Biomechanics and Medicine in Swimming XI

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for displacing the body over a given unit of distance (Zamparo et al, 2005). Furthermore, it is accepted as an important bioenergetical determinant of swimming performance (Wakayoshi et al, 1995; Kjendlie et al., 2004; Fernandes et al., 2006). However, the body of scientific literature needs approaches on the relationships between the IdC and the C in trying to understand how these two variables may be connected. The present study aimed at assessing relationships between the IdC and the C in front crawl, especially at intensities ranging between ~70 % and 100% of the maximal oxygen consumption ( V � O 2 max). We hypothesised that if velocity is controlled, IdC and C are inversely related. Methods Seven high-level swimmers (17.0 ± 1.8 years; 168.0 ± 8.8 cm; 58.4 ± 8.2 kg) participant in national swimming championships were tested. Mean (± SD) main physiological characteristics were: 18.0 (6.9) % of fat mass, 54.9 (10.1) ml.kg -1 .min -1 of V � O 2 max and 7.5 (2.4) of blood lactate concentrations ([La - ]) at intensities corresponding to V � O 2 max. In an indoor 25 m swimming pool, the participants performed an intermittent incremental protocol, with increments of 0.05 m·s -1 each 200 m stage (and 30 s intervals), until exhaustion (Fernandes et al., 2003). Initial velocity was established according to the individual level of fitness and was set at the swimmer’s individual performance on the 400 m freestyle minus seven increments of velocity. Swimming velocity was controlled using a visual pacer (TAR 1.1, GBK-electronics, Aveiro, Portugal) with successive flashing lights, 2.5 m apart, on the bottom of the pool. V � O 2 was measured through direct breath-by-breath oximetry (K4 b 2 , Cosmed, Rome, Italy) connected to the swimmer by a respiratory snorkel and valve system (Keskinen et al., 2003). Capillary blood samples (25 µl) for [La - ] analysis were collected from the earlobe at rest, in the 30 s rest interval, at the end of exercise and during the recovery period (YSI1500L- Sport auto-analyser, Yellow Springs Incorporated, Ohio, USA). The C was calculated by dividing total energy expenditure (Ė) by velocity (v) and converted to SI units, were 1 mlO 2 is equivalent to 20.1 J (Zamparo et al., 2005; Fernandes et al., 2006): C = Ė /v (1) The Ė corrected for body mass was calculated using the V � O 2 net (difference between the value measured in the end of the stage and the rest value), and the blood lactate net (difference between the value measured in two consecutive stages) transformed into V � O 2 equivalents using a 2.7mlO 2 kg -1 mmol -1 proportionality constant and by Equation (2) (cf. Fernandes et al., 2006) Ė = V� O2net + [La-]net (2) Two video cameras (JVC GR-SX1 SVHS and JVC GR-SXM 25 SVHS) were fixed on the lateral wall of the pool at a 10 m distance perpendicular to the swimmers’ plane of movement. The cameras were connected to a double entry and edited on a mixing table (Panasonic Digital Mixer WJ-AVE55 VHS), providing a dual-media image (Panasonic AG 7355), below and above the water surface (Vilas-Boas et al., 2006), at a frequency of 50 Hz (1:250/s shutter speed). For each step of the incremental protocol, two arm strokes were analysed in every 50 m of the 200 m. Arm stroking coordination was obtained through IdC (Chollet et al., 2000), being each arm stroke broken down into four phases: (i) entry and catch (corresponding to the time between the entry of the hand into the water and the beginning of its backward movement); (ii) pull (corresponding to the time between the beginning of the hand’s backward movement and its arrival in a vertical plane to the shoulder); (iii) push (corresponding to the time from the position of the hand below the shoulder to its release from the water) and (iv) recovery (corresponding to the point of water release to water re-entry of the arm, i.e., the above water phase). The duration of each phase was measured for each arm-stroke cycle with a precision of 0.02 s. The duration of the propulsive phases was the addition of the pull and the push phases, and the duration of the non-propulsive phases was obtained by the sum of chaPter2.Biomechanics the catch and the recovery phases (the duration of a complete arm-stroke was the sum of the propulsive and non-propulsive phases). The IdC was calculated as the time gap between the propulsion of the two arms as a percentage of the duration of the complete arm stroke cycle. Higher negative percentage values expressed an evident discontinuity in the inter-arm propulsion, tending to IdC=0% as the time gap was diminishing. Mean ± SD computations for descriptive analysis were obtained in each stage for all variables (all data were checked for distribution normality with the Shapiro-Wilk test). Pearson correlation