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The Ecological Validity and Application of the Session-RPE Method for Quantifying Training Loads in Swimming
Abstract
There are few practical methods available for evaluating training loads (TL) during swimming. The purpose of this study was to examine the ecological validity of the session-rating of perceived exertion (RPE) method for quantifying internal TL in competitive swimmers using heart rate (HR)-based methods and distance as criterion measures. This study also examined the correspondence between athlete and coach perceptions of internal TL using the session-RPE method. Twelve (six male, six female) well-trained swimmers (mean +/- SD: age 22.3 +/- 3.1 years, weight 71.8 +/- 11.6 kg, height 175.0 +/- 9.0 cm) participated in this study. All subjects completed a swimming step test to evaluate individual HR zones and blood lactate profile before undertaking 20 swim training sessions where RPE, HR, and distance covered were recorded. Training load was then calculated for each session using the session-RPE, HR-based methods, and session distance. The session-RPE scores were correlated to HR-based methods for measuring internal TL as well as training distance for each swimmer. All individual correlations between session-RPE, HR-based methods (r = 0.55-0.94; p < 0.05), and distance measures (r = 0.37-0.81; p < 0.05) were significant. Two-way ANOVA showed that there was a significant interaction for training intensity x coach-athlete perception, indicating that coach RPE was lower than athlete RPE for low-intensity sessions and higher than athlete RPE at high-intensity sessions. The results of this study suggest that session-RPE may provide a practical, noninvasive method for quantifying internal TL in competitive swimmers.
... In an attempt to specify the differences, the training sessions have been divided into easy, moderate, and hard. On the RPE CR10 scale [12], easy, moderate, and hard were classified as an RPE < 3, 3-5, and >5, respectively [14][15][16][17]. However, studies using the 6 to 20 Borg scale [18] have defined two different classifications for easy, moderate, and hard, i.e., RPE < 11, 11-14, and >14, respectively [19], and RPE < 13, 13-14, and >14, respectively [20]. ...
... Previous studies using the RPE CR10 scale showed no differences in intensity, duration, and training load on average [14][15][16][17]. However, the training load of easy sessions was perceived as higher by the athletes. ...
... Intended moderate sessions did not show any differences between coach and athlete, except for male cross-country runners who perceive it as harder [17]. Moreover, the training load of intended hard sessions was perceived as lower by runners [14], swimmers [16], and female cross-country runners [17]. For cyclists [15] and male cross-country runners [17], there were no differences for intended hard sessions. ...
The aim of this observational study was to examine the differences between training variables as intended by coaches and perceived by junior speed skaters and to explore how these relate to changes in stress and recovery. During a 4-week preparatory period, intended and perceived training intensity (RPE) and duration (min) were monitored for 2 coaches and their 23 speed skaters, respectively. The training load was calculated by multiplying RPE by duration. Changes in perceived stress and recovery were measured using RESTQ-sport questionnaires before and after 4 weeks. Results included 438 intended training sessions and 378 executed sessions of 14 speed skaters. A moderately higher intended (52:37 h) versus perceived duration (45:16 h) was found, as skaters performed fewer training sessions than anticipated (four sessions). Perceived training load was lower than intended for speed skating sessions (−532 ± 545 AU) and strength sessions (−1276 ± 530 AU) due to lower RPE scores for skating (−0.6 ± 0.7) or shorter and fewer training sessions for strength (−04:13 ± 02:06 hh:mm). All training and RESTQ-sport parameters showed large inter-individual variations. Differences between intended–perceived training variables showed large positive correlations with changes in RESTQ-sport, i.e., for the subscale’s success (r = 0.568), physical recovery (r = 0.575), self-regulation (r = 0.598), and personal accomplishment (r = 0.589). To conclude, speed skaters that approach or exceed the coach’s intended training variables demonstrated an increased perception of success, physical recovery, self-regulation, and personal accomplishment.
... Several studies have found that perceptions often do not match, suggesting that athletes (such as soccer players 4 , swimmers 9 , and runners 11 ) perceive easy workouts as more difficult than intended, and challenging workouts as easier than intended, specifically in intensity, duration, and load 2,4,9,11 . To this point, it is unclear how moderate intensity workouts are perceived by athletes, as studies show a mix of results. ...
... Several studies have found that perceptions often do not match, suggesting that athletes (such as soccer players 4 , swimmers 9 , and runners 11 ) perceive easy workouts as more difficult than intended, and challenging workouts as easier than intended, specifically in intensity, duration, and load 2,4,9,11 . To this point, it is unclear how moderate intensity workouts are perceived by athletes, as studies show a mix of results. ...
... To the authors' knowledge, few studies have observed comparisons of coaches' intentions and athletes' perceptions in distance runners 15 , choosing instead to focus on other sports, such as volleyball programs 16,17 and swimming programs 9,12 . As the demands and training programs differ between sports, it is possible that discrepancies of coaches' intentions and athletes' perceptions are sport-specific. ...
Coaches are trusted to create effective training plans based on the abilities of their athletes. However, there can exist a discrepancy between the coaches’ intended training intensity and the intensity perceived by their athletes. Thus, the purpose of this study was to evaluate athletes’ perceptions of training intensity and how they compared to their coach’s intended training intensity. Six female collegiate track and field athletes who ran >800 meter events were recruited for this study (Mean [SD]: 21.3 [1.2] years). Training duration, rate of perceived exertion (RPE), average heart rate for each training session and hours slept nightly were recorded for the next 14 weeks. Easy training days showed a discernible difference with actual session RPE rating higher than the target value (mean [SD] perception 3.25 [.847], target 1.51 [.692], p<.001), while hard training days were perceived as easier than intended (mean [SD] perception 6.26 [1.24], target 8.16 [.646], p<.001). Similarly, average training load (defined as the product of Session RPE and exercise duration) was higher than coach’s intentions on easy days (actual load mean [SD] 117.28 [19.15] p=.046), and lower than the coach’s intentions on hard days (p=.029). Workouts that are more intense than intended may lead to overtraining syndrome in athletes, and workouts that are less intense than intended may lead to undertraining, and athletes not achieving their full potential. Appropriate monitoring of training load can provide important information to athletes and coaches. Training load needs to be accurately determined to establish other recovery factors.
... However, there are times where a coach's perceived intensity of a training session is not matched by his or her players. Previous studies have investigated discrepancies between the workload planned by coaches and how the athletes actually perceive the load (1,4,15). These studies reported discrepancies between player and coach perceptions often surrounding the intensity of the training sessions. ...
