Because of the specificity of the physiological demand in swimming only sports-specific test methods provide meaningful results within the framework of performance diagnosis and training control (Holmer 1992). The main test procedures are lactate diagnostics (Pyne et al. 2001) or spiroergometry (Capelli et al. 1998). The lactate performance diagnostics can mainly assess the capability of the metabolism. Spirometric test methods can determine the maximal oxygen uptake as the gross criterion for the aerobic capacity. Apart from this, however, by determining the alteration of the oxygen uptake from one exercise step to the next (DeltaVO2/Deltav), the spiroergometry can assess the swimming economy and therefore the swimming technique. The application of the "breath by breath" spirometry method with the possibility of an online registration of data as well as the use of a swim flume which facilitates a very high standardization level are advantageous. It is also interesting to see to what existent the results in the swim flume can be transferred to pool conditions. Therefore, the aim of the present study was to compare physiological parameters and economy between swimming in the flume and free swimming. Methods In a randomized manner 18 swimmers (13 male, 5 female; age: 23.2+/-3.6 yrs.) performed 200m-step tests (beginning at 0.95 m/s, increasing 0.05 m/s each exercise step, 1-minute break between each exercise step) until exhaustion in the flume (f), 25m (25) and 50m (50) pool. A two-way ANOVA was performed to compare variables between the 3 different test settings. The Tuckey and Scheffe test were used for post hoc analysis. Significance was set at p<0.05. Results On maximal exercise steps there were no statistically significant differences in heart rate, stroke rate, lactate and oxygen uptake (determined by the rebreathing method via exponential backward extrapolation). At submaximal workloads, lactate, VO2 (both accounting for power output Pi), heart rate and stroke rate were not different in 25 and 50 but were significantly higher in the pool situations than f (2way-ANOVA) (Fig.1, Fig.2). A significantly higher number of steps were performed in the flume compared to the pool situations (25: 8.0+/- 1.9; 50: 7.7+/-1.2; f: 9.7+/-1.5; 1way-ANOVA). On each exercise step performance time was longest in f and shortest in 25. Pi in f was significantly lower than in free swimming. By means of the equation Pi=(Axv3)/(egxep) (A=drag factor, ep=propelling efficiency, eg=gross efficiency) can be derived that swimming in the flume is more economical than free swimming. Discussion/Conclusion The difference in performance time can be attributed to the time saving turns. The higher economy in flume swimming can be explained by a smaller loss of kinetic energy towards the water due to the water movement and by a lower degree of static elements although different stroke technique and the creation of vortices aggravate the swimming in a swim flume.
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