coefficient and partial correlation were applied. Level of significance was established at 5%. results The mean ± SD values of velocity, % V � O 2 max, C, and IdC, obtained in each step during the intermittent incremental test, are presented in Table 1. An increase of swimming intensity implies an increase of both C and IdC (Table 1). Table 1. Mean values of velocity, % V� O2max, IdC and C obtained in each 200 m step of the incremental protocol (n=7). Step velocity (m·s-1 ) % V� O2max C ( J·kg-1 ·m-1 1 1.15 ± 0.1 72.1 ± 8.7 ) 9.4 ± 2.5 IdC (%) -12.5 ± 2.5 2 1.20 ± 0.1 76.5 ± 9.1 10.3 ± 2.8 -12.1 ± 2.7 3 1.25 ± 0.1 77.8 ± 5.3 10.1 ± 3.0 -11.8 ± 2.6 4 1.30 ± 0.1 85.5 ± 3.3 11.5 ± 3.2 -10.9 ± 2.6 5 1.35 ± 0.1 90.9 ± 3.2 12.7 ± 2.8 -9.7 ± 2.7 6 1.40 ± 0.1 97.3 ± 3.2 13.7 ± 2.4 -8.2 ± 2.7 7 1.45 ± 0.1 100.0 ± 0.0 14.0 ± 4.2 -6.8 ± 2.5 The relationships between velocity and C, and velocity and IdC are shown in Fig. 1 (left panel), being possible to observe a high correlation value between these variables (r=0.98 and r=0.99, respectively, both for p
BiomechanicsandmedicineinswimmingXi dIscussIon Despite a previous case study by Morais et al. (2008), and a study that was conducted with sprint swimmers performing at incremental sub-maximal intensities (Komar et al., 2010), the present study is the first that aimed to relate IdC and C in front crawl. The present results agree with both the referred studies, finding positive and significant r values between both variables. In this study, however, it was confirmed that this is true for velocity values ranging from very low to heavy exercise intensities (~ V � O2max). All swimmers reached their maximal aerobic power during the incremental protocol, which was assured by traditional physiological criteria (cf. Fernandes et al., 2003). Subjects presented V � O2max mean values similar to those described in the literature for experienced competitive swimmers (Wakayoshi et al, 1995; Rodriguez and Mader, 2003; Fernandes et al., 2006). The obtained mean values of [La - ]max are in accordance with the literature for intensities of exercise corresponding to V � O2max (Fernandes et al., 2003; Rodriguez and Mader, 2003; Fernandes et al., 2006). Along the incremental protocol it was observed that an increase in the swimming intensity led to an increase of the IdC. This is consistent with previous studies that showed a raise of IdC values with increasing race paces, namely from 1500/800 to 50 m freestyle (Chollet et al., 2000; Seifert et al., 2004; Seifert et al., 2007). This increase seems to be a strategy that swimmers use to overcome higher active drag that is related with higher swimming velocity (Seifert et al., 2004). These data also reveals that swimmers changed their arm stroke coordination, from moderate to heavy exercise intensities, in order to be able to reach higher swimming velocity. In fact, this shift in IdC from a catch-up pattern to a pattern closer to the opposition coordination mode, aiming to achieve higher propulsive continuity at V � O 2 max swimming intensity, was also described before (Chollet et al., 2000; Seifert et al., 2004; Seifert et al., 2007). The values of IdC obtained in the present study were similar to those obtained in the previously mentioned studies and it did not reach positive values since IdC>0% only occurs after 93% of the swimmers maximal velocity, which corresponds to the 100 m maximal velocity (Seifert et al., 2004). Such as the IdC, the C values also increased with velocity. This fact has been described before for front crawl stroke with similar C values (Zamparo et al., 2005; Morais et al., 2008; Komar et al, 2010), and seems to be justified by the increasing power output (P = Dv) necessary to overcome drag (D), and presumably by the increase in internal work associated with a higher stroke rate. The main finding of this study was the very high direct relationship between IdC and C, which is, as stated, in accordance with previous studies in swimming, but also in human terrestrial locomotion, namely in the walk-run transition (cf. Seifert et al., 2007). Studies have been carried out in order to relate the C with other biomechanical parameters. Barbosa et al. (2008) showed that the C is highly related to stroke parameters, namely with stroke rate and stroke length, while Chatard et al. (1990) showed that C is dependent on swimming technique. In this sense, after observing that the IdC, a coordinative parameter, is strongly related with C, our results seems to be consistent with literature (Alberty et al., 2005), indicating that the mode of coordination might be an individual response to physiological constraints associated to the task. However, despite the agreement of the results of other approaches, the simple analysis of the r value obtained between IdC and C shows that the C increase with the increased