... These studies reported discrepancies between player and coach perceptions often surrounding the intensity of the training sessions. Coaches and players tended to agree more often for the moderate-intensity sessions than for the low-intensity and highintensity sessions (1,13,15). Players tended to report higher RPE values when compared with their coaches for both low-intensity and high-intensity training sessions. Other factors may also affect the level of agreement. ...
... This could be because of variations in the duration of sessions, volume and type of drills, or intensity levels throughout the season. The results reported for the primary analysis corresponded with the previous literature comparing coach with player perceptions of workload (1,4,8,10,13,15). As with every study, there were limitations faced. ...
Ratings of perceived exertion (RPE) are used extensively to subjectively evaluate workload in sport. The purpose of this study was to compare season long player to coach perceptions of RPE loads (RPEL) in Division I men's soccer and women's lacrosse programs. Coach and player self-reported RPE were collected during the competitive seasons for both teams within 30 minutes of training sessions. Scores of RPE were multiplied by recorded training time to determine RPEL and averaged to create a daily coach and player RPEL. Accuracy of RPEL prediction between coaches and players was determined via mean bias, mean absolute percent error (MAPE), correlation, and an equivalence test. Soccer coaches underestimated RPEL (1,345 ± 410 arbitrary unit [AU]) compared with players (1,372 ± 435 AU). The coach mean bias was −27.3 ± 151.9 AU, wieth an MAPE of 7.4%, a strong correlation (r = 0.937, p < 0.001), and coach to player equivalence (p = 0.045). Lacrosse coaches overestimated RPELs (876 ± 349 AU) compared with players (829 ± 214 AU). The coach mean bias was 47 ± 189 AU, with an MAPE of 14.7%, a strong correlation (r = 0.883, p < 0.001), and coach to player equivalence (p = 0.010). Analyses indicated that coaches accurately predicted player RPEL within both sports. Variance occurred on days with high RPELs, with overestimations occurring in lacrosse and underestimation in soccer. Coaches can use RPELs to assess subjective training load but should consider objective measures, including microtechnology, to provide a comprehensive assessment.
... For instance, Redkva et al. [16] found no differences when comparing the sRPE prescribed by the coaches and perceived by the athletes in physical, technical, and tactical training sessions during the three weeks of pre-season in soccer players. However, some studies [5,[17][18][19] have reported a difference between the training load planned by coaches and the load perceived by athletes. In general, these disagreements between coaches and athletes were identified in the prescribed training as easy or hard [5,[17][18][19]. ...
... However, some studies [5,[17][18][19] have reported a difference between the training load planned by coaches and the load perceived by athletes. In general, these disagreements between coaches and athletes were identified in the prescribed training as easy or hard [5,[17][18][19]. Besides, Rabelo et al. [20] demonstrated that in all three effort categories (easy, moderate, and hard), the athletes perceived a lower training load than intended by the coach. ...
... Therefore, this systematic review and meta-analysis of the literature aimed to investigate whether there are differences between the training load perceived by athletes and that prescribed/intended/observed by coaches. We hypothesized that significant differences would be found between that expected by coaches and that perceived by the athletes [5,[17][18][19]. ...
Background
Rating of perceived exertion (RPE) and session RPE (sRPE) has been widely used to verify the internal load in athletes. Understanding the agreement between the training load prescribed by coaches and that perceived by athletes is a topic of great interest in sport science.
Objective
This systematic review and meta-analysis aimed to investigate differences between the training/competition load perceived by athletes and prescribed/intended/observed by coaches.
Methods
A literature search (September 2020 and updated in November 2021) was conducted using PubMed, Web of Science, Embase, and SPORTDiscus databases. The protocol was registered in the Open Science Framework (osf.io/wna4x). Studies should include athletes and coaches of any sex, age, or level of experience. The studies should present outcomes related to the RPE or sRPE for any scale considering overall training/competition sessions (physical, strength, tactical, technical, games) and/or classified into three effort categories: easy, moderate, and hard.
Results
Twenty-seven studies were included in the meta-analysis. No difference was found between coaches and athletes for overall RPE (SMD = 0.19, P = 0.10) and overall sRPE (SMD = 0.05, P = 0.75). There was a difference for easy RPE (SMD = − 0.44, small effect size, P = 0.04) and easy sRPE (SMD = − 0.54, moderate effect size, P = 0.04). No differences were found for moderate RPE (SMD = 0.05, P = 0.74) and hard RPE (SMD = 0.41, P = 0.18). No difference was found for moderate (SMD = -0.15, P = 0.56) and hard (SMD = 0.20, P = 0.43) sRPE.
Conclusion
There is an agreement between coaches and athletes about overall RPE and sRPE, and RPE and sRPE into two effort categories (moderate and hard). However, there were disagreements in RPE and sRPE for easy effort category. Thus, despite a small disagreement, the use of these tools seems to be adequate for training monitoring.
... 1 In addition, training monitoring is used to assess fatigue and recovery status and to reduce the risk of developing nonfunctional overreaching, injury, and illness. 1 An array of monitoring devices and methods are available to assess the external (eg, global positioning systems) and internal (eg, rating of perceived exertion) load experienced by an athlete during training. 2 External load (ie, objective assessment of work performed) measures are commonly used to inform training prescription. 1,2 Accelerometer and global positioning system-based analysis of athletic performance are common in numerous land-based sports to assess external load. ...
... 2 External load (ie, objective assessment of work performed) measures are commonly used to inform training prescription. 1,2 Accelerometer and global positioning system-based analysis of athletic performance are common in numerous land-based sports to assess external load. 1,3 However, the use of such devices within the aquatic environment presents many challenges, including the need for airtight sealing of sensors and ports, ambiguous validity of device positioning, and requirement for a reliable method to mount the device on the athlete. ...
... 4,6 Recent advancements in wearable technologies have sought to overcome these limitations; however, further validation of the swimmer metrics is required. 2,3,[5][6][7] Previous research suggests that there is a wearable device which is capable of measuring swim training and performance metrics. 5 However, this study only assessed the validity of freestyle and breaststroke over a distance of 100 m in a 25-m pool. ...
Purpose:
This study aimed to independently validate a wearable inertial sensor designed to monitor training and performance metrics in swimmers.
