ECSS Paris 2023: CP-BM16
INTRODUCTION: Middle-aged women experience a decline in circulating estrogen levels, which affects muscle strength (1). Torque-velocity analysis allows us to monitor these strength alterations. The main aims of this study were to compare the goodness of fit and derived parameters of linear and non-linear models of fitting the torque-velocity (TV) relationship in postmenopausal women and to contrast the results using target or real maximum velocities as independent variable. METHODS: 16 physically active postmenopausal women participated in a study funded by the Spanish Ministry of Science, Innovation and University (PID2021-124277OB). Knee extensors (KE) muscle strength was evaluated in the dominant limb using an isokinetic dynamometer. Range of motion was: 80º(knee flexed) to 0º(knee full extended). Isokinetic test was completed at 30, 60, 120, 180, 240, 300 and 400°/s. Peak torque was selected where >90% of the maximum target velocity was reached. Linear, polynomic and Hill regression models (2) were used to fit the TV data. Since the dynamometer reported a torque value even though the target velocity has not been reached, we obtained the TV relationship considering both real (i.e., the velocity achieved; TVR) and target velocity (i.e., the velocity preset on the dynamometer; TVT). The coefficient of determination (R2), mean square error (MSE) and all the TV parameters derived from each model were obtained considering TVR and TVT relationships. RESULTS: The isokinetic dynamometer failed to apply the preset target velocity, particularly at velocities >240º/s. In those cases, the automatic report included a peak torque reached at a velocity much lower than the target velocity but indicating that it was achieved at the target velocity. The goodness of fit of linear, polynomic and Hill models for fitting TVR and TVT data was excellent (R2>0.915). However, there were significant variations in both goodness of fit values and parameters derived from the linear and polynomial model, indicating that TVR and TVT were not similar (p<0.05). No variations in those variables were detected using Hill model (p>0.056). Considering TVR data, the best adjustment was obtained using Hill model (R2=0.991;MSE=3.72±1.63N2·m2) and the worst with linear model. However, the theoretical maximum velocity (V0) obtained from Hills model resulted physiologically incorrect (6764.69°/s). The theoretical maximum torque (T0) and velocity (V0) obtained from Hill model resulted higher compared with the values obtained from linear and polynomial models. CONCLUSION: Caution should be exercised when performing isokinetic assessment at high velocities in a population with low strength levels. Obtained data should be meticulously reviewed since TVR and TVT cannot be used interchangeably. The model choice can influence the parameters value. We recommend the polynomial model to fit the TV data for KE in postmenopausal women. 1. Maltais, ML. J Muscu loskelet Neuronal Interact. 2009. 2. Hill, A.V.Series B, Biological Sciences, 1938
Read CV JESSICA RIAL-VAZQUEZECSS Paris 2023: CP-BM16
INTRODUCTION: Low back pain is the most reported work-related musculoskeletal disorder (WMSD), accounting for 21.8M disability adjusted life years (Fan & Straube, 2016). Exoskeletons designed for occupational use have the potential to reduce the risk associated with several work-related risk factors, including awkward postures and handling of heavy loads. Passive exoskeletons don’t require an external power supply and are often lighter and less cumbersome but have been reported to provide less support (Schwartz et al., 2023). Therefore, the aim of this study was to investigate the efficacy of a commercially available back-support passive exoskeleton during a maximal effort lifting task. METHODS: The exoskeleton adopted for this study was the Laevo V2.6 (Laevo Exoskeletons, Schiedam, Netherlands). Adult workers with experience in manual handling and with no history of low back pain in the last year were recruited for the study. After a short warm-up, the participants performed three trials of maximal isometric deadlift each with and without the exoskeleton, using a load cell to measure strength performance. EMG data were collected bilaterally for the iliocostalis, multifidus, biceps femoris and external obliques. RMS and envelope activation peak were computed for each acquired signal. RESULTS: The sample consisted of 10 participants (23,6 ± 3.4 years old), 1RM without the exoskeleton was 173,7 ± 27,4 kg, and 173,3 ± 40,2 with the exoskeleton (p-value = 0.95). No significant differences were found for any muscle’s EMG after applying Holm-Bonferroni correction. CONCLUSION: The exoskeleton provided no support during the selected task, with 6 participants performing worse than without the device. It is possible that the additional torque provided by the exoskeleton was offset by the non-familiarity with the instrument and was masked by the relatively high level of maximal strength expressed by the participants sampled. Future studies could further explore the differences between passive and active exoskeletons. REFERENCES Fan, X., & Straube, S. (2016). Reporting on Work-Related Low Back Pain: Data Sources, Discrepancies and The Art of Discovering Truths. Pain Management, 6(6), 553–559. https://doi.org/10.2217/pmt.16.8 Schwartz, M., Desbrosses, K., Theurel, J., & Mornieux, G. (2023). Biomechanical Consequences of Using Passive and Active Back-Support Exoskeletons during Different Manual Handling Tasks. International journal of environmental research and public health, 20(15), 6468. https://doi.org/10.3390/ijerph20156468
Read CV Francesco FavroECSS Paris 2023: CP-BM16
INTRODUCTION: The influence of wind on archery performance remains underexplored (1). Research suggests that external and holistic attention improves performance over internal focus in experienced athletes (2). However, it remans unclear which types of external focus attention-skill-related (Ext-skill) or environment (Ext-env)-is as beneficial as holistic attention (H). Therefore, this study aimed to investigate the effects of these attentional foci on skilled archers. METHODS: Eight recurve bow archers (4 females; 18.6-21.2 years; 5.5-11.2 years of experience; weekly training 15-25 hours; personal best: 625-662) were recruited. Each archer completed 12 ends of 6 arrows in a simulated competition across 2 sessions per attention condition (144 arrows per condition per archer). After each shot, archers rated wind strength, performance outcome, and overall feeling of the shooting movement (all on a 1-10 scale), corresponding to Ext-env, Ext-skill, and H condition, respectively. For data anlysis, a generalized estimation equation (GEE) model was used to compare across attnetion conditions, with sex as a factor. Furthermore, actual wind strength, phase durations (setup, drawing, aiming, clicker reaction time [CRT]), aiming trjectory in the X and Y axes 0.5 s before and after clicker fall of each shot, and sex were input into separate GEE models to examine respective effects on score for each attention condition. RESULTS: The first GEE model revealed no significant effects of attention condition (p=.426) and sex (p=.400) on score. However, separate analyses on each condition showed better model fit for Ext-env (QIC=1218) compared to Ext-skill (QIC=1389) and H (QIC=1551). All three models revealed that stronger wind negatively affected score (beta = -0.062 to -0.128, p = .033 to <.001). Specifically, in the Ext-env condition, CRT (beta = -0.002, p=.015), aiming trajectory in the Y axis before (beta = -0.017, p=.017) and after clicker fall (beta = -0.038, p=.003), and sex (males > females, p = .02) had effects on score. These results suggested that when archers focused on wind strength, they adjusted their release timing and aiming trajectory in the Y axis. Such adjustments were not found in the Ext-skill or H conditions. CONCLUSION: This study provided evidence that wind strength affects outdoor recurve archery performance. Focusing on wind conditions facilitated adjustments in release timing and vertical aiming, while focusing on skill or movement did not. These findings highlight the potential importance of attentional strategies in optimizing performance under varying environmental conditions in archery.
Read CV Yin-Hua ChenECSS Paris 2023: CP-BM16