continuity of technique (higher IdC), which seems to be paradoxal, being probably explainable by the fact that both parameters are strongly influenced by velocity (as shown in fig. 1). In accordance, we decided to analyse the partial correlation of the two variables removing the effect of velocity. Surprisingly, IdC and C did not correlate significantly (r=0.42, p=0.40). Furthermore, the obtained r value remains positive, while it was theoretically expected a negative relationship. Indeed, we hypothesised that, controlling the velocity effect, the reduction of propulsive discontinuities should allow the front crawl technique to become more economical, instead of implying higher energy costs. Samples with higher number of subjects as well as other factors (e.g. intracyclic velocity variation) should be searched to explain these apparently conflicting findings. Particularly, we recommend to study IdC and C at the same swimming 76 velocity performed in different subjects, and in the same subjects manipulating coordination. reFerences Alberty, M., Sidney, M., Huot-Marchand, F., Hespel, J. M. & Pelayo, P. (2005) Intracyclic velocity variations and arm coordination during exhaustive exercise in front crawl stroke. Int J Sports Med, 26(6), 471-5. Barbosa, T. M., Fernandes, R. J., Keskinen, K. L. & Vilas-Boas, J. P. (2008). The influence of stroke mechanics into energy cost of elite swimmers. Eur J Appl Physiol, 103(2), 139-49. Chatard, J. C., Collomp, C., Maglischo, E. & Maglischo, C. (1990). Swimming skill and stroking characteristics of front crawl swimmers. Int J Sports Med, 11(2), 156-61. Chollet, D., Chalies, S. & Chatard, J. C. (2000). A new index of coordination for the crawl: description and usefulness. Int J Sports Med, 21(1), 54-9. Fernandes, R. J., Cardoso, C. S., Soares, S. M., Ascensão, A., Colaco, P. J. & Vilas-Boas, J. P. (2003). Time limit and VO2 slow component at intensities corresponding to VO2max in swimmers. Int J Sports Med, 24(8), 576-81. Fernandes, R. J., Billat, V. L., Cruz, A. C., Colaço, P. J., Cardoso, C. S. & Vilas-Boas, J. P. (2006). Does net energy cost of swimming affect time to exhaustion at the individual’s maximal oxygen consumption velocity? J Sports Med Phys Fitness, 46(3), 373-80. Kjendlie, P. L., Ingjer, F., Stallman, R. & Stray-Gundersen, J. (2004). Factors affecting swimming economy in children and adults. Eur J Appl Physiol, 93, 1164-8. Komar, J., Leprêtre, P. M., Alberty, M., Vantorre, J., Fernandes, R.J., Hellard, et al. (2010). Effect of Increasing Energy Cost on Arm Coordination at Different Exercise Intensities in Elite Sprint Swimmers. In: Kjendlie, P.L., Stallman, R.K. & Cabri, J. (eds.). Biomechanics and Medicine in Swimming XI. Oslo. In Press. Keskinen, K. L. & Komi, P. V. (1993). Stroking characteristics of front crawl swimming during exercise. J Appl Biomech, 9, 219-26. Keskinen, K. L., Rodríguez, F. A. & Keskinen, O. P. (2003). Respiratory snorkel and valve system for breath-by-breath gas analysis in swimming. Scand J Med Sci Sports, 13, 322-29. Morais, P., Vilas-Boas, J. P., Seifert, L., Chollet, D., Keskinen, K.L. & Fernandes, R. (2008). Relationship between energy cost and the index of coordination in crawl - a pilot study. J Sport Sci, 26(Suppl. 1), 11. Rodriguez, F. A. & Mader, A. (2003). Energy metabolism during 400 and 100m crawl swimming: Computer simulation based on free swimming measurements. In: Chatard, J. C. (ed.). Biomechanics and Medicine in Swimming IX. Saint-Étienne: Publications de l’Université de Saint- Étienne, 373-378. Seifert, L., Chollet, D. & Bardy, B. G. (2004). Effect of swimming velocity on arm coordination in the front crawl: a dynamic analysis. J Sports Sci, 22(7), 651-60. Seifert, L., Chollet, D. & Rouard, A. (2007). Swimming constraints and arm coordination. Hum Mov Sci, 26(1), 68-86. Vilas-Boas, J. P. (1996). Speed fluctuations and energy cost with different breaststroke techniques, In: Troup J, Hollander AP, Strass D (eds.). Biomechanics and Medicine in Swimming VII. London: E&FN SPON, 167- 171. Vilas-Boas, J. P., Cunha, P., Figueiras, T., Ferreira, M. & Duarte, J. A. (1996). Movement analysis in simultaneous swimming techniques. In: Wilke K, Daniel K, Hoffmann U, Klauck, J (eds.). Symposiumsbericht Kolner Schwimmsportage. Bockenem: Sport Fahnemann Verlag, 95-103. Wakayoshi, K., D’Acquisto, L., Cappaert, J. & Troup, J. (1995). Relationship between oxygen uptake, stroke rate and swimming velocity in competitive swimming. Int J Sports Med, 16(1), 19-23. Zamparo, P., Pendargast, D., Mollendorf, J., Termin, A. & Minetti, A. (2005). An Energy Balance of Front Crawl. Eur J Appl Physiol, 94, 134-44. AcKnoWledGeMents This study was supported by grant: PTDC/DES/101224/2008
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Pahlen Norge AS Pahlen Norge AS Cha
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