Gabriele Mascherini, Cristian Petri, Elena Ermini, Angelo Pizzi, Antonio Ventura and Giorgio Galanti
101 Sport Edition, Akern, Florence, Italy). Resistance (RZ, Ω) was the opposition to the flow of an alternating current, at any current frequency, through intra and extracellular ionic solutions and reflected the amount of body water, while Reactance (XC, Ω) was the dielectric or capacitive component of cell membranes and organelles, and tissue interfaces. Starting from these variables, the estimate of the following body compartments was derived: body cellular mass (BCM in kg), extracellular mass (ECM in kg), total body water (TBW in L), extracellular water (ECW
Lucia Mala, Tomas Maly, František Zahalka, Vaclav Bunc, Ales Kaplan, Radim Jebavy and Martin Tuma
The goal of this study was to identify and compare body composition (BC) variables in elite female athletes (age ± years): volleyball (27.4 ± 4.1), softball (23.6 ± 4.9), basketball (25.9 ± 4.2), soccer (23.2 ± 4.2) and handball (24.0 ± 3.5) players. Fat-free mass (FFM), fat mass, percentage of fat mass (FMP), body cell mass (BCM), extracellular mass (ECM), their ratio, the percentage of BCM in FFM, the phase angle (α), and total body water, with a distinction between extracellular (ECW) and intracellular water, were measured using bioimpedance analysis. MANOVA showed significant differences in BC variables for athletes in different sports (F60.256 = 2.93, p < 0.01, η2 = 0.407). The results did not indicate any significant differences in FMP or α among the tested groups (p > 0.05). Significant changes in other BC variables were found in analyses when sport was used as an independent variable. Soccer players exhibited the most distinct BC, differing from players of other sports in 8 out of 10 variables. In contrast, the athletes with the most similar BC were volleyball and basketball players, who did not differ in any of the compared variables. Discriminant analysis revealed two significant functions (p < 0.01). The first discriminant function primarily represented differences based on the FFM proportion (volleyball, basketball vs. softball, soccer). The second discriminant function represented differences based on the ECW proportion (softball vs. soccer). Although all of the members of the studied groups competed at elite professional levels, significant differences in the selected BC variables were found. The results of the present study may serve as normative values for comparison or target values for training purposes.
Krzysztof Przednowek, Janusz Iskra, Krzysztof Wiktorowicz, Tomasz Krzeszowski and Adam Maszczyk
– an initial study. In: Proceedings 28th European Conference on Modelling and Simulation ECMS , 382-387; 2014 Lapkova D Pluhacek M Kominkova Oplatkova Z Adamek M. Using artificial neural network for the kick techniques classification – an initial study Proceedings 28th European Conference on Modelling and Simulation ECMS 382 387 2014
Maszczyk A, Roczniok R, Waśkiewicz Z, Czuba M, Mikołajec K, Zając A, Stanula A. Application of regression and neural models to predict competitive swimming performance. Percept Motor Skill , 2012; 114(2): 610–626 10.2466/05.10.PMS