Methods:
A total of 4 male (21 [4] y, 1 national and 3 international) and 6 female (22 [3] y, 1 national and 5 international) swimmers completed 15 training sessions in an outdoor 50-m pool. Swimmers were fitted with a wearable device (TritonWear, 9-axis inertial measurement unit with triaxial accelerometer, gyroscope, and magnetometer), placed under the swim cap on top of the occipital protuberance. Video footage was captured for each session to establish criterion values. Absolute error, standardized effect, and Pearson correlation coefficient were used to determine the validity of the wearable device against video footage for total swim distance, total stroke count, mean stroke count, and mean velocity. A Fisher exact test was used to analyze the accuracy of stroke-type identification.
Results:
Total swim distance was underestimated by the device relative to video analysis. Absolute error was consistently higher for total and mean stroke count, and mean velocity, relative to video analysis. Across all sessions, the device incorrectly detected total time spent in backstroke, breaststroke, butterfly, and freestyle by 51% (15%). The device did not detect time spent in drill. Intraclass correlation coefficient results demonstrated excellent intrarater reliability between repeated measures across all swimming metrics.
Conclusions:
The wearable device investigated in this study does not accurately measure distance, stroke count, and velocity swimming metrics or detect stroke type. Its use as a training monitoring tool in swimming is limited.
... Most sports science research groups term the responses as exercise and the training or match stimuli as internal and external load, workload, or training load, respectively [1,[4][5][6][7]. We acknowledged that this terminology might be misleading considering the In this framework, it can be distinguished between four different categories of internal parameter assessments: First, the internal load estimates collected during exercise, primarily made up of HR-based indices and RPE or session-RPE. ...
... Most sports science research groups term the responses as exercise and the training or match stimuli as internal and external load, workload, or training load, respectively [1,[4][5][6][7]. We acknowledged that this terminology might be misleading considering the mechanical concepts where the load is weight or resistance, which is expressed in Newtons (N), as defined by the Système International d'Unites (SI), as various other research groups have indicated [8][9][10][11]. ...
Citation: Helwig, J.; Diels, J.; Röll, M.; Mahler, H.; Gollhofer, A.; Roecker, K.; Willwacher, S. Relationships between External, Wearable Sensor-Based, and Internal Parameters: A Systematic Review. Sensors 2023, 23, 827. Abstract: Micro electro-mechanical systems (MEMS) are used to record training and match play of intermittent team sport athletes. Paired with estimates of internal responses or adaptations to exercise, practitioners gain insight into players' dose-response relationship which facilitates the prescription of the training stimuli to optimize performance, prevent injuries, and to guide rehabilitation processes. A systematic review on the relationship between external, wearable-based, and internal parameters in team sport athletes, compliant with the PRISMA guidelines, was conducted. The literature research was performed from earliest record to 1 September 2020 using the databases PubMed, Web of Science, CINAHL, and SportDISCUS. A total of 66 full-text articles were reviewed encompassing 1541 athletes. About 109 different relationships between variables have been reviewed. The most investigated relationship across sports was found between (session) rating of perceived exertion ((session-)RPE) and PlayerLoad™ (PL) with, predominantly, moderate to strong associations (r = 0.49-0.84). Relationships between internal parameters and highly dynamic, anaerobic movements were heterogenous. Relationships between average heart rate (HR), Edward's and Banister's training impulse (TRIMP) seem to be reflected in parameters of overall activity such as PL and TD for running-intensive team sports. PL may further be suitable to estimate the overall subjective perception. To identify high fine-structured loading-relative to a certain type of sport-more specific measures and devices are needed. Individualization of parameters could be helpful to enhance practicality.
... The external training load is the work that is performed by the athlete, e.g., cycling for an hour at 200 W. While this external load is independent of the individual characteristics of an athlete (Wallace et al. 2009), the internal training load quantifies how the external training load is experienced by the athlete. Common measures for the internal training load are the heart rate or the Session Rating of Perceived Exertion (Foster 1998). ...
... There are several complications in finding accurate connections between the external and internal training loads. Most importantly, each individual responds differently to training activities and therefore a personalized approach is preferable (Wallace et al. 2009). However, in most cases there is not enough data to apply an individualized approach and groups of athletes need to be considered together to find significant dependencies. ...
We present a personalized approach for frequent fitness monitoring in road cycling solely relying on sensor data collected during bike rides and without the need for maximal effort tests. We use competition and training data of three world-class cyclists of Team Jumbo–Visma to construct personalised heart rate models that relate the heart rate during exercise to the pedal power signal. Our model captures the non-trivial dependency between exertion and corresponding response of the heart rate, which we show can be effectively estimated by an exponential kernel. To construct the daily heart rate models that are required for day-to-day fitness estimation, we aggregate all sessions in the previous week and apply sampling. On average, the explained variance of our models is 0.86, which we demonstrate is more than twice as large as for models that ignore the temporal integration involved in the heart’s response to exercise. We show that the fitness of a cyclist can be monitored by tracking developments of parameters of our heart rate models. In particular, we monitor the decay constant of the kernel involved, and also analytically determine virtual aerobic and anaerobic thresholds. We demonstrate that our findings for the virtual anaerobic threshold on average agree with the results of exercise tests. We believe this work is an important step forward in performance optimization by opening up avenues for switching to adaptive training programs that take into account the current physiological state of an athlete.
... Six weeks before the lockdown period, the internal training load of daily swimming training was estimated by calculating the session rating of perceived exertions (session-RPE) using a 10-point Borg scale. 9,10 During the 11 weeks of lockdown, the coach provided training guidelines for all swimmers prescribing daily dryland training. To assess the swimmers' training content during the lockdown period, a daily physical activity questionnaire was completed by each swimmer. ...
... The duration in minutes and the perceived difficulty of each training type and session were recorded daily for estimation of the session-RPE dryland training load. 10 For the statistical analysis, the mean training load of the last 6 weeks of swimming training and the mean training load of the 11 weeks of lockdown period were compared. ...
Purpose:
To examine the effect of dryland training during an 11-week lockdown period due to COVID-19 on swimming performance.
Methods:
Twelve competitive swimmers performed 50- and 300-m maximum-effort tests in their preferred stroke and 200-, 400-, and four 50-m front crawl sprints (4 × 50 m) before and after the lockdown period. Critical speed as an index of aerobic endurance was calculated using (1) 50-, 300-, and (2) 200-, 400-m tests. Blood lactate concentration was measured after the 400- and 4 × 50-m tests. To evaluate strength-related abilities, the dryland tests included handgrip and shoulder isometric strength. Tethered swimming force was measured during a 10-second sprint. During the lockdown period, dryland training was applied, and the session rating of perceived exertion training (sRPE) load was recorded daily.
