More than metrics: The role of socio- environmental factors in determining the success of athlete monitoring

The perceived value of athlete monitoring systems (AMS) has recently been questioned. Poor perceptions of AMS are important, because where practitioners lack confidence in monitoring their ability to influence programming, and performance is likely diminished. To address this, researchers have primarily sought to improve factors related to monitoring metrics, e.g., validity rather than socio-environmental factors, e.g., buy-in. Seventy-five practitioners (response rate: n = 30) working with Olympic and Paralympic athletes were invited to take part in a survey about their perceptions of AMS value. Fifty-two per cent (n = 13) was confident in the sensitivity of their athlete self-report measures, but only 64% (n = 16), indicated their monitoring was underpinned by scientific evidence. A scientific base was associated with improved athlete feedback (r S (23) = 0.487, p =0.014*) and feedback correlated with athlete monitoring adherence (r S (22) = 0.675, p = &lt;0.001**). If athletes did not complete their monitoring, 52% (n = 13) of respondents felt performance might be compromised. However, most respondents 56% (n = 14), had worked with internationally successful athlete(s) who did not complete their monitoring. While AMS can be a useful tool to aid performance optimisation, its potential value is not always realised. Addressing socio-environmental factors alongside metric-factors may improve AMS efficacy. </p

The Effect of Cycling Intensity on Cycling Economy During Seated and Standing Cycling

BACKGROUND: Previous research has shown that cycling in a standing position reduces cycling economy compared with seated cycling. It is unknown whether the cycling intensity moderates the reduction in cycling economy while standing. PURPOSE: The aim was to determine whether the negative effect of standing on cycling economy would be decreased at a higher intensity. METHODS: Ten cyclists cycled in 8 different conditions. Each condition was either at an intensity of 50% or 70% of maximal aerobic power, at a gradient of 4% or 8% and in the seated or standing cycling position. Cycling economy and muscle activation level of 8 leg muscles were recorded. RESULTS: There was an interaction between cycling intensity and position for cycling economy (P = 0.03), the overall activation of the leg muscles (P = 0.02) and the activation of the lower leg muscles (P = 0.05). The interaction showed decreased cycling economy when standing compared with seated cycling, but the difference was reduced at higher intensity. The overall activation of the leg muscles and the lower leg muscles respectively increased and decreased, but the differences between standing and seated cycling were reduced at higher intensity. CONCLUSIONS: Cycling economy was lower during standing cycling than seated cycling, but the difference in economy diminishes when cycling intensity increases. Activation of the lower leg muscles did not explain the lower cycling economy while standing. The increased overall activation therefore suggests that increased activation of the upper leg muscles explains part of the lower cycling economy while standing

RELIABILITY OF A TRUNK MOUNTED ACCELEROMETER WHEN DETERMINING GAIT PARAMETERS IN PEOPLE WITH STROKE

Wearable sensors and accelerometers can objectively and reliably assess gait parameters in both healthy individuals and stroke patients. The purpose of this study was to determine whether a wireless tri-axial accelerometer is reliable when measuring spatio-temporal gait parameters in patients with stroke. Thirty-one chronic stroke patients (age: 59.5±13.6 years; time since stroke: 28.1±17.8 months) completed three repeated walks along a 10m flat walkway whilst wearing a trunk mounted accelerometer (BTS G-Walk) secured around the waist of the participant over the L5 vertebrae. Outcome measures included cadence, speed, stride length, %stride length/height, gait cycle duration, step length, stance and swing phase duration, single and double support duration for both symptomatic and asymptomatic lower limbs where relevant. Reliability was assessed via intraclass correlation coefficient (ICC), standard error of the mean (SEM) and smallest detectable change (SDC) values. ICCs were \u3e 0.75 for all parameters, excluding step length on the asymptomatic side (ICC = 0.70). SEM and the SDC were marginally larger for the symptomatic limb than the asymptomatic limb for gait cycle duration and step length, but smaller for all other outcomes. The study showed that the BTS G-Walk is a reliable tool for measuring spatio-temporal parameters in patients with stroke. Physiotherapists and clinicians often prefer detailed information on gait ability. As advanced technologies could help with specific goals relating to gait performance, such devices could be reliably implemented as an alternative to the gold standard in clinical and community settings to monitor patients outside of a lab-based environment

Gross efficiency and cycling performance: a review.

