This study aimed to assess the effects of post-activation potentiation in the strength related variables of a kick start. Thirteen competitive swimmers performed three kick starts after a standardized warm up (denoted USUAL) and another after inducing post-activation through five isotonic repetitions on an eccentric flywheel (denoted PAP). A T-test was used to quantify differences between USUAL and PAP warm up. The best trial of each subject achieved by natural conditions (denoted PEAK) was compared with data obtained after PAP. An instrumented starting block with independent triaxial force plates, collected the strength variables related with the impulse at take off. Improvements in the vertical components of force were observed after PAP compared with USUAL, meanwhile no differences were detected on the horizontal components of it. The velocity at take off was higher after PAP compared with USUAL (4.32 ± 0.88 vs 3.93 ± 0.60 m*s-1; p = 0.02). No differences in force or velocity were detected comparing PAP with PEAK (4.13 ± 0.62 m*s-1, p = 0.11). The PAP warm-up increased vertical force and it was transferred to a higher resultant velocity at take-off. This improvement would equal the best result possible obtained in natural conditions after some trials.

The relationships between the start time and kinematic, kinetic and electromyographic data were examined in order to establish the common features of an effective backstroke swimming start. Complementarily, different starting positions were analysed to identify the parameters that account for the fastest backstroke start time under different constraints. 6 high-level swimmers performed 4×15 m maximal trials of each start variants with different feet position: parallel and entirely submerged (BSFI) and above water surface (BSFE), being monitored with synchronized dual-media image, underwater platform plus handgrip with a load cell, and eletromyographic signal of Rectus Femoris and Gastrocnemius Medialis. Mean and SD values of start time for BSFI and BSFE were 2.03±0.19 and 2.14±0.36 s, respectively. In both starts, high associations (r>=0.75, p<0.001) were observed between start time and centre of mass resultant average velocity at glide phase and horizontal impulse at take-off for BSFI, and centre of mass horizontal position at the start signal for BSFE. It was concluded that the greater impulse during the take-off and its transformation into a fast underwater movement are determinant to decrease the start time at BSFI. Regarding BSFE, a greater centre of mass pool-wall approximation might imply a flatter take-off angle, compromising underwater velocity and starting performance.

This study assessed accuracy of surface and underwater 3D reconstruction of a calibration volume with and without homography. A calibration volume (6000 × 2000 × 2500 mm) with 236 markers (64 above and 88 underwater control points—with 8 common points at water surface—and 92 validation points) was positioned on a 25 m swimming pool and recorded with two surface and four underwater cameras. Planar homography estimation for each calibration plane was computed to perform image rectification. Direct linear transformation algorithm for 3D reconstruction was applied, using 1600000 different combinations of 32 and 44 points out of the 64 and 88 control points for surface and underwater markers (resp.). Root Mean Square (RMS) error with homography of control and validations points was lower than without it for surface and underwater cameras (P≤0.03). With homography, RMS errors of control and validation points were similar between surface and underwater cameras (P≥0.47). Without homography, RMS error of control points was greater for underwater than surface cameras (P≤0.04) and the opposite was observed for validation points (P≤0.04). It is recommended that future studies using 3D reconstruction should include homography to improve swimming movement analysis accuracy.

Purpose:: To conduct a biophysical analysis of the factors associated with front-crawl performance at moderate and severe swimming intensities, represented by anaerobic-threshold (vAnT) and maximal-oxygen-uptake (vV̇O₂max) velocities.Methods:: Ten high-level swimmers performed 2 intermittent incremental tests of 7 × 200 and 12 × 25 m (through a system of underwater push-off pads) to assess vAnT, and vV̇O₂max, and power output. The 1st protocol was videotaped (3D reconstruction) for kinematic analysis to assess stroke frequency (SF), stroke length (SL), propelling efficiency (η_P), and index of coordination (IdC). V̇O₂ was measured and capillary blood samples (lactate concentrations) were collected, enabling computation of metabolic power. The 2nd protocol allowed calculating mechanical power and performance efficiency from the ratio of mechanical to metabolic power.Results:: Neither vAnT nor vV̇O₂max was explained by SF (0.56 ± 0.06 vs 0.68 ± 0.06 Hz), SL (2.29 ± 0.21 vs 2.06 ± 0.20 m), η_P (0.38 ± 0.02 vs 0.36± 0.03), IdC (–12.14 ± 5.24 vs –9.61 ± 5.49), or metabolic-power (1063.00 ± 122.90 vs 1338.18 ± 127.40 W) variability. vV̇O₂max was explained by power to overcome drag (r = .77, P ≤ .05) and η_P (r = .72, P ≤ .05), in contrast with the nonassociation between these parameters and vAnT; both velocities were well related (r = .62, P ≤ .05).Conclusions:: The biomechanical parameters, coordination, and metabolic power seemed not to be performance discriminative at either intensity. However, the increase in power to overcome drag, for the less metabolic input, should be the focus of any intervention that aims to improve performance at severe swimming intensity. This is also true for moderate intensities, as vAnT and vV˙O2max are proportional to each other.

Swimming and training are carried out with wide variability in distances and intensities. However, oxygen uptake kinetics for the intensities seen in swimming has not been reported. The purpose of this study was to assess and compare the oxygen uptake kinetics throughout low-moderate to severe intensities during incremental swimming exercise. We hypothesized that the oxygen uptake kinetic parameters would be affected by swimming intensity. Twenty male trained swimmers completed an incremental protocol of seven 200-m crawl swims to exhaustion (0.05 m·s⁻¹ increments and 30-s intervals). Oxygen uptake was continuously measured by a portable gas analyzer connected to a respiratory snorkel and valve system. Oxygen uptake kinetics was assessed using a double exponential regression model that yielded both fast and slow components of the response of oxygen uptake to exercise. From low-moderate to severe swimming intensities changes occurred for the first and second oxygen uptake amplitudes (P ≤ 0.04), time constants (P = 0.01), and time delays (P ≤ 0.02). At the heavy and severe intensities, a notable oxygen uptake slow component (>255 mL·min⁻¹) occurred in all swimmers. Oxygen uptake kinetics whilst swimming at different intensities offers relevant information regarding cardiorespiratory and metabolic stress that might be useful for appropriate performance diagnosis and training prescription.

Cardiorespiratory response in swimming has been used to better understand aerobic performance, especially by assessing oxygen uptake (VO₂). The current study aimed to compare different VO₂ time-averaging intervals throughout low to severe swimming intensities, hypothesizing that VO₂ values are similar for different time averages at low to moderate and heavy swimming intensities, but not for the severe domain. 20 male trained swimmers completed an incremental protocol of 7×200 m until exhaustion (0.05 m/s increments and 30 s intervals). VO₂ was measured by a portable gas analyser connected to a snorkel system. 6 time average intervals (breath-by-breath, 5, 10, 15, 20 and 30 s) were compared for all the protocol steps. Breath-by-breath and 5 s average exhibited higher VO₂ values than averages≥10 s for all swimming intensities (P≤0.02; partial η²≤0.28). VO₂ values did not differ between 10, 15, 20 and 30 s averages throughout the incremental protocol (P>0.05; partial η²≤0.05). Furthermore, 10 and 15 s averages showed the lowest VO₂ mean difference (0.19 mL^·kg^−1 ·min⁻¹). For the 6 time average intervals analysed, 10 and 15 s averages were those that showed the lowest changes on VO₂ values. We recommended the use of 10 and 15 s time averaging intervals to determine relevant respiratory gas exchange parameters along a large spectrum of swimming intensities.