Results:
sRPE training load during the lockdown was decreased by 78% (16%), and critical speed was reduced 4.7% to 4.9% compared to prelockdown period (P < .05). Performance time in 200, 300, and 400 m deteriorated 2.6% to 3.9% (P < .05), while it remained unaltered in 4 × 50- and 50-m tests (P > .05). Tethered force increased 9% (10%) (P < .01), but handgrip and shoulder isometric force remained unaltered (P > .05). Blood lactate concentration decreased 19% (21%) after the 400-m test and was unchanged following the 4 × 50-m tests (P > .05).
Conclusions:
Performance deterioration in the 200, 300, and 400 m indicates reduced aerobic fitness and impaired technical ability, while strength and repeated-sprint ability were maintained. When a long abstention from swimming training is forced, dryland training may facilitate preservation in short-distance but not middle-distance swimming performance.
... Monitoring training loads is extremely important, since stimuli incompatible with the athlete's physical capacity can trigger negative and/or null adaptations. 3 Regardless of the type of period chosen by the technical committee, in swimming the stimuli are planned and distributed in generally annual macrocycles and the polishing step is carried out two to three weeks before the target competition. 4,5,6 At this stage, in addition to maximizing physical capabilities, the recovery of motor, tactical, psychic and emotional actions (stress control, anxiety and motivation) must be carefully monitored, with the knowledge that restful sleep is also part of this recovery strategy. ...
... 16 The Subjective Effort Perception (SEP) monitored the internal load through the SEP-session. 2,3,22 The calculation was composed of the product between the training intensity, obtained through the SEP session and the total time of the session in minutes, presenting the value in arbitrary units (AU). 5,21 Drowsiness was checked using the Karolinska Scale, applied together with the SEP session, consisting of 9 points, starting with a value of 1 ("Very alert") and ending with a value of 9 ("Very sleepy, struggling with sleep, a lot of effort to stay awake"). ...
Introduction: Tapering is a decisive phase in planning a young swimmer's preparation for competition. During this period, not only training loads, but also recovery, which includes sleep quality, must be constantly monitored.
Objective: This study aims to investigate sleep behavior as a variable directly influenced by training load during the tapering phase of training for young swimmers.
Methods: A polysomnography test was performed at the beginning of the tapering phase, as a baseline for sleep variables. In each daily training session, the overload and recovery variables were measured. The internal training load was evaluated in the PSE session and the external load by quantifying the training. The recovery variables were divided into the recovery variable, assessed using the TQR questionnaire, and sleep variables, which included sleepiness, scored using the Karolinska scale, and sleep behavior, using an actigraph and a sleep diary.
Conclusion: It is concluded that there is no significant influence between training loads and sleep variables. However, a strong association was observed between TST and EL (External load), in the irregular sleep group.
... 'Where is the load?' Revisiting the Strategic Assessment of Risk and Risk Tolerance (StARRT) framework for return to sport by including an athlete's sport-specific training capacity? Matt Taberner ,1,2 Daniel Dylan Cohen , 3,4 Anthony Carter, 5,6 Johann Windt 7,8 ...
... It is perhaps the most ecologically important consideration since it encapsulates the 'actual' demands and requirements of the athlete's sport and their level of participation. [3][4][5] While the importance of monitoring training load in rehabilitation has been established, 6 7 we emphasise that sufficient consideration has not been given to the role of the athlete's sports-specific training capacity in decision-making throughout the RTS continuum. 5 8 ...
... Such measures are helpful to compare the amount of exercise performed by different trainees 3 . However, ETL does not consider the internal processes of training assimilation (Wallace, Slattery, & Coutts, 2009). Internal training load (ITL) is the individual and relative physiological and psychological stress felt by the trainees due to training and the rest of the demands in their daily lives (Bourdon et al., 2017;Halson, 2014). ...
... ITL enables monitoring training adaptation by looking into physiological biomarkers (e.g., average heart rate, heart rate variability, or saliva tests) and/or perceived self-reported status (e.g., rating of perceived exertion after training; or rating of perceived fatigue, muscle soreness, stress and sleep satisfaction before training) (Miguel et al., 2021). The study of training principles and variations of ITL and ETL is mainly based on research with professional athletes (Bourdon et al., 2017;Wallace et al., 2009;Halson, 2014;Miguel et al., 2021). Little attention has been given to patients with cancer in this matter, but there is evidence on how exercise has shown improvements in HRV parameters linked to cardiac autonomic balance (Niederer et al., 2012;Dias Reis et al., 2017). ...
Alleviating the burden of breast cancer has become in one of the biggest challenges of our times. The advances in surgery, radiotherapy, and systemic therapy have improved the survival rates of patients with breast cancer, but have also produced a higher number of patients suffering short- and long-term side effects, with high the risk of recurrence, developing comorbidities, and death. Therapeutic exercise poses a means to address this issues; however, exercise interventions in patients with cancer are often adhered to the same therapeutic exercise guidelines. This results in one-size-fits-all exercise prescriptions for all adults, regardless their individual exercise capabilities and needs, which may lead to inadequate training adaptation.
The mobile health (mHealth) paradigm has enabled the remote and individual monitoring of health through wearable sensors and smartphones. Personalizing training adaptation with an mHealth approach has already been successfully conducted in sports settings, and the literature suggests that similar strategies may translated to patients with chronic conditions such as breast cancer. However, recent works do not target the adjustment of training doses to the individual needs of the patients.
This thesis presents three contributions to support the personalization of therapeutic exercise intervention in patients with breast cancer. First, ATOPE+, an mHealth system to support the remote monitoring of patients’ training load through heart rate variability (HRV), self-reported wellness, and Fitbit physical activity and sleep data. ATOPE+ also integrates a decision-support system with expert rules that automatically trigger daily exercise recommendations for patients. Second, the ATOPE+Breast dataset, an open dataset describing the continuous evolution of training load during therapeutic exercise intervention for 23 patients with breast cancer. Third, a clustering approach to assess training needs in patients with breast cancer. Data science and artificial intelligence (AI) are leveraged in this approach to better understand the different states of the patient throughout an exercise
intervention, and eventually serve as a tool to make more informed decisions when prescribing an exercise dose.
