periphery