It is essential for any highly trained cyclist to optimize his pedalling movement in order to maximize the performance and minimize the risk of injuries. Current techniques rely on bicycle fitting and off-line laboratory measurements. These techniques do not allow the assessment of the kinematics of the cyclist during training and competition, when fatigue may alter the ability of the cyclist to apply forces to the pedals and thus induce maladaptive joint loading. We propose a radically different approach that focuses on determining the actual status of the cyclist’s lower limb segments in real-time and real-life conditions. Our solution is based on body area wireless motion sensor nodes that can collaboratively process the sensory information and provide the cyclists with immediate feedback about their pedalling movement. In this paper, we present a thorough study of the accuracy of our system with respect to the gold standard motion capture system. We measure the knee and ankle angles, which influence the performance as well as the risk of overuse injuries during cycling. The results obtained from a series of experiments with nine subjects show that the motion sensors are within 2.2° to 6.4° from the reference given by the motion capture system, with a correlation coefficient above 0.9. The wireless characteristics of our system, the energy expenditure, possible improvements and usability aspects are further analysed and discussed.

During fatiguing voluntary contractions, the excitability of motoneurons innervating arm muscles decreases. However, the behavior of motoneurons innervating quadriceps muscles is unclear. Findings may be inconsistent because descending cortical input influences motoneuron excitability and confounds measures during exercise. To overcome this limitation, we examined effects of fatigue on quadriceps motoneuron excitability tested during brief pauses in descending cortical drive after transcranial magnetic stimulation (TMS). Participants ( n = 14) performed brief (~5-s) isometric knee extension contractions before and after a 10-min sustained contraction at ~25% maximal electromyogram (EMG) of vastus medialis (VM) on one ( n = 5) or two ( n = 9) days. Electrical stimulation over thoracic spine elicited thoracic motor evoked potentials (TMEP) in quadriceps muscles during ongoing voluntary drive and 100 ms into the silent period following TMS (TMS-TMEP). Femoral nerve stimulation elicited maximal M-waves (M_max). On the 2 days, either large (~50% M_max) or small (~15% M_max) TMS-TMEPs were elicited. During the 10-min contraction, VM EMG was maintained ( P = 0.39), whereas force decreased by 52% (SD 13%) ( P < 0.001). TMEP area remained unchanged ( P = 0.9), whereas large TMS-TMEPs decreased by 49% (SD 28%) ( P = 0.001) and small TMS-TMEPs by 71% (SD 22%) ( P < 0.001). This decline was greater for small TMS-TMEPs ( P = 0.019; n = 9). Therefore, without the influence of descending drive, quadriceps TMS-TMEPs decreased during fatigue. The greater reduction for smaller responses, which tested motoneurons that were most active during the contraction, suggests a mechanism related to repetitive activity contributes to reduced quadriceps motoneuron excitability during fatigue. By contrast, the unchanged TMEP suggests that ongoing drive compensates for altered motoneuron excitability. NEW & NOTEWORTHY We provide evidence that the excitability of quadriceps motoneurons decreases with fatigue. Our results suggest that altered intrinsic properties brought about by repetitive activation of the motoneurons underlie their decreased excitability. Furthermore, we note that testing during voluntary contraction may not reflect the underlying depression of motoneuron excitability because of compensatory changes in ongoing voluntary drive. Thus, this study provides evidence that processes intrinsic to the motoneuron contribute to muscle fatigue of the knee extensors.

Force-velocity tests performed on stationary cycle ergometers are widely used to assess the torque- and power-generating capacities of the lower limbs. The aim of this study was to identify how testing and modeling procedures influence the assessment of individual torque-cadence and power-cadence relationships. Seventeen males completed 62 ± 16 pedal cycles from six 6-s all-out efforts interspersed with 5 min of rest. True measures of maximal power for a particular cadence were obtained for 24 ± 3 pedal cycles, while power was only 94 ± 3% of the true maximum in 19 ± 5 pedal cycles. Pedal cycles showing maximal levels of power also displayed higher levels of electromyography (EMG: 89 ± 7 vs . 87 ± 7%) and coactivation (34 ± 11 vs . 31 ± 10 arbitrary units), as well as lower variability in crank torque and EMG profiles. Compared with the linear and second-order polynomial models that are traditionally used, a better goodness of fit was obtained when the torque-cadence and power-cadence relationships were predicted using second- and third-order polynomials, respectively. The later modeling procedures also revealed an asymmetry in the power-cadence relationship in most participants (i.e., 15 out of 17) and provided a better estimation of maximal cadence [C_max: 214 ± 20 revolutions/min (rpm)] from the x-intercept of power-cadence relationships (C₀: 214 ± 14 rpm). Therefore, we recommend predicting the individual shapes of torque- and power-cadence relationships using second- and third-order polynomial regressions after having selected pedal cycles during which true measures of cadence-specific maximal power were recorded. NEW & NOTEWORTHY This study is the first to demonstrate that suboptimal activation of the lower limb muscles accompanied reductions in cadence-specific levels of torque and power produced during a force-velocity test performed on a stationary cycle ergometer. This research is also the first to show that, in most noncyclist participants, torque-cadence relationships are not linear, whereas power-cadence relationships display asymmetric shapes, with power production decreasing rapidly when cadence increases beyond 180 revolutions/min.

We investigated whether potassium (K⁺) disturbances during and following intense exercise may be pronounced when utilizing a large contracting muscle mass, examining maximal 2,000-m rowing exercise effects on radial arterial plasma K⁺concentration ([K⁺]_a) in 11 healthy adults. Blood was sampled at baseline, preexercise, each 30 s during rowing, and for 30 min postexercise. Time to complete 2,000 m was 7.26 ± 0.59 min; power output at 30 s was 326 ± 81 W (mean ± SD). With exercise time expressed in deciles, power output fell 16.5% from the first to fourth decile ( P < 0.05) and 19.9% at the ninth decile ( P < 0.05); EMG median frequency declined 4.6% by the third decile and 5.5% by the eighth decile ( P < 0.05). Plasma [K⁺]_aincreased from 3.89 ± 0.13 mM at rest to 6.13 ± 0.46 mM by 90 s rowing ( P < 0.001) and was then sustained until end exercise ( P < 0.001). In recovery, [K⁺]_adecreased abruptly, reaching 3.33 ± 0.22 mM at 5 min postexercise ( P < 0.001) and remaining below preexercise after 30 min ( P < 0.005). At end exercise, blood [lactate]_a(preexercise 0.64 ± 0.18 mM) reached 10.87 ± 1.33 mM, plasma volume decreased 9.7 ± 2.3% from preexercise, and pH_adecreased to 7.10 ± 0.07 units ( P < 0.001). In conclusion, arterial hyperkalemia was sustained during exhaustive rowing reflecting a balance between K⁺release and reuptake in contracting muscles and K⁺uptake by inactive muscles. While high, the [K⁺]_awas lower than anticipated compared with maximal cycling or sprinting, possibly reflecting greater adrenergic response and Na⁺,K⁺-ATPase activity in contracting muscles; fatigue was evidenced by reduced power output and EMG median frequency. A prolonged hypokalemia after rowing likely reflected continuing muscular Na⁺,K⁺-ATPase activity.