The potential of these contributions may lead to new research directions in the personalization of therapeutic exercise interventions in real-life scenarios, specially regarding the application of mHealth and AI to improve chronic conditions.
... For this measure, the swimmers were standing inside the pool with water at the swimmer's chest level, avoiding any variation between land and water environment. For the RPE, where it was verified at the end of the test, the modified Borg's RPE score (scale from 0 to 10) proposed for swimming was used, considering 0 as "Rest" and 10 as "Maximal" 28 . The SN was verified right after the RPE evaluation considering the middle of the pool as a reference for rounding the quantity, which was also checked by the video recording of the test days. ...
... Considering that the RPE has not reached the last stage, this fact can be corroborated in the difficulty of the individuals to interpret the scale at the end of the test. Although the RPE has a good validity in the intensity classification 28,32 . However, Abbreviations: BHR -before (test) heart rate in beats per minute; AHRafter (test) heart rate in beats per minute; SN -swimming number (laps); S m -Average speed in meters per second (average number of laps performed); L cic -stroke cycles length in meters per cycle (average number of laps performed); SI -stroke index. ...
Abstract Aim: This study aimed to verify the reproducibility of an endurance test for master swimmers. Methods: Seventeen male swimmers, aged from 30 to 50 years (35.06 ± 5.36), weight (78.71 ± 13.06 kg), height (174.35 ± 0.07 cm), participated in this study. The participants underwent the Progressive Swim Test (PSwT), which corresponds to swimming progressively to exhaustion in a 25-meter pool, guided by the recording of sound signals indicating the swimming rhythm. We verified the following variables: heart rate before the test (BHR) and right after the end of the test (AHR), followed by the rate of perceived exertion (RPE) and a total of laps performed (SN - swimming number). For comparison between the three days of tests, the one-way repeated measures ANOVA with Tukey's Post-Hoc was performed. Relative reproducibility was performed by the r test and the intraclass correlation coefficient (ICC). Absolute reproducibility was determined using the coefficient of variation (CV) and the confidence interval (CI). Results: The results showed high reproducibility in (PSwT) in master swimmers in the analyzed variables of intergroup and intragroup with relative reproducibility of r > 0.60 and ICC > 0.70 and absolute reproducibility with CI 95% (lower −1.10 and upper 0.99) and CV < 10%. Most of the cases were within the limits of agreement of the Bland-Altman tests, all variables were considered a level of significance with (p
... Completing an 'easy' day at a greater perceived exertion than planned by the coach may result in an athlete being under-recovered for a subsequent high-quality session and thus be unable to achieve the required training intensities. Coaches of endurance athletes can underestimate session RPE relative to what the athletes expressed (Foster, Helmann, Esten, Brice, & Porcari, 2001;Wallace, Slattery, & Coutts, 2009). For coach-prescribed easy days, athletes can report a higher training load, yet on prescribed harder days, athletes described a lower intensity and load (Foster, Helmann, et al., 2001;Wallace et al., 2009). ...
... Coaches of endurance athletes can underestimate session RPE relative to what the athletes expressed (Foster, Helmann, Esten, Brice, & Porcari, 2001;Wallace, Slattery, & Coutts, 2009). For coach-prescribed easy days, athletes can report a higher training load, yet on prescribed harder days, athletes described a lower intensity and load (Foster, Helmann, et al., 2001;Wallace et al., 2009). This intriguing phenomenon suggests potential underrecovery of athletes, a heightened need for global measures of training load which encompass multiple facets of the training dose and response, and the need for monitoring of athlete recovery (Kellmann, 2010). ...
... Therefore, it is important to understand the relationship between sRPE-TL and measures of external load by examining its validity and utility as a tool for monitoring training load within a particular team sport setting. Several studies have done so and have provided preliminary evidence to indicate that sRPE-TL is highly correlated with total distance [15], accelerometer load [16], and high-speed efforts [16]. Further, a recent meta-analysis indicates that sRPE-TL is more strongly associated with external load compared to traditional HR-based measures of internal load [17]. ...
... This aspect of affordability and minimal equipment need has contributed to its popularity as a monitoring tool within sports. The observed relationship between sRPE-TL and measures of the external workload from the current study aligns with those previously reported in soccer [14,16,[24][25][26][27] and across a variety of sport types [11,15,[28][29][30][31][32][33]. Previous work in semiprofessional soccer athletes indicated that sRPE-TL was strongly associated with measures of external load such as total distance covered and PlayerLoad™ over 44 training sessions [16]. ...
Purpose:
The purpose of this study was to determine whether session rating of perceived exertion-derived training load (sRPE-TL) correlates with GPS-derived measures of external load in National Collegiate Athletics Association (NCAA) Division I female soccer athletes.
Methods:
Twenty-one NCAA Division 1 collegiate women's soccer athletes (11 starters, 10 non-starters; 65.1 ± 7.2 kg, 168.4 ± 7.9 cm, 20.3 ± 1.5 yrs) volunteered to take part in this study. Data for this study were collected over the course of 16 weeks during the 2018 NCAA women's soccer season. External load and heart rate (HR) data were collected during each training session and match during the season. At least 30 min after the end of an activity (e.g., match or practice), athletes were prompted to complete a questionnaire reporting their perceived exertion for the session. sRPE-TL was calculated at the end of the season by multiplying perceived exertion by the respective session duration.
Results:
sRPE-TL was very strongly correlated with total distance, distance covered in velocity zones 1-3, the number of accelerations in zones 4 and 5, total PlayerLoad™, and PlayerLoad™. For internal load, sRPE-TL correlated very strongly (0.70 ≤ |r| < 0.90) with Edward's and Bannister's TRIMP and strongly (0.50 ≤ |r| < 0.70) with duration spent in in heart rate zones 5 and 6 (80-90% and 90-100% max HR, respectively) while correlations with maximum HR (bpm), mean HR (bpm), and mean HR (%) and sRPE-TL were moderate (0.30 ≤ |r| < 0.50).
Conclusions:
In NCAA Division I women soccer, sRPE-TL is strongly associated with external measures of workload. These relationships were stronger during match play, with acceleration load and total distance exhibiting the strongest relationship with sRPE-TL.
