Modeling Optimal Cadence as a Function of Time during Maximal Sprint Exercises Can Improve Performance by Elite Track Cyclists

In track cycling sprint events, optimal cadence PRopt is a dynamic aspect of fatigue. It is currently unclear what cadence is optimal for an athlete’s performance in sprint races and how it can be calculated. We examined fatigue-induced changes in optimal cadence during a maximal sprint using a mathematical approach. Nine elite track cyclists completed a 6-s high-frequency pedaling test and a 60-s isokinetic all-out sprint on a bicycle ergometer with continuous monitoring of crank force and cadence. Fatigue-free force-velocity (F/v) and power-velocity (P/v) profiles were derived from both tests. The development of fatigue during the 60-s sprint was assessed by fixing the slope of the fatigue-free F/v profile. Fatigue-induced alterations in PRopt were determined by non-linear regression analysis using a mono-exponential equation at constant slope. The study revealed that PRopt at any instant during a 60-s maximal sprint can be estimated accurately using a mono-exponential equation. In an isokinetic mode, a mean PRopt can be identified that enables the athlete to generate the highest mean power output over the course of the effort. Adding the time domain to the fatigue-free F/v and P/v profiles allows time-dependent cycling power to be modelled independent of cadence.

The Effect of Pedaling At Different Cadence On Attentional Resources

Research aim: We investigated the relationship between attentional resources and pedaling cadence using electroencephalography (EEG) to measure P300 amplitudes and latencies. Methods: Twenty-five healthy volunteers performed the oddball task while pedaling on a stationary bike or relaxing (no pedaling). We set them four conditions: 1) performing only the oddball task (control), 2) performing the oddball task while pedaling at optimal cadence (optimal), 3) performing the oddball task while pedaling faster than optimal cadence (fast), and 4) performing the oddball task while pedaling slower than optimal cadence (slow). Results: P300 amplitudes at Cz and Pz electrodes under optimal, fast, and slow conditions were significantly lower than that under control conditions. P300 amplitudes at Pz under fast and slow conditions were significantly lower than that under the optimal condition. No significant changes in P300 latency at any electrode were observed under any condition. Conclusion: Our findings revealed that pedaling at non-optimal cadence results in less attention being paid to external stimuli compared with pedaling at optimal cadence.

Modeling cycling performance: Effects of saddle position and cadence on cycle pedaling efficiency

The modeling method is an effective means of estimating causality as well as examining cycle pedaling efficiency. Pedaling efficiency can also be examined by an experimental method, but the experimental method can lead to contradictory results due to perturbation of the measured output parameters. Experimental studies generally yield realistic results, but it is difficult to control for all the variables of interest and to determine the causal relationships between them. The objective of this study is to investigate the pedaling efficiency and causality with considering saddle position and pedaling cadence as variables. Based on the mathematical pedaling modeling, the internal work calculation method was used to calculate the consumed mechanical energy and energy conservation percentage ([Formula: see text]). The optimal saddle position with the lowest mechanical energy and the highest energy conservation percentage could be changed by the cadence. At the low cadence, the higher saddle position, and the shorter horizontal distance between the saddle and crankshaft led to higher pedaling efficiency ( h: 0.95 m, d: 0.16 m, and knee angle: [Formula: see text]). However, the highest pedaling efficiency was achieved at the high cadence with a saddle height ( h) of 0.9 m and a horizontal distance between the saddle and the crankshaft ( d) of 0.06 m (knee angle: [Formula: see text]). The lowest cadence is the optimal cadence in terms of the consumed energy, but the optimal cadence was 90 r/min in terms of the energy conservation percentage. Compared to the energy consumption, the energy conservation percentage was demonstrated to influence the fatigue of a cycle rider more critically. The energy conservation percentage was highest at 90 r/min, and 90 r/min was close to the preferred cadence by the cyclist.

