ObjectiveTo analyse rider’s subjective responses after a standardised bicycle ergonomic adjustment method.MethodsExperimental study of 160 healthy, amateur mountain bikers analysed previously and 30 days after a bike-fitting session. The main outcome measures were subjective comfort level (Feeling Scale, FEEL), fatigue (OMINI Scale) and pain (Visual Analogue Scale, VAS).ResultsAll variables demonstrated statistical significance between groups pre and post bike-fit session (p<0001). FEEL, OMNI and VAS-knee demonstrated large effect sizes (d=1.30; d=1.39 and d=0.86, respectively). VAS-hands, VAS-neck and VAS-back indicated moderate effect size (d=0.58; d=0.52 and d=0.43, respectively). VAS-groin and VAS-ankle indicated a small size effect (d=0.46 and d=0.43, respectively).ConclusionsOverall discomfort, fatigue and pain in healthy mountain biker adults improved according to all three scales. The major improvements in pain levels were detected on the knee, hands, back and neck compared with presession values. Groin and ankle pain had smaller improvements but were still significant. Future clinical trials should address the bias effects of this experimental study.

The evaluation of anticipatory postural adjustments (APAs) requires high-cost and complex handling systems, only available at research laboratories. New alternative methods are being developed in this field, on the other hand, to solve this issue and allow applicability in clinic, sport and hospital environments. The objective of this study was to validate an app for mobile devices to measure the APAs during gait initiation by comparing the signals obtained from cell phones using the Momentum app with measurements made by a kinematic system. The center-of-mass accelerations of a total of 20 healthy subjects were measured by the above app, which read the inertial sensors of the smartphones, and by kinematics, with a reflective marker positioned on their lumbar spine. The subjects took a step forward after hearing a command from an experimenter. The variables of the anticipatory phase, prior to the heel-off and the step phase, were measured. In the anticipatory phase, the linear correlation of all variables measured by the two measurement techniques was significant and indicated a high correlation between the devices (APAonset: r = 0.95, p < 0.0001; APAamp: r = 0.71, p = 0.003, and PEAKtime: r = 0.95, p < 0.0001). The linear correlation between the two measurement techniques for the step phase variables measured by ques was also significant (STEPinterval: r = 0.56, p = 0.008; STEPpeak1: r = 0.79, p < 0.0001; and STEPpeak2: r = 0.64, p < 0.0001). The Bland–Altman graphs indicated agreement between instruments with similar behavior as well as subjects within confidence limits and low dispersion. Thus, using the Momentum cell phone application is valid for the assessment of APAs during gait initiation compared to the gold standard instrument (kinematics), proving to be a useful, less complex, and less costly alternative for the assessment of healthy individuals.

Background: Kinematic analysis aimed toward scientific investigation or professional purposes is commonly unaffordable and complex to use. Objective: The purpose of this study was to verify concurrent validation between a cycling-specific 3D camera and the gold-standard 3D general camera systems. Methods: Overall, 11 healthy amateur male triathletes were filmed riding their bicycles with Vicon 3D cameras and the Retul 3D cameras for bike fitting analysis simultaneously. All 18 kinematic measurements given by the bike fitting system were compared with the same data given by Vicon cameras through Pearson correlation (r), intraclass correlation coefficients (ICC), standard error measurements (SEM), and Bland–Altman (BA) analysis. Confidence intervals of 95% are given. Results: A very high correlation between cameras was found on six of 18 measurements. All other presented a high correlation between cameras (between 0.7 and 0.9). In total, six variables indicate a SEM of less than one degree between systems. Only two variables indicate a SEM higher than two degrees between camera systems. Overall, four measures indicate bias tendency according to BA. Conclusions: The cycling-specific led-emitting 3D camera system tested revealed a high or very high degree of correlation with the gold-standard 3D camera system used in laboratory motion capture. In total, 14 measurements of this equipment could be used in sports medicine clinical practice and even by researchers of cycling studies.

Introduction: Postural control is a determining factor for functional performance and motor skills during sports activities. Objective: The objective of this study was to investigate postural control during the controlled soccer ball kicking task through a biomechanical analysis system. Methods: The sample consisted of 11 professional male athletes recruited using convenience sampling, with a mean age of 22 years. The athletes performed twenty-five precision kicks at a target, with the ball in vertical motion released by means of a hand-held device synchronized with the computed biomechanical measurements. Marking of the lower limb segments involved in the kick and the ball were analyzed by accelerometry, while postural control measures were quantified by a force platform in three axes of movement. The support leg was investigated in single leg stance during all tests on the force platform. The main variables of postural control calculated by stabilographic analysis and computed during the 25 kicks were: center of pressure (COP) displacement area, velocity and frequency of COP oscillation in the anteroposterior and mediolateral directions. The mean was used for final analysis to determine the differences in the three phases: pre-kick, kick, and post-kick. Results: The results revealed significant differences (p <0.01) between the three phases, with the kick phase presenting higher values of postural COP oscillations than the other phases. The COP area and oscillation velocity were the variables with greatest sensitivity to changes in the kick phase, obtaining an effect size of d = 14 and d = 12, respectively. In clinical terms, the increase in COP values reached 557% between the pre-kick and kick phases; this difference was reduced to 241% when compared to post-kick (i.e., difference between kick and post-kick was 316%). Conclusion . These results have important implications for the perception of postural control responses during soccer ball kicks and consequently, for injury prevention when motor and sensory deficits are diagnosed in soccer players. Level of Evidence III; Study of nonconsecutive patients; without consistently applied reference ‘‘gold’’ standard.

The purpose of this study is to analyze the long-term riders’ subjective responses to a standardized bikefitting method on their bicycles. Eighty-six amateur mountain bikers had their riding posture and bicycle components ergonomically adjusted through a 3D kinematic bikefitting method. Validated subjective scales (Feeling, OMNI, and Numerical Rating Pain Scale) were used to assess their overall riding comfort and fatigue along with localized pain for six body parts. Data were collected just before intervention (baseline or pre), immediately after (or post), and 30, 60, 90, and 120 days after the bikefit session. A Student’s t-test comparing before bikefit and after 120 days showed significant (p < 0.05) reduction in localized pain for all six body parts and riding comfort along with a large effect size effect (d = 1.18) for riding comfort. Although initially reduced, fatigue scores gradually increased over the months, showing a high correlation (r = 0.946) with increased monthly training volume. In conclusion, overall riding discomfort and pain were significantly decreased after a standardized kinematic bikefit session even after 120 days post intervention. However, fatigue scores began to rise after 30 days, showing a high correlation with increasing monthly training volume.