... This study found no overall differences and very large relationships between RPE vs iRPE and sRPE vs isRPE, when all participants were combined, for training sessions in which major elements of the training were executed as described by the coach. The magnitude of these relationships was similar to the relationships found in studies investigating individual sports [5,23,27], but contrasts to the weak and moderate relationships found in studies investigating team sports [16,28]. These differences can likely be ascribed to the inherent differences between team and individual sports. ...
... For training sessions performed at low intensity, the RPE scores for the cyclists were lower when compared to the iRPE scores of the coach. This conflicts with findings in literature where other sports yielded higher RPE scores for low-intensity training sessions when compared to the iRPE score of the coach [5,16,19,27]. This could be explained by the use of the polarized training model by the coach, which is based on an approximate 80-to-20 ratio of low-intensity to high-intensity training [30]. ...
This study aimed to investigate whether (semi-)professional cyclists’ execution of a training program differs from the coach’s designed training program. Also, the study sought to ascertain, in instances where the training sessions were indeed executed as designed by the coach, whether the perception of the cyclists differed from the intention of the coach. This study highlights the differences between the coach and the individual cyclist. In total 747 training sessions were collected from 11 (semi-)professional cyclists. Rating of Perceived Exertion (RPE) and session Rating of Perceived Exertion (sRPE) were compared with intended RPE (iRPE) and intended sRPE (isRPE), planned by the coach. Pearson’s correlation, regression coefficients and Typical Error of Estimate (TEE) were used to identify differences between the executed and planned training sessions. Moderate to large TEEs were noted between executed and intended sRPE, which indicates that cyclists do not always execute the training program planned by the coach. Furthermore, when the training was executed as planned by the coach, very large correlations but moderate to very large TEEs were noted between cyclists’ (s)RPE and the coach’s i(s)RPE, with unique individual regression coefficients. This indicates that the relationship between RPE and iRPE is unique to each cyclist. Both the different execution and perception of the training program by the individual cyclists could cause an impaired training adaptation. Therefore, the coach must pay attention to the perception of training sessions by the individual cyclist. Improved individual management of training load could result in the optimization of the proposed training program.
... The internal load is defined as individual changes caused by the external workload stimuli [6,7] and enables assessment of the athlete's physiological and psychological stresses [8]. External load refers to the amount of workload irrespective of internal physiological characteristics [7,9]. One of the methods to monitor internal workload was proposed by Foster et al. [10] using the rating of perceived exertion (RPE) of the session associated with training time. ...
... Perceived exertion has been demonstrated as a valid method for estimating intensity. Borg's original scale of exertion (6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20) has been primarily used to monitor aerobic exercise [11]. The Borg CR10 [32] and OMNI scale [33] provide exertion ratings from 1 to 10 and have also been determined as valid methods to quantify perceived exertion. ...
The present study aimed to validate the perceived exertion scale based on the repetitions in reserve (RIR) of Paralympic Powerlifting (PP) athletes. Twenty-one PP athletes were assessed in the one-maximum repetition test (1RM) of the bench press exercise, maximum repetition strength tests with loads corresponding to 90%, 85%, 80%, and 75% of 1RM, and 4-repetitions strength tests (4-repST) with 100%, 90%, 85%, 80%, and 75% of the 1RM. The RIR scale was assessed after each set of the 4-repST and compared to the 1RM and maximum strength tests. For criterion validity, the total estimated repetition was significantly lower compared to the maximum strength test repetitions in the lower scores of the RIR scale (median=7.0 vs. 9.0 for 75% of 1RM). The total estimated repetition correlation with maximum strength was very high and significant (ICC=0.91). Using the Bland and Altman method, the difference between means was 0.9 reps, and the interval around differences was 6.4 reps. For construct validity, and the RIR scale presented high correlation with 1RM intensities (rho=0.86, p≤0.05). The RIR scale was validated and coaches and sports trainers can use this monitoring tool to ensure submaximal loads when improving lift technique, which is extremely rigorous in PP.
... Typically, training is prescribed based on the measurement of external load, which can be varied based on volume or intensity. External load can be defined as the work completed by an athlete measured independently of their internal responses (85). External load is often represented by surrogate measures such as distance, speed, and acceleration (33) or the time spent performing various game-relevant tasks such as gliding, pushing, resting, shooting, and pushing with the ball (5). ...
... Na natação as sessões de treino são prescritas tendo como referência algumas variáveis como a distância nadada (volume) ou velocidade de nado (intensidade), e a cada sessão ocorre o aumento gradativo destas cargas de treino, procedimento que é comum na tentativa de melhorar o desempenho dos atletas (Wallace, 2009;Shell et al., 2020). É adequado destacar que nadadores costumeiramente competem em mais de um tipo de modalidade ao longo de uma competição, variando o ritmo de sua braçada, o que pode influenciar em algum nível o seu rendimento em provas de longa e curta duração (Stewart & Hopkins, 2000). ...
A participação olímpica do Brasil na modalidade dos 50 metros livre desde a primeira olimpíada em que esta modalidade foi introduzida em 1988 até a última olimpíada de Tóquio 2020, pode trazer evidências que ajudem a nortear o entendimento da participação esportiva dos atletas brasileiros nesta modalidade. Vários são os aspectos que podem interferir no desempenho dos atletas, tais como: Aspectos físicos, técnicos, táticos e emocionais. Sendo, portanto, importante investigar a consistência da performance brasileira nesta modalidade. Este trabalho teve como objetivo discutir criticamente o desempenho esportivo dos atletas brasileiros em provas de 50 metros livres. Este estudo adota a abordagem quantitativa com análise descritiva é aplicada a fim de observar um fenômeno e as condições, fatos e variáveis que contribuíram para os acontecimentos que estavam relacionados com o fato proposto. Os dados foram obtidos através do site: “https://olympics.com/olympic-games”, com informações disponibilizadas pelo próprio Comitê Olímpico Internacional (COI). Entre os quinze melhores tempos, das quatro vezes que os brasileiros subiram ao pódio, três tempos estão entre os melhores sendo que um está no Top-3 de melhores tempos da história desta modalidade em específico, o que mostra uma consistência nos dados de desempenho dos atletas brasileiros. Em um cenário de acentuada desigualdade, o esporte se apresenta como um mecanismo de inclusão social, e que apesar das adversidades, os atletas brasileiros tem demonstrado consistência em resultados olímpicos ao longo da trajetória desta modalidade.
... Similar analyses have been often made in taekwondo [32][33][34]. Furthermore, such examinations are regularly performed in soccer [35][36][37][38] and swimming [39,40]. However, the literature is lacking in defining training loads based on HR levels in K1 kickboxing. ...