Cadence (steps/min) and relative intensity in 21 to 60-year-olds: the CADENCE-adults study

Background Heuristic cadence (steps/min) thresholds of ≥100 and ≥ 130 steps/min correspond with absolutely-defined moderate (3 metabolic equivalents [METs]; 1 MET = 3.5 mL O2·kg− 1·min− 1) and vigorous (6 METs) intensity, respectively. Scarce evidence informs cadence thresholds for relatively-defined moderate (≥ 64% heart rate maximum [HRmax = 220-age], ≥ 40%HR reserve [HRR = HRmax -HRresting, and ≥ 12 Rating of Perceived Exertion [RPE]); or vigorous intensity (≥ 77%HRmax, ≥ 60%HRR, and ≥ 14 RPE). Purpose To identify heuristic cadence thresholds corresponding with relatively-defined moderate and vigorous intensity in 21–60-year-olds. Methods In this cross-sectional study, 157 adults (40.4 ± 11.5 years; 50.6% men) completed up to twelve 5-min treadmill bouts, beginning at 0.5 mph and increasing by 0.5 mph. Steps were directly observed, HR was measured with chest-worn monitors, and RPE was queried in the final minute of each bout. Segmented mixed model regression and Receiver Operating Characteristic (ROC) curve analyses identified optimal cadence thresholds, stratified by age (21–30, 31–40, 41–50, and 51–60 years). Reconciliation of the two analytical models, including trade-offs between sensitivity, specificity, positive and negative predictive values, and overall accuracy, yielded final heuristic cadences. Results Across all moderate intensity indicators, the segmented regression models estimated optimal cadence thresholds ranging from 123.8–127.5 (ages 21–30), 121.3–126.0 (ages 31–40), 117.7–122.7 (ages 41–50), and 113.3–116.1 steps/min (ages 51–60). Corresponding values for vigorous intensity were 140.3–144.1, 140.2–142.6, 139.3–143.6, and 131.6–132.8 steps/min, respectively. ROC analysis estimated chronologically-arranged age groups’ cadence thresholds ranging from 114.5–118, 113.5–114.5, 104.6–112.9, and 103.6–106.0 across all moderate intensity indicators, and 127.5, 121.5, 117.2–123.2, and 113.0 steps/min, respectively, for vigorous intensity. Conclusions Heuristic cadence thresholds corresponding to relatively-defined moderate intensity for the chronologically-arranged age groups were ≥ 120, 120, 115, and 105 steps/min, regardless of the intensity indicator (i.e., % HRmax, %HRR, or RPE). Corresponding heuristic values for vigorous intensity indicators were ≥ 135, 130, 125, and 120 steps/min. These cadences are useful for predicting/programming intensity aligned with age-associated differences in physiological response to, and perceived experiences of, moderate and/or vigorous intensity. Trial registration Clinicaltrials.gov NCT02650258. Registered 24 December 2015.

Walking cadence (steps/min) and intensity in 41 to 60-year-old adults: the CADENCE-adults study

Background In younger adults (i.e., those < 40 years of age) a walking cadence of 100 steps/min is a consistently supported threshold indicative of absolutely-defined moderate intensity ambulation (i.e., ≥ 3 metabolic equivalents; METs). Less is known about the cadence-intensity relationship in adults of middle-age. Purpose To establish heuristic (i.e., evidence-based, practical, rounded) cadence thresholds for absolutely-defined moderate (3 METs) and vigorous (6 METs) intensity in adults 41 to 60 years of age. Methods In this cross-sectional study, 80 healthy adults of middle-age (10 men and 10 women representing each 5-year age-group between 41 to 60 years; body mass index = 26.0 ± 4.0 kg/m2) walked on a treadmill for 5-min bouts beginning at 0.5 mph and increasing in 0.5 mph increments. Performance termination criteria included: 1) transitioning to running, 2) reaching 75% of age-predicted maximum heart rate, or 3) reporting a Borg rating of perceived exertion > 13. Cadence was directly observed (i.e., hand tallied). Intensity (i.e., oxygen uptake [VO2] mL/kg/min) was assessed with an indirect calorimeter and converted to METs (1 MET = 3.5 mL/kg/min). A combination of segmented regression and Receiver Operating Characteristic (ROC) modeling approaches was used to identify optimal cadence thresholds. Final heuristic thresholds were determined based on an evaluation of classification accuracy (sensitivity, specificity, positive and negative predictive value, overall accuracy). Results The regression model identified 101.7 (95% Predictive Interval [PI]: 54.9–110.6) and 132.1 (95% PI: 122.0–142.2) steps/min as optimal cadence thresholds for 3 METs and 6 METs, respectively. Corresponding values based on ROC models were 98.5 (95% Confidence Intervals [CI]: 97.1–104.9) and 117.3 (95% CI: 113.1–126.1) steps/min. Considering both modeling approaches, the selected heuristic thresholds for moderate and vigorous intensity were 100 and 130 steps/min, respectively. Conclusions Consistent with our previous report in 21 to 40-year-old adults, cadence thresholds of 100 and 130 steps/min emerged as heuristic values associated with 3 and 6 METs, respectively, in 41 to 60-year-old adults. These values were selected based on their utility for public health messaging and on the trade-offs in classification accuracy parameters from both statistical methods. Findings will need to be confirmed in older adults and in free-living settings.

