Mário J. Costa

The Interaction Between Intra-Cyclic Variation of the Velocity and Mean Swimming Velocity in Young Competitive Swimmers

The aim of this study was to assess the relationship between the intra-cyclic variation of the horizontal velocity (dv) and the velocity of the 4 competitive swimming techniques in young swimmers. 45 young swimmers performed a set of maximal 4 × 25 m (freestyle, backstroke, breaststroke and butterfly stroke) swims with in water start. A speed-meter cable was attached to the swimmers hip. The dv and the swimming velocity were analyzed. Within-subject tests presented significant variations in the dv based on the swimming technique. Post-hoc test revealed significant differences across all pair-wised swimming techniques (P<0.001), except for the comparison between freestyle and backstroke (P=0.98). The dv was higher in the breaststroke, followed by the butterfly, the backstroke and the freestyle. The quadratic models had the best goodness-of-fit and the lower error of estimation for the relationship between the dv and the swimming velocity in all swimming techniques (0.24 ≤ R(2) ≤ 0.51). As a conclusion, there is a non-linear relationship where the increase of swimming velocity leads to a decrease of dv in young competitive swimmers.

Morphometric study for estimation and validation of trunk transverse surface area to assess human drag force on water.

Morphometric Study for Estimation and Validation of Trunk Transverse Surface Area To Assess Human Drag Force on Water The aim of this study was to compute and validate estimation equations for the trunk transverse surface area (TTSA) to be used in assessing the swimmers drag force in both genders. One group of 133 swimmers (56 females, 77 males) was used to compute the estimation equations and another group of 131 swimmers (56 females, 75 males) was used for its validations. Swimmers were photographed in the transverse plane from above, on land, in the upright and hydrodynamic position. The TTSA was measured from the swimmers photo with specific software. Also measured was the height, body mass, biacromial diameter, chest sagital diameter (CSD) and the chest perimeter (CP). With the first group of swimmers, it was computed the TTSA estimation equations based on stepwise multiple regression models from the selected anthropometrical variables. For males TTSA=6.662*CP+17.019*CSD-210.708 (R2=0.32; Ra2=0.30; P<0.01) and for females TTSA=7.002*CP+15.382*CSD-255.70 (R2=0.34; Ra2=0.31; P<0.01). For both genders there were no significant differences between assessed and estimated mean TTSA. Coefficients of determination for the linear regression models between assessed and estimated TTSA were R2=0.39 for males and R2=0.55 for females. More than 80% of the plots were within the 95% interval confidence for the Bland-Altman analysis in both genders.

ANNIE, a tool for integrating ergonomics in the design of car interiors

In this ANNIE project – Applications of Neural Networks to Integrated Ergonomics – BE96-3433, a tool for integrating ergonomics into the design process is developed. This paper presents some features in the current ANNIE as applied to the design of car interiors. A variant of the ERGOMan mannequin with vision is controlled by a hybrid system for neuro-fuzzy simulation. It is trained by using an Elite system for registration of movements. An example of a trajectory generated by the system is shown. A fuzzy model is used for comfort evaluation. An experiment was performed to test its feasibility and it showed very promising results.

Stability of elite freestyle performance from childhood to adulthood

Abstract Stability of athletic performance is important for practitioners and coaches, since it allows the selection of appropriate training methods and prediction of ages for best results. We performed a longitudinal study of 1694 season-best performances of 242 elite-standard swimmers throughout their careers, from 12 to 18 years of age. Mean stability (descriptive statistics and one-way repeated-measures ANOVA, followed by a Bonferroni post-hoc test) and normative stability (Cohens kappa tracking index and the Pearson correlation coefficient) were determined for seven consecutive seasons. Performance improvements in all events were observed (14.36–18.97%). Bonferroni post-hoc tests verified changes in almost all events assessed. Cohens kappa demonstrated low stability (0.17–0.27) in relative performance. Pearson correlations only became high from 15 to 16 years in the 50-m and 100-m events, and from 16 to 17 years in the 200-m, 400-m, and 1500-m events. Our results show that: (a) swimmers should display a substantial improvement (14–19%) to become elite standard as adults, such as at 18 years; (b) 16 is the age at which the ability to predict adult performance increases markedly.

