Intensity control in swim training by means of the individual anaerobic threshold

Concurrent sprint and aerobic training in swimming: Influence of exercise sequence on physiological responses and perceived exertion

The study examined the effect of aerobic and sprint sets sequence on physiological responses and perceived exertion during concurrent training sessions. Twelve male highly trained swimmers performed four sessions in randomized order, using combinations of the following training sets: (a) lactate threshold training (8 × 200-m at a speed corresponding to lactate threshold with 30-s recovery; LT), (b) high-intensity aerobic training (8 × 100-m at the maximal aerobic speed with 30-s recovery; MAS) and (c) repeated-sprints training (8 × 25-m repeated sprints with 2-min recovery; SPR). The four combinations used were as follows: LT-SPR, SPR-LT, MAS-SPR, SPR-MAS. Blood lactate (BL), pH, base excess (BE), bicarbonate, heart rate (HR), HR variability, objective [training impulse (iTRIMP)] and subjective training load [session's rating of perceived exertion (sRPE)] were measured. Between session pH and BE were no different, but mean BL was higher in sessions starting with repeated sprints compared with the reverse order (SPR-LT: 6.3 ± 3.6, LT-SPR: 5.3 ± 3.7 mmol·L-1, p = 0.03; SPR-MAS: 7.2 ± 3.9, MAS-SPR: 6.0 ± 3.7 mmol·L-1, p = 0.05). Bicarbonate in SPR-LT was lower compared with LT-SPR (p = 0.03). sRPE, but not iTRIMP, was higher in sessions starting with SPR compared with the reverse order (p = 0.02). Anaerobic-aerobic set sequence, compared with the reverse order, augments BL response and increases perceived training load but not the training impulse.

Lactate threshold evaluation in swimming using a sweat lactate sensor: A prospective study

Since assessing aerobic capacity is key to enhancing swimming performance, a simple and widely applicable technology should be developed. Therefore, we aimed to noninvasively visualize real-time changes in sweat lactate (sLA) levels during swimming and investigate the relationship between lactate thresholds in sweat (sLT) and blood (bLT). This prospective study included 24 university swimmers (age: 20.7 s ± 1.8 years, 58% male) who underwent exercise tests at incremental speeds with or without breaks in a swimming flume to measure heart rate (HR), bLT, and sLT based on sLA levels using a waterproof wearable lactate sensor attached to the dorsal upper arm on two different days. The correlation coefficient and Bland-Altman methods were used to verify the similarities of the sLT with bLT and personal performance. In all tests, dynamic changes in sLA levels were continuously measured and projected onto the wearable device without delay, artifacts, or contamination. Following an initial minimal current response, with increasing speed the sLA levels increased substantially, coinciding with a continuous rise in HR. The speed at sLT strongly correlated with that at bLT (p < 0.01 and r = 0.824). The Bland-Altman plot showed a strong agreement (mean difference: 0.08 ± 0.1 m/s). This prospective study achieved real-time sLA monitoring during swimming, even with vigorous movement. The sLT closely approximated bLT; both were subsequently validated for their relevance to performance.

Physiological Responses and Swimming-Performance Changes Induced by Altering the Sequence of Training Sets

PURPOSE

Interval-training sets may be applied in a different sequence within a swimming training session. The aim of this study was to investigate the effect of different set sequences on performance and physiological responses in a training session.

METHODS

Twelve highly trained male swimmers performed 4 sessions in randomized order. Each session included a different combination of 2 training sets: set A-set C, set C-set A, set B-set C, or set C-set B. Set A consisted of 8 × 200 m at speed corresponding to lactate threshold (30-s recovery), set B included 8 × 100 m at maximum aerobic speed (30-s recovery), and set C included 4 × 50-m all-out swimming (2-min recovery). Performance and physiological responses (lactate concentration, pH, base excess, bicarbonate, heart rate, and heart-rate variability) were measured.

RESULTS

Performance in each set was similar between sessions irrespective of set sequence. Blood lactate, heart rate, and acid-base responses during set C were similar in all sessions, but blood lactate was higher in sets A and B during C-A and C-B sessions (P = .01). The overall blood lactate and acid-base response was higher in C-A and C-B sessions compared with A-C and B-C sessions, respectively (P = .01). Heart-rate variability in each set, separately as well as the overall session effect, did not differ and was thus independent to the set sequence applied.

CONCLUSIONS

Training sessions including all-out swimming as a first set increase the magnitude of metabolic responses to the subsequent aerobic-dominated training set.