Isovelocity vs. Isoinertial Sprint Cycling Tests for Power- and Torque-cadence Relationships

Sprint cycling performance is heavily dependent on mechanical peak power output (PPO) and the underlying power- and torque-cadence relationships. Other key indices of these relationships include maximum torque (TMAX), cadence (CMAX) and optimal cadence (COPT). Two common methods are used in the laboratory to ascertain PPO: isovelocity and isoinertial. Little research has been carried out to compare the magnitude and reliability of these performance measures with these two common sprint cycling assessments. The aim of this study was to compare the magnitude and reliability of PPO, TMAX, CMAX and COPT measured with isovelocity and isoinertial sprint cycling methods. Two experimental sessions required 20 trained cyclists to perform isoinertial sprints and then isovelocity sprints. For each method, power-cadence and torque-cadence relationships were established, and PPO and COPT were interpolated and TMAX and CMAX were extrapolated. The isoinertial method produced significantly higher PPO (p<0.001) and TMAX (p<0.001) than the isovelocity method. However, the isovelocity method produced significantly higher COPT (p<0.001) and CMAX (p=0.002). Both sprint cycling tests showed high levels of between-session reliability (isoinertial 2.9–4.4%; isovelocity 2.7–4.0%). Functional measures of isovelocity and isoinertial sprint cycling tests were highly reliable but should not be used interchangably.

The Relationship Between Freely Chosen Cadence and Optimal Cadence in Cycling

Purpose:The main aim of this study was to compare the freely chosen cadence (FCC) and the cadence at which the blood lactate concentration at constant power output is minimized (optimal cadence [Copt]). The second aim was to examine the effect of a concomitant change of road incline and body position on FCC, the maximal external power output (Pmax), and the corresponding Copt.Methods:FCC, Copt, and Pmax were analyzed under 2 conditions: cycling on level ground in a dropped position (LGDP) and cycling uphill in an upright position (UHUP). Seven experienced cyclists participated in this study. They cycled on a treadmill to test the 2 main hypotheses: Experienced cyclists would choose an adequate cadence close to Copt independent of the cycling condition, and FCC and Copt would be lower and Pmax higher for UHUP than with LGDP.Results:Most but not all experienced cyclists chose an adequate cadence close to Copt. Independent of the cycling condition, FCC and Copt were not statistically different. FCC (82.1 ± 11.1 and 89.3 ± 10.6 rpm, respectively) and Copt (81.5 ± 9.8 and 87.7 ± 10.9 rpm, respectively) were significantly lower and Pmax was significantly higher (2.0 ± 2.1%) for UHUP than for LGDP.Conclusion:Most experienced cyclists choose a cadence near Copt to minimize peripheral fatigue at a given power output independent of the cycling condition. Furthermore, it is advantageous to use a lower cadence and a more upright body position during uphill cycling.

Less is more: standard warm-up causes fatigue and less warm-up permits greater cycling power output

The traditional warm-up (WU) used by athletes to prepare for a sprint track cycling event involves a general WU followed by a series of brief sprints lasting ≥50 min in total. A WU of this duration and intensity could cause significant fatigue and impair subsequent performance. The purpose of this research was to compare a traditional WU with an experimental WU and examine the consequences of traditional and experimental WU on the 30-s Wingate test and electrically elicited twitch contractions. The traditional WU began with 20 min of cycling with a gradual intensity increase from 60% to 95% of maximal heart rate; then four sprints were performed at 8-min intervals. The experimental WU was shorter with less high-intensity exercise: intensity increased from 60% to 70% of maximal heart rate over 15 min; then just one sprint was performed. The Wingate test was conducted with a 1-min lead-in at 80% of optimal cadence followed by a Wingate test at optimal cadence. Peak active twitch torque was significantly lower after the traditional than experimental WU (86.5 ± 3.3% vs. 94.6 ± 2.4%, P < 0.05) when expressed as percentage of pre-WU amplitude. Wingate test performance was significantly better ( P < 0.01) after experimental WU (peak power output = 1,390 ± 80 W, work = 29.1 ± 1.2 kJ) than traditional WU (peak power output = 1,303 ± 89 W, work = 27.7 ± 1.2 kJ). The traditional track cyclist's WU results in significant fatigue, which corresponds with impaired peak power output. A shorter and lower-intensity WU permits a better performance.