Effects of swim training on energetics and performance

The aim of this study was to determine the effect of several months of training on performance and energetic profile of elite swimmers. 9 elite swimmers were evaluated at 3 different time periods during the 2010-2011 calendar. Swimming performance was assessed based on lists of times for the 200 m freestyle event. An incremental set of 7×200 m swims was applied to obtain the energetic data. Measurements and/or estimations were made for the: velocity at 4 mmol l(-1) of lactate concentrations, highest value of lactate concentrations, maximal oxygen consumption, minimum swimming velocity where the maximal oxygen consumption is reached and total energy expenditure (Etot). The performance and most of the energetic variables assessed presented no significant variations during the study period. The only exception was the Etot with significant differences between all measurements. Correlation coefficients suggested a high stability for all variables. Cohens Kappa tracking index demonstrated high variability in the individual adaptations to training. It is concluded that elite swimmers demonstrate a slight improvement in performance and energetic profile in response to several months of training. Each subject has an individual way of adapting to the training load, combining the different energetic confounders to enhance performance.

The Power Output and Sprinting Performance of Young Swimmers

Abstract Barbosa, TM, Morais, JE, Marques, MC, Costa, MJ, and Marinho, DA. The power output and sprinting performance of young swimmers. J Strength Cond Res 29(2): 440–450, 2015—The aim of this article was to compare swimming power output between boys and girls and to model the relationship between swimming power output and sprinting performance in young swimmers. One hundred young swimmers (49 boys and 51 girls, aged between 11 and 13 years) underwent a test battery including anthropometrics (body mass, height, arm span [AS], and trunk transverse surface area), kinematic and efficiency (velocity, stroke frequency, stroke length, speed fluctuation, normalized speed fluctuation, stroke index, and Froude efficiency), hydrodynamics (active drag and active drag coefficient), and power output (power to overcome drag, power to transfer kinetic energy to water, and external power) assessments and sprinting performance (official 100 freestyle race). All variables but the trunk transverse surface area, stroke length normalize to AS, speed fluctuation, active drag coefficient, and Froude efficiency were significantly higher in boys than in girls with moderate-strong effects. Comparing both sexes but controlling the effect of the sprinting performance, most variables presented a no-significant variation. There was a significant and strong relationship between power output and sprinting performance: y = 24.179x 2.9869 (R 2 = 0.426; standard error of estimation = 0.485; p < 0.001). As a conclusion, boys presented better performances than girls because of their higher power output. There is a cubed relationship between power output and sprinting performance in young swimmers.

Characterization of speed fluctuation and drag force in young swimmers: a gender comparison.

The aim of this study was to compare the speed fluctuation and the drag force in young swimmers between genders. Twenty-three young pubertal swimmers (12 boys and 11 girls) volunteered as subjects. Speed fluctuation was measured using a kinematical mechanical method (i.e., speedo-meter) during a maximal 25-m front crawl bout. Active drag, active drag coefficient and power needed to overcome drag were measured with the velocity perturbation method for another two maximal 25m front crawl bouts with and without the perturbation device. Passive drag and the passive drag coefficient were estimated using the gliding decay velocity method after a maximal push-off from the wall while being fully immersed. The technique drag index was also assessed as a ratio between active and passive drag. Boys presented meaningfully higher speed fluctuation, active drag, power needed to overcome drag and technique drag index than the girls. There were no significant gender differences for active drag coefficient, passive drag and passive drag coefficient. There were positive and moderate-strong associations between active drag and speed fluctuation when controlling the effects of swim velocity. So, increasing speed fluctuation leads to higher drag force values and those are even higher for boys than for girls.