Effects of Training Sets Sequence on Swimming Performance, Training Load and Physiological Responses

The study examined the effect of set sequence on performance and physiological responses in a training session and in each set separately. Twelve male swimmers performed four sessions in a randomized order, including a combination of two training sets: (i) set A-set C, (ii) set C-set A, (iii) set B-set C, (iv) set C-set B. Set A consisted of 8 × 200 m at a speed corresponding to lactate threshold (30 s recovery), set B included 8 × 100 m at the maximal aerobic speed (30 s recovery), set C included 8 × 50 m sprints at 95% of the maximum 50 m speed (30 s recovery). Speed, blood lactate, pH, base excess, bicarbonate and heart rate variability (HRV) were measured. Speed in each set was similar between sessions irrespective of set sequence (p > 0.05). Physiological responses during sets A and C were similar in all sessions (p > 0.05). In set B, when applied after set C, the metabolic response increased, and HRV decreased (p < 0.05). Overall, session biochemical disturbance was higher when set C was applied before sets A and B (p < 0.05). The magnitude of metabolic and HRV responses in a set conducted at maximal aerobic speed, but not at lactate threshold intensity, is increased when applied after sprint intervals.

Muscle Oxygenation, Heart Rate, and Blood Lactate Concentration During Submaximal and Maximal Interval Swimming

This study aimed to determine the relationship between three testing procedures during different intensity interval efforts in swimming. Twelve national-level swimmers of both genders executed, on different occasions and after a standardized warm-up, a swimming protocol consisting of either a submaximal (Submax: 8 efforts of 50 m) or a maximal interval (Max: 4 efforts of 15 m), followed by two series of four maximal 25 m efforts. Near-infrared spectroscopy in terms of muscle oxygen saturation (SmO₂), heart rate (HR), and blood lactate concentration (BLa) were analyzed at three testing points: after the Submax or the Max protocol (TP₁), after the 1st 4 × 25-m (TP₂), and after the 2nd maximal 4 × 25-m set (TP₃). BLa and HR showed significant changes during all testing points in both protocols (P ≤ 0.01; ES range: 0.45–1.40). SmO₂ was different only between TP₁ and TP₃ in both protocols (P ≤ 0.05–0.01; ES range: 0.36–1.20). A large correlation during the Max protocol between SmO₂ and HR (r: 0.931; P ≤ 0.01), and also between SmO₂ and BLa was obtained at TP₁ (r: 0.722; P ≤ 0.05). A range of moderate-to-large correlations was revealed for SmO₂/HR, and BLa/HR for TP₂ and TP₃ after both protocols (r range: 0.595–0.728; P ≤ 0.05) were executed. SmO₂ is a novel parameter that can be used when aiming for a comprehensive evaluation of competitive swimmers' acute responses to sprint interval swimming, in conjunction with HR and BLa.

The Maximal Lactate Steady State Workload Determines Individual Swimming Performance

The lactate threshold (LT) and the strongly related maximal lactate steady state workload (MLSS_W) are critical for physical endurance capacity and therefore of major interest in numerous sports. However, their relevance to individual swimming performance is not well understood. We used a custom-made visual light pacer for real-time speed modulation during front crawl to determine the LT and MLSS_W in a single-exercise test. When approaching the LT, we found that minute variations in swimming speed had considerable effects on blood lactate concentration ([La^-]). The LT was characterized by a sudden increase in [La^-], while the MLSS_W occurred after a subsequent workload reduction, as indicated by a rapid cessation of blood lactate accumulation. Determination of the MLSS_W by this so-called "individual lactate threshold" (ILT)-test was highly reproducible and valid in a constant speed test. Mean swimming speed in 800 and 1,500 m competition (S-Comp) was 3.4% above MLSS_W level and S-Comp, and the difference between S-Comp and the MLSS_W (Δ S-Comp/MLSS_W) were higher for long-distance swimmers (800-1,500 m) than for short- and middle-distance swimmers (50-400 m). Moreover, Δ S-Comp/MLSS_W varied significantly between subjects and had a strong influence on overall swimming performance. Our results demonstrate that the MLSS_W determines individual swimming performance, reflects endurance capacity in the sub- to supra-threshold range, and is therefore appropriate to adjust training intensity in moderate to severe domains of exercise.

Effects of Postexercise Sauna Bathing on Recovery of Swim Performance

PURPOSE

Despite indications of positive effects of sauna (SAU) interventions, effects on performance recovery are unknown. The aim of the current study was to investigate acute effects of SAU bathing after an intensive training session on recovery of swim performance.