Background: Kickboxing is a combat sport in which scientific observations are regularly made to improve the quality of the training process. Heart rate monitoring is the basic form of the evaluation of training load and diagnosing the athlete's capabilities. The purpose of this study was to determine training load based on heart rate measurements in K1 kickboxers. Methods: The study was conducted on 18 kickboxers, with HR recorded over a 3-round kickboxing fight. HRmax level was calculated for each athlete according to the most recent formula. Based on these data, the percentage training load was determined according to the needs arising from the training periodization. Results: The results of the study showed that training of K1 kickboxers is based primarily on submaximal heart rates, which increase with each round of the bout (p<0.001). Conclusions: The training load for a K1 kickboxing bout based on maximum heart rate should be 95.44% HRmax in the first round, 96.23% HRmax in the second, and 97.01% HRmax in the round..
... However, given that the use of heart-rate-based methods is not always feasible [10], subjective and self-reporting measures have become common, low-cost alternatives for monitoring ITL [11,12]. Thus, the session rating of perceived exertion (sRPE) is increasingly used as a simple, noninvasive technique for monitoring ITL [10,[13][14][15]. Previously, it was shown that sRPE is highly correlated with heart rate and lactate concentrations during intermittent team sports such as soccer [4,10,[16][17][18][19][20][21]. ...
The aim of this study was to identify the external training load (ETL) variables that are most influential on the session rating of perceived exertion (sRPE) during elite soccer training. The participants (n = 29) were adult male soccer players from a single team that competed in Croatia’s highest national soccer competition in the 2021/2022 season. Data were collected using the 10 Hz Global Positioning System from 66 training sessions, and a total of 1061 training observations were undertaken. The univariate and multivariate relationships among the predictors (ETL variables) and the criterion (sRPE) were assessed using forward stepwise multiple regressions and Pearson’s correlations, respectively. ETL variables explained 63% of the variance in the sRPE (Multiple R = 0.79; p < 0.01), and the model was successfully cross-validated. The significant partial regressors were total distance (β = 0.66), metres per minute (β = −0.47), high-intensity accelerations (β = 0.22) and decelerations (β = 0.18), and sprint distance (β = 0.14). All ETL variables were significantly correlated with the sRPE (all p < 0.01), with the highest correlations found for total distance covered (r = 0.70) and high-intensity accelerations and decelerations (r = 0.62 and 0.65, respectively). Such results show that (i) the total distance and acceleration rates during the training sessions are the most important predictors of the sRPE, and (ii) a combination of different ETL variables predicts the sRPE better than any individual parameter alone. This study shows that both the volume and intensity of training are related to players’ internal responses. The findings ultimately provide further evidence to support the use of sRPE as a global measure of training load in soccer players.
... It is difficult to impede the ability to derive accurate cause and-effect relationships between the training an athlete does and the resultant changes in performance. The fact that there is often disagreement between the perceptions of training load of the coaches compared with that of the athletes [3,4]. ...
International result-oriented performance in sports requires systematic scientific training. A proper pedagogical approach is required for systematic loading of the athletes in order to record-breaking performance. The performance of an athlete largely depends upon a progressive training load for a relatively long period of time. The degree of mechanical tension, subcellular damage, and metabolic stress can all play a role in exercise-induced muscle adaptations. The process of adaptation largely depended upon the ratio of load and recovery stimulus. Thus the load dynamics and proper adaptation is reflected in the achievement of an athlete. The present research review-based article discussed systematically the procedure of training load, importance of recovery, and adaptation of load.
... Participants bent one knee to 90˚ for 1 s and then extended the leg for 1 more sec. We measured the exercise intensity using the 10-point Rating of Perceived Exertion (CR-10: RPE) (39) scale that is shown in Table 1. We measured only the first set and the last set. ...
... km): 75% of aerobic training, 15% of HIIT, and 10% of HIT (Table 1, Figure 1). Rating of perceived exertion load (RPE load) was calculated by multiplying the swimmer's rating of perceived exertion (RPE, scale 1-10) after 30 min of each session by the training volume (duration) of the session [22][23][24] (Table 1). ...
... km): 75% of aerobic training, 15% of HIIT, and 10% of HIT (Table 1, Figure 1). Rating of perceived exertion load (RPE load) was calculated by multiplying the swimmer's rating of perceived exertion (RPE, scale 1-10) after 30 min of each session by the training volume (duration) of the session [22][23][24] (Table 1). ...
This study aimed to examine the effect of four weeks of aquatic high-volume training (HVT) on the psychological state (somatic, cognitive anxiety, and self-confidence) and sprint swimming performance (50 m front crawl) compared to the standard training program (moderate volume training) in competitive swimmers. Twenty-eight male competitive swimmers participated in this study and were randomly allocated into two groups: HVT group (n = 14; age = 16.4 ± 0.31 years) and control group that underwent the standard training program (n = 14; age = 16.1 ± 0.30 years). All psychological state variables and swimming performance were measured in pre and post-test. Our findings showed a significant increase in anxiety state (34.13% to 45.83%; ES = 3.26 to 3.38) and a significant decrease in self-confidence (18.43%; ES = 2.39) after four weeks of HVT, while all psychological state variables remained unchanged in the control group (p > 0.05). In addition, our results showed no significant enhancement in swimming performance in both groups (p > 0.05). The sudden increase in training mileage negatively affected the anxiety, decreasing the state of self-confidence of the participants. In addition, four weeks of high training volume are insufficient to improve swimming performance. To conclude, gradually increasing the volume of the training load may be an adequate solution to promote adaptation to the effort, thus maintaining the stability of the psychological state of swimmers. In addition, it is recommended to integrate a concurrent mental preparation program with high-volume training to monitor the psychological state of competitive swimmers.
... When (23) the studies were evaluated according to the average number of citations per year, the most influential first article was the work of Sargent et al. (2014) . The (24) second most influential article was the study of Wallace et al. (2009) . The third most influential article was the (25) study of Gleeson et al. (1999) . ...
