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Monitoring variations in the functioning of the autonomic nervous system may help personalize training of runners and provide more pronounced physiological adaptations and performance improvements. We systematically reviewed the scientific literature comparing physiological adaptations and/or improvements in performance following training based on responses of the autonomic nervous system (ie, changes in heart rate variability) and predefined training. PubMed, SPORTDiscus, and Web of Science were searched systematically in July 2019. Keywords related to endurance, running, autonomic nervous system, and training. Studies were included if they (a) involved interventions consisting predominantly of running training; (b) lasted at least 3 weeks; (c) reported pre‐ and post‐intervention assessment of running performance and/or physiological parameters; (d) included an experimental group performing training adjusted continuously on the basis of alterations in HRV and a control group; and (e) involved healthy runners. Five studies involving six interventions and 166 participants fulfilled our inclusion criteria. Four HRV‐based interventions reduced the amount of moderate‐ and/or high‐intensity training significantly. In five interventions, improvements in performance parameters (3000 m, 5000 m, Loadmax, Tlim) were more pronounced following HRV‐based training. Peak oxygen uptake (VO\(_{2peak}\)) and submaximal running parameters (eg, LT1, LT2) improved following both HRV‐based and predefined training, with no clear difference in the extent of improvement in VO\(_{2peak}\). Submaximal running parameters tended to improve more following HRV‐based training. Research findings to date have been limited and inconsistent. Both HRV‐based and predefined training improve running performance and certain submaximal physiological adaptations, with effects of the former training tending to be greater.
The rating of perceived exertion (RPE) is a subjective load marker and may assist in individualizing training prescription, particularly by adjusting running intensity. Unfortunately, RPE has shortcomings (e.g., underreporting) and cannot be monitored continuously and automatically throughout a training sessions. In this pilot study, we aimed to predict two classes of RPE (≤15 “Somewhat hard to hard” on Borg’s 6–20 scale vs. RPE >15 in runners by analyzing data recorded by a commercially-available smartwatch with machine learning algorithms. Twelve trained and untrained runners performed long-continuous runs at a constant self-selected pace to volitional exhaustion. Untrained runners reported their RPE each kilometer, whereas trained runners reported every five kilometers. The kinetics of heart rate, step cadence, and running velocity were recorded continuously ( 1 Hz ) with a commercially-available smartwatch (Polar V800). We trained different machine learning algorithms to estimate the two classes of RPE based on the time series sensor data derived from the smartwatch. Predictions were analyzed in different settings: accuracy overall and per runner type; i.e., accuracy for trained and untrained runners independently. We achieved top accuracies of 84.8 % for the whole dataset, 81.8 % for the trained runners, and 86.1 % for the untrained runners. We predict two classes of RPE with high accuracy using machine learning and smartwatch data. This approach might aid in individualizing training prescriptions.
The aim of this study was to investigate inter-day and -week as well as intra- and inter-individual variation of selected biomarkers in high-performance youth soccer players to assist practitioners interpreting player’s internal load to counteract underperformance and unwanted health risks. Eleven male youth soccer players were tested multiple times during two 3-week periods at midpoint (3-wkmid) and at the end (3-wkend) of the first half of a German under-19 1. Bundesliga season. The levels of creatine kinase (CK), urea, and C-reactive protein (CRP) were measured during 3-wkmid and 3-wkend each Monday, Wednesday, and Friday. In 3-wkmid the CK median was 14% higher (241 vs. 212 U/L) compared to 3-wkend (P = 0.26, ES = 0.16). Overall, the medians of CK, urea (P = 0.59, ES = 0.08), and CRP (P = 0.56, ES = 0.10) during 3-wkmid did not differ to the values of 3-wkend. Daily coefficient of variations (CVs) ranged from 22 to 71% (CK), 17 to 37% (urea), and 9 to 164% (CRP). Individual medians ranged from 101 to 350 U/L (CK), 23 to 50 mg/dL (urea), and 0.6 to 1.1 mg/L (CRP). High intra-individual variability was demonstrated by large intra-individual CVs (medians: CK 50%, urea 18%, and CRP 45%). Our data show (i) large inter-day and inter-week variability of all biomarkers, depending on the external load and (ii) considerable inter- and intra-individual parameter variations. Creatine kinase concentrations could sensitively reflect soccer-specific loads during the season.