Biomechanics of Competitive Swimming Strokes

Competitive swimming is one of the most challenging sports to perform scientific research. Not only the research of human movement is quite complex, because human beings are not so determinists as other (bio)mechanical systems; but also, assessing human beings in aquatic environment becomes even more as this is not their natural environment and other physical principles have to be considered. On regular basis, for human movement analysis, including the ones made on aquatic environments, experimental and numerical methods are used. Experimental methods are characterized by attaching bio-sensors to the subjects being analyzed, acquiring the biosignal and thereafter processing it. Numerical methods are characterized by the introduction of selected input data, processing data according to given mechanical equations and thereafter collecting the output data. Both methods groups aim to perform kinematics analysis, kinetics analysis, neuromuscular analysis and anthropometrical/inertial analysis. These method groups are also used for biomechanical analysis of competitive swimming. A swimming event can be decomposed in four moments or phases: (i) the starting phase; (ii) the swimming phase; (iii) the turning phase and; (iv) the finishing phase. During any swimming event, a swimmer spends most of his/her absolute or relative time in the swimming phase. Therefore, the swimming phase is the most (but not the only one) determinant moment of the swimming performance. In this sense, a large part of the biomechanical analysis of competitive swimming is dedicated to the four competitive swimming strokes: (i) the Front Crawl; (ii) the Backstroke; (iii) the Breaststroke and; (iv) the Butterfly stroke. The aim of this chapter has two folds: (i): to perform a biomechanical characterization of the four competitive swimming strokes, based on the kinematics, kinetics and neuromuscular analysis; (ii) to report the relationships established between all the domains and how it might influence the swimming performance.

Physiological Adaptations to Training in Competitive Swimming: A Systematic Review

Abstract The purpose of this systematic review was to summarize longitudinal studies on swimming physiology and get implications for daily practice. A computerized search of databases according to the PRISMA statement was employed. Studies were screened for eligibility on inclusion criteria: (i) present two testing points; (ii) on swimming physiology; (iii) using adult elite swimmers; (iv) no case-studies or with small sample sizes. Two independent reviewers used a checklist to assess the methodological quality of the studies. Thirty-four studies selected for analysis were gathered into five main categories: blood composition (n=7), endocrine secretion (n=11), muscle biochemistry (n=7), cardiovascular response (n=8) and the energetic profile (n=14). The mean quality index was 10.58 ± 2.19 points demonstrating an almost perfect agreement between reviewers (K = 0.93). It can be concluded that the mixed findings in the literature are due to the diversity of the experimental designs. Micro variables obtained at the cellular or molecular level are sensitive measures and demonstrate overtraining signs and health symptoms. The improvement of macro variables (i.e. main physiological systems) is limited and may depend on the athletes’ training background and experience.

Growth influences biomechanical profile of talented swimmers during the summer break

This study aimed to analyse the effect of growth during a summer break on biomechanical profile of talented swimmers. Twenty-five young swimmers (12 boys and 13 girls) undertook several anthropometric and biomechanical tests at the end of the 2011–2012 season (pre-test) and 10 weeks later at the beginning of the 2012–2013 season (post-test). Height, arm span, hand surface area, and foot surface area were collected as anthropometric parameters, while stroke frequency, stroke length, stroke index, propelling efficiency, active drag, and active drag coefficient were considered as biomechanical variables. The mean swimming velocity during an all-out 25 m front crawl effort was used as the performance outcome. After the 10-week break, the swimmers were taller with an increased arm span, hand, and foot areas. Increases in stroke length, stroke index, propelling efficiency, and performance were also observed. Conversely, the stroke frequency, active drag, and drag coefficient remained unchanged. When controlling the effect of growth, no significant variation was determined on the biomechanical variables. The performance presented high associations with biomechanical and anthropometric parameters at pre-test and post-test, respectively. The results show that young talented swimmers still present biomechanical improvements after a 10-week break, which are mainly explained by their normal growth.