Objective: Although the number of global studies on swimming has increased, there are still no bibliometric studies in the literature. This study aimed to present a medical perspective by examining scientific articles published in the field of swimming sports with statistical methods. Material and Method: Articles on swimming published between 1980 and 2021 were obtained from the Web of Science database. Spearman's correlation coefficient was used for correlation analysis. Network visualization maps were used to identify trending topics. Results: A total of 21732 publications were found. 2392 (70.5%) of these publications were articles. The top 3 contributing countries to the literature were USA (462, 19.3%), UK (331, 10.4), and Australia (298, 12.1%). The top 2 most active institutions were Universidade Do Porto (n=93), and Australian Institute of Sport (n=82). The most active journals with the highest number of articles were International Journal of Sports Medicine (n=171), and Journal of Sports Sciences (n=150). According to the average number of citations per article, the top most influential journal was Journal of Sport & Exercise Psychology (citation: 51.8). Conclusion: The most studied subjects related to medicine and health in swimming were blood lactate, heart rate, fatigue, shoulder, body composition, anthropometry, oxygen uptake, oxidative stress, disability, energy cost, electromyography, oxygen consumption, physiology, motivation, physical activity, aging, muscle strength, shoulder pain, testosterone, core temperature, and stress. General topics studied in recent years were athletic performance, physiology, stress, strength, disability, paralympic, electromyography, youth, shoulder pain, sports, force, competition, kinetics, adolescent, sport, swimming training, and aging.
... Спорт, хусусан, юқори натижалар спортида, профессионал спортда юкламаларни меъёрлаштириш масалаларига катта эътибор қаратилади. Жисмоний тарбия ва оммавий спорт амалиётида эса аксар ҳолатларда бунга етарли эътибор қаратилмайди [4]. ...
В практике образовательных учреждений в большинстве случаев уделяется недостаточное внимание самостоя-
тельному привлечению студентов к занятиям физической культурой и массовым спортом, отсутствуют соответ-
ствующие их интересам кружки, занятия проводятся по единой для всех программе. Поэтому в этих упражнениях
не уделяется внимания определению нагрузок и их согласованию в теле занимающихся. Не учитываются интересы
студентов и не поддерживаются студенческие инициативы. Это, в свою очередь, снижает интерес студентов к
физической культуре и массовому спорту.
В данной статье рассматривается важность балансировки нагрузки в занятиях физической культурой и массо-
вым спортом.
... This is consistent with other studies showing that session-RPE can be considered a valid, reliable and consistent indicator of global internal load (Coutts et al., 2003;Haddad et al., 2017;Impellizzeri et al., 2004;Impellizzeri, Rampinini & Marcora, 2005). This method was initially proposed by Foster et al. (1996) for monitoring internal training load in endurance athletes, but more recently is has also been proven to be applicable to other sports and physical activities with both men and women of different age and among different levels of experience (Haddad et al., 2017;Lupo, Ungureanu & Brustio, 2020;Wallace, Slattery & Coutts, 2009). ...
Objective
The present study seeks to explore the relationship between measures of cycling training on a given day and the heart rate variability (HRV) and mood states obtained the following morning. The association between HRV and mood state is also studied, as is the relationship between internal and external measures of training.
Methods
During a 6-week period, five recreational road cyclists collected 123 recordings of morning HRV and morning mood, and 66 recordings of training power and rate of perceived exertion (RPE). Training power was used as an external measure of performance and RPE as an internal measure of performance. The HRV parameters used in the study were the mean of RR intervals (mean RR) and the standard deviation of all RR intervals (SDNN) as time domain analysis, and the normalized high frequency band (HFnu), normalized low frequency band (LFnu) and the ratio between low and high frequency bands, as frequency domain analysis. Mood was measured using a 10-point cognitive scale.
Results
It was found that the higher the training power on a given day, the lower the HFnu and the higher LF/HF were on the following morning. At the same time, results showed an inverse relationship between training and mood, so the tougher a training session, the lower the mood the following day. A relationship between morning HRV and mood was also found, so that the higher mean RR and HFnu, the more positive the mood (r = 0.497 and r = 0.420 respectively; p < 0.001). Finally, RPE correlated positively with external power load variables (IF: r = 0.545; p < 0.001).
Conclusion
Altogether, the results indicate a relationship between training of cyclists on a given day and their morning HRV and mood state on the following day. Mood and HRV also seem positively related. It is argued that developing a monitoring system that considers external and internal training loads, together with morning mood, could help understand the state of the individual, enabling feedback to athletes to facilitate the adaptation to training and to prevent problems associated with overtraining. However, more research is needed to further understand the association between the different variables considered.
... In order to meet the requirements of this program, students are engaged in educational work at school and at home in order to gain knowledge. [2] of course, in order to perform such a great mental loading work, one must be energetic and healthy. It's no secret that a healthy child will perform all tasks at a high level of quality, he will have free will, aspiration, curiosity. ...
In the practice of higher education institutions, the independent involvement of students in physical education and mass sports is not given enough attention in the case of the opposite, there are no circles of interest to them, classes are conducted for all on the basis of the same program. Therefore, in these exercises, there is no emphasis on setting loads and coordinating them with the body of the engaged person. Such student interest is not taken into account, student initiatives are not supported. These in turn reduce the interest of students in physical education and mass sports. As a result of this, low activity occurs in student activities, and as a result of low activity, various diseases develop in their body, immunityitet decreases, students will not have access to information about physical loads. In this article, we will talk about the importance of normalizing loads in physical education and mass sports-wellness training.
... In the practice of physical education and mass sports, in most cases, this is not given enough attention. [4] Load normalization is a specific diagnosis of physical education and mass sports. ...
Annotation In the practice of educational institutions, in most cases, insufficient attention is paid to the independent involvement of students in physical education and mass sports, there are no clubs that suit their interests, classes are conducted on the basis of the same program for all. Therefore, in these exercises there is no attention to the definition of loads and their coordination in the body of the trainees. Students' interests are not taken into account and student initiatives are not supported. This, in turn, reduces students' interest in physical education and mass sports. As a result, students become inactive, and as a result of inactivity they develop various diseases in the body, immunity is reduced, students do not have information about physical activity. This article discusses the importance of load balancing in physical education and mass sports.
... In order to meet the requirements of this program, students are engaged in educational work at school and at home in order to gain knowledge. [2] of course, in order to perform such a great mental loading work, one must be energetic and healthy. It's no secret that a healthy child will perform all tasks at a high level of quality, he will have free will, aspiration, curiosity. ...
In the practice of higher education institutions, the independent involvement of students in physical education and mass sports is not given enough attention in the case of the opposite, there are no circles of interest to them, classes are conducted for all on the basis of the same program. Therefore, in these exercises, there is