To elucidate the mechanisms underlying the differences in adaptation of arm and leg muscles to sprint training, over a period of 11 days 16 untrained men performed six sessions of 4–6 × 30-s all-out sprints (SIT) with the legs and arms, separately, with a 1-h interval of recovery. Limb-specific VO2peak, sprint performance (two 30-s Wingate tests with 4-min recovery), muscle efficiency and time-trial performance (TT, 5-min all-out) were assessed and biopsies from the m. vastus lateralis and m. triceps brachii taken before and after training. VO2peak and Wmax increased 3–11% after training, with a more pronounced change in the arms (P < 0.05). Gross efficiency improved for the arms (+8.8%, P < 0.05), but not the legs (−0.6%). Wingate peak and mean power outputs improved similarly for the arms and legs, as did TT performance. After training, VO2 during the two Wingate tests was increased by 52 and 6% for the arms and legs, respectively (P < 0.001). In the case of the arms, VO2 was higher during the first than second Wingate test (64 vs. 44%, P < 0.05). During the TT, relative exercise intensity, HR, VO2, VCO2, VE, and Vt were all lower during arm-cranking than leg-pedaling, and oxidation of fat was minimal, remaining so after training. Despite the higher relative intensity, fat oxidation was 70% greater during leg-pedaling (P = 0.017). The aerobic energy contribution in the legs was larger than for the arms during the Wingate tests, although VO2 for the arms was enhanced more by training, reducing the O2 deficit after SIT. The levels of muscle glycogen, as well as the myosin heavy chain composition were unchanged in both cases, while the activities of 3-hydroxyacyl-CoA-dehydrogenase and citrate synthase were elevated only in the legs and capillarization enhanced in both limbs. Multiple regression analysis demonstrated that the variables that predict TT performance differ for the arms and legs. The primary mechanism of adaptation to SIT by both the arms and legs is enhancement of aerobic energy production. However, with their higher proportion of fast muscle fibers, the arms exhibit greater plasticity.
PurposeOur aims were to examine (i) the internal load during simulated soccer match-play by elite youth players; and (ii) the time-course of subsequent recovery from perceived and performance fatigability.
MethodsEleven male youth players (16 ± 1 years, 178 ± 7 cm, 67 ± 7 kg) participated in a 2 × 40-min simulated soccer match, completing 30 rounds (160 s each) with every round including multidirectional and linear sprinting (LS20m), jumping (CMJ) and running at different intensities. During each round, LS20m, CMJ, agility, heart rate (HR), oxygen uptake (VO2), energy expenditure (EE), substrate utilization and perceived exertion RPE were assessed. In addition, the blood level of lactate (Lac) was obtained after each of the five rounds. Creatine kinase (CK) concentration, maximal voluntary isometric knee extension and flexion, CMJ, number of skippings in 30 s, and subjective ratings on the Acute Recovery and Stress Scale (ARSS) were examined before and immediately, 24 and 48 h after the simulation.
Results: During the game %HR\(_{peak}\) (p < 0.05, d = 1.08), %VO2\(_{peak}\) (p < 0.05; d = 0.68), Lac (p < 0.05, d = 2.59), RPE\(_{total}\) (p < 0.05, d = 4.59), and RPE\(_{legs}\) (p < 0.05, d = 4.45) all increased with time during both halves (all p < 0.05). Agility improved (p < 0.05, d = 0.70) over the time-course of the game, with no changes in LS20m (p ≥ 0.05, d = 0.34) or CMJ (p ≥ 0.05, d = 0.27). EE was similar during both halves (528 ± 58 vs. 514 ± 61 kcal; p = 0.60; d = 0.23), with 62% (second half: 65%) carbohydrate, 9% (9%) protein and 26% (27%) fat utilization. With respect to recovery, maximal voluntary knee extension (p ≥ 0.05, d = 0.50) and flexion force (p ≥ 0.05, d = 0.19), CMJ (p ≥ 0.05, d = 0.13), number of ground contacts (p ≥ 0.05, d = 0.57) and average contact time (p ≥ 0.05, d = 0.39) during 30-s of skipping remained unaltered 24 and 48 h after the game. Most ARSS dimensions of load (p < 0.05, d = 3.79) and recovery (p < 0.05, d = 3.22) returned to baseline levels after 24 h of recovery. Relative to baseline values, CK was elevated immediately and 24 h after (p < 0.05, d = 2.03) and normalized 48 h later.
ConclusionIn youth soccer players the simulated match evoked considerable circulatory, metabolic and perceptual load, with an EE of 1042 ± 118 kcal. Among the indicators of perceived and performance fatigability examined, the level of CK and certain subjective ratings differed considerably immediately following or 24–48 h after a 2 × 40-min simulated soccer match in comparison to baseline. Accordingly, monitoring these variables may assist coaches in assessing a U17 player’s perceived and performance fatigability in connection with scheduling training following a soccer match.
The effects of circuit-like functional high-intensity training (Circuit\(_{HIIT}\)) alone or in combination with high-volume low-intensity exercise (Circuit\(_{combined}\)) on selected cardio-respiratory and metabolic parameters, body composition, functional strength and the quality of life of overweight women were compared. In this single-center, two-armed randomized, controlled study, overweight women performed 9-weeks (3 sessions·wk\(^{−1}\)) of either Circuit\(_{HIIT}\) (n = 11), or Circuit\(_{combined}\) (n = 8). Peak oxygen uptake and perception of physical pain were increased to a greater extent (p < 0.05) by Circuit\(_{HIIT}\), whereas Circuit\(_{combined}\) improved perception of general health more (p < 0.05). Both interventions lowered body mass, body-mass-index, waist-to-hip ratio, fat mass, and enhanced fat-free mass; decreased ratings of perceived exertion during submaximal treadmill running; improved the numbers of push-ups, burpees, one-legged squats, and 30-s skipping performed, as well as the height of counter-movement jumps; and improved physical and social functioning, role of physical limitations, vitality, role of emotional limitations, and mental health to a similar extent (all p < 0.05). Either forms of these multi-stimulating, circuit-like, multiple-joint training can be employed to improve body composition, selected variables of functional strength, and certain dimensions of quality of life in overweight women. However, Circuit\(_{HIIT}\) improves peak oxygen uptake to a greater extent, but with more perception of pain, whereas Circuit\(_{Combined}\) results in better perception of general health.
The purpose of this study was threefold: 1) to assess the eggbeater kick and throwing performance using a number of water polo specific tests, 2) to explore the relation between the eggbeater kick and throwing performance, and 3) to investigate the relation between the eggbeater kick in the water and strength tests performed in a controlled laboratory setting in elite water polo players. Fifteen male water polo players of the German National Team completed dynamic and isometric strength tests for muscle groups (adductor, abductor, abdominal, pectoralis) frequently used during water polo. After these laboratory strength tests, six water polo specific in-water tests were conducted. The eggbeater kick assessed leg endurance and agility, maximal throwing velocity and jump height. A 400 m test and a sprint test examined aerobic and anaerobic performance. The strongest correlation was found between jump height and arm length (p < 0.001, r = 0.89). The laboratory diagnostics of important muscles showed positive correlations with the results of the in-water tests (p < 0.05, r = 0.52-0.70). Muscular strength of the adductor, abdominal and pectoralis muscles was positively related to in-water endurance agility as assessed by the eggbeater kick (p < 0.05; r = 0.53-0.66). Findings from the current study emphasize the need to assess indices of water polo performance both in and out of the water as well as the relation among these parameters to best assess the complex profile of water polo players.
The purpose of this study was to determine whether an individually designed incremental exercise protocol results in greater rates of oxygen uptake VO\(_{2max}\) than standardized testing. Fourteen well-trained, male runners performed five incremental protocols in randomized order to measure their VO\(_{2max}\): i) an incremental test (INC\(_{S+I}\)) with pre-defined increases in speed (2 min at 8.64 km.h\(^{-1}\), then a rise of 1.44 km.h\(^{-1}\) every 30 s up to 14.4 km.h\(^{-1}\)) and thereafter inclination (0.5.every 30 s); ii) an incremental test (INC\(_{I}\)) at constant speed (14.4 km.h\(^{-1}\)) and increasing inclination (2 degrees every 2 min from the initial 0 degrees); iii) an incremental test (INC\(_{S}\)) at constant inclination (0 degrees) and increasing speed (0.5 km.h\(^{-1}\) every 30 s from the initial 12.0 km.h\(^{-1}\)); iv) a graded exercise protocol (GXP) at a 1 degrees incline with increasing speed (initially 8.64 km.h\(^{-1}\) + 1.44 km.h\(^{-1}\) every 5 min); v) an individual exercise protocol (INDXP) in which the runner chose the inclination and speed. VO\(_{2max}\) was lowest (-4.2%) during the GXP (p = 0.01; d = 0.06 - 0.61) compared to all other tests. The highest rating of perceived exertion, heart rate, ventilation and end-exercise blood lactate concentration were similar between the different protocols (p < 0.05). The time to exhaustion ranged from 7 min 18 sec (INC\(_{S}\)) to 25 min 30 sec (GXP) (p = 0.01). The VO\(_{2max}\) attained by employing an individual treadmill protocol does not differ from the values derived from various standardized incremental protocols.
The aim was to examine certain aspects of circulatory, metabolic, hormonal, thermoregulatory, cognitive, and perceptual responses while sitting following a brief session of high-intensity interval exercise. Twelve students (five men; age, 22 ± 2 years) performed two trials involving either simply sitting for 180 min (SIT) or sitting for this same period with a 6-min session of high-intensity exercise after 60 min (SIT+HIIT). At T\(_0\) (after 30 min of resting), T\(_1\) (after a 20-min breakfast), T\(_2\) (after sitting for 1 h), T\(_3\) (immediately after the HIIT), T\(_4\), T\(_5\), T\(_6\), and T\(_7\) (30, 60, 90, and 120 min after the HIIT), circulatory, metabolic, hormonal, thermoregulatory, cognitive, and perceptual responses were assessed. The blood lactate concentration (at T\(_3\)–T\(_5\)), heart rate (at T\(_3\)–T\(_6\)), oxygen uptake (at T\(_3\)–T\(_7\)), respiratory exchange ratio, and sensations of heat (T\(_3\)–T\(_5\)), sweating (T\(_3\), T\(_4\)) and odor (T\(_3\)), as well as perception of vigor (T\(_3\)–T\(_6\)), were higher and the respiratory exchange ratio (T\(_4\)–T\(_7\)) and mean body and skin temperatures (T\(_3\)) lower in the SIT+HIIT than the SIT trial. Levels of blood glucose and salivary cortisol, cerebral oxygenation, and feelings of anxiety/depression, fatigue or hostility, as well as the variables of cognitive function assessed by the Stroop test did not differ between SIT and SIT+HIIT. In conclusion, interruption of prolonged sitting with a 6-min session of HIIT induced more pronounced circulatory and metabolic responses and improved certain aspects of perception, without affecting selected hormonal, thermoregulatory or cognitive functions.
Purpose:
The aim of the study was to evaluate the mucosal immune function and circadian variation of salivary cortisol, Immunoglobin-A (sIgA) secretion rate and mood during a period of high-intensity interval training (HIIT) compared to long-slow distance training (LSD).
Methods:
Recreational male runners (n = 28) completed nine sessions of either HIIT or LSD within 3 weeks. The HIIT involved 4 × 4 min of running at 90–95% of maximum heart rate interspersed with 3 min of active recovery while the LSD comprised of continuous running at 70–75% of maximum heart rate for 60–80 min. The psycho-immunological stress-response was investigated with a full daily profile of salivary cortisol and immunoglobin-A (sIgA) secretion rate along with the mood state on a baseline day, the first and last day of training and at follow-up 4 days after the last day of training. Before and after the training period, each athlete's running performance and peak oxygen uptake (V·O\(_{2peak}\)) was determined with an incremental exercise test.
Results:
The HIIT resulted in a longer time-to-exhaustion (P = 0.02) and increased V·O\(_{2peak}\) compared to LSD (P = 0.01). The circadian variation of sIgA secretion rate showed highest values in the morning immediately after waking up followed by a decrease throughout the day in both groups (P < 0.05). With HIIT, the wake-up response of sIgA secretion rate was higher on the last day of training (P < 0.01) as well as the area under the curve (AUC\(_{G}\)) higher on the first and last day of training and follow-up compared to the LSD (P = 0.01). Also the AUC\(_{G}\) for the sIgA secretion rate correlated with the increase in V·O\(_{2peak}\) and running performance. The AUC\(_{G}\) for cortisol remained unaffected on the first and last day of training but increased on the follow-up day with both, HIIT and LSD (P < 0.01).
Conclusion:
The increased sIgA secretion rate with the HIIT indicates no compromised mucosal immune function compared to LSD and shows the functional adaptation of the mucosal immune system in response to the increased stress and training load of nine sessions of HIIT.