Efficiency, the ratio of work generated to the total metabolic energy cost, has been suggested to be a key determinant of endurance cycling performance. The purpose of this brief review is to evaluate the influence of gross efficiency on cycling power output and to consider whether or not gross efficiency can be modified. In a re-analysis of data from five separate studies, variation in gross efficiency explained ~30% of the variation in power output during cycling time-trials. Whilst other variables, notably VO2max and lactate threshold, have been shown to explain more of the variance in cycling power output, these results confirm the important influence of gross efficiency. Case study, cross-sectional, longitudinal, and intervention research designs have all been used to demonstrate that exercise training can enhance gross efficiency. Whilst improvements have been seen with a wide range of training types (endurance, strength, altitude), it would appear that high intensity training is the most potent stimulus for changes in gross efficiency. In addition to physiological adaptations, gross efficiency might also be improved through biomechanical adaptations. However, ‘intuitive’ technique and equipment adjustments may not always be effective. For example, whilst ‘pedalling in circles’ allows pedalling to become mechanically more effective, this technique does not result in short term improvements in gross efficiency

The Relationship between Skinfold and Ultrasound Measures of Subcutaneous Fat in Untrained Healthy Males

Ultrasound measurement of adipose tissue offers an alternative measure of body composition with less technical skill requirement than skinfolds. However, the relationship between skinfold and ultrasound measurements of adipose tissue is uncertain. The aim of this study was to compare these measures in a healthy untrained male population. One hundred male participants (aged 18–40 years) of varying body compositions had skinfold measures taken at the biceps, triceps and front thigh sites. Ultrasound measures were also taken at the same sites using B-wave ultrasound with a linear probe in the transverse plane. Strong, significant (p &lt; 0.01), positive correlations were observed between skinfold and ultrasound measures at the biceps (r = 0.828), triceps (r = 0.813), and front thigh (r = 0.888) sites. However, there was significant (p &lt; 0.01) variance between the techniques at all measurement sites. Whilst skinfold and ultrasound measures of adipose tissue have good linear agreement, skinfolds are consistently higher at all sites indicating a difference in the nature of the tissue measured via each technique. The exact nature of the relationship should be established on a population-specific basis

The 3-minute all-out cycling test is sensitive to changes in cadence using the Lode Excalibur Sport ergometer

This study investigated the effect cadence has on the estimation of critical power (CP) and the finite work capacity (Wʹ) during the 3-minute all-out cycling test. Ten participants completed 8 tests: 1) an incremental test to calculate gas exchange threshold (GET), maximal aerobic power (MAP) and peak oxygen uptake (V̇O2peak), 2–4) three time-trial-exhaustion tests at 80, 100 and 105% MAP to calculate CP and Wʹ, 5–7) four 3-minute all-out tests to calculate end power (EP) and work done above EP (WEP) using cadences ranging from preferred −5 to preferred +10 rev·min-1 to set the fixed resistance. Significant differences were seen between CP and EP-preferred (267.5 ± 22.6 W vs. 296.6 ± 26.1 W, P < 0.001), CP and EP−5 (267.5 ± 22.6 W vs. 303.6 ± 24.0 W, P < 0.001) and between CP and EP+5 (267.5 ± 22.6 W vs. 290.0 ± 28.0 W, P = 0.002). No significant differences were seen between CP and EP+10 (267.5 ± 22.6 W vs. 278.1 ± 30.9 W, P = 0.331). Significant differences were seen between Wʹ and WEP at all tested fixed resistances. EP is reduced when cycling at higher than preferred cadences, providing better estimates of CP