METHODS

In total, 20 competitive swimmers and triathletes (3 female and 17 male) with a minimum of 2 y of competition experience (national level or higher) participated in the study. Athletes completed an intensive training session followed by either a SAU bathing intervention or a placebo (PLAC) condition in a randomized order. SAU consisted of 3 × 8 min of SAU bathing at 80-85°C, whereas during PLAC, athletes applied a deidentified, pH-balanced massage oil while passively resting in a seated position. Prior to training, swimmers conducted a 4 × 50-m all-out swim test that was repeated on the following morning. Furthermore, subjective ratings of fatigue and recovery were measured.

RESULTS

Swimmers performed significantly worse after SAU (4 × 50-m pre-post difference: +1.69 s) than after PLAC (-0.66 s; P = .02), with the most pronounced decrease in the first 50 m (P = .04; +2.7%). Overall performance of 15 athletes deteriorated (+2.6 s). The subjective feeling of stress was significantly higher after SAU than after PLAC (P = .03).

CONCLUSION

Based on published findings, the smallest substantial change in swimming performance is an increase in time of more than 1.2 s; thus, the observed reductions appear relevant for competitive swimmers. According to the current results, coaches and athletes should be careful with postexercise SAU if high-intensity training and/or competitions are scheduled on the following day.

Verifying Physiological and Biomechanical Parameters during Continuous Swimming at Speed Corresponding to Lactate Threshold

The purpose of this study was to verify the physiological responses and biomechanical parameters measured during 30 min of continuous swimming (T30) at intensity corresponding to lactate threshold previously calculated by an intermittent progressively increasing speed test (7 × 200 m). Fourteen competitive swimmers (18.0 (2.5) years, 67.5 (8.8) kg, 174.5 (7.7) cm) performed a 7 × 200 m front crawl test. Blood lactate concentration (BL) and oxygen uptake (VO₂) were determined after each 200 m repetition, while heart rate (HR), arm-stroke rate (SR), and arm-stroke length (SL) were measured during each 200 m repetition. Using the speed vs. lactate concentration curve, the speed at lactate threshold (sLT) and parameters corresponding to sLT were calculated (BL-sLT, VO₂-sLT, HR-sLT, SR-sLT, and SL-sLT). In the following day, a T30 corresponding to sLT was performed and BL-T30, VO₂-T30, HR-T30, SR-T30, and SL-T30 were measured after the 10th and 30th minute, and average values were used for comparison. VO₂-sLT was no different compared to VO_2-T30 (p > 0.05). BL-T30, HR-T30, and SR-T30 were higher, while SL-T30 was lower compared to BL-sLT, HR-sLT, SR-sLT, and SL-sLT (p < 0.05). Continuous swimming at speed corresponding to lactate threshold may not show the same physiological and biomechanical responses as those calculated by a progressively increasing speed test of 7 × 200 m.

The influence of sex, stroke and distance on the lactate characteristics in high performance swimming

Background

In order to achieve world-class performances, regular performance diagnostics is required as an essential prerequisite for guiding high performance sport. In high performance swimming, the lactate performance diagnostic is an important instrument in testing the sport specific endurance capacity. Although the role of lactate as a signaling molecule, fuel and a gluconeogenic substrate is accepted, lactate parameters are discussed concerning stability, explanatory power and interpretability.

Methods

We calculated the individual anaerobic threshold (IAT) of Bunc using the swimming-specific lactate threshold test by Pansold.

Results

The cross-sectional analysis (ANOVA) of n = 398 high performance swimmers showed significant effects for sex, stroke and distance on the IAT, the percentage of personal best time on the IAT (% of PB on IAT) and maximal lactate values (max. bLA). For the freestyle events the IAT decreased, % of PB on IAT and max. bLA increased from 100 to 400 m significantly in men and women. Women showed significantly higher % of PB on IAT with descriptive lower IAT in 7 of 8 analyzed events. Men showed significantly higher max. bLA in 5 of 8 events. In the second step, the analysis of 1902 data sets of these 398 athletes with a multi-level analysis (MLA) showed also significant effects for sex, swimming distance and stroke. For initial status and development over time, the effect sizes for the variables distance and sex were medium to large, whereas for stroke there were no or small effect sizes.

Discussion

These significant results suggest that lactate tests in swimming specifically have to consider the lactate affecting factors sex and distance under consideration of the time period between measurements. Anthropometrical factors and the physiology of women are possible explanations for the relative better performance for lower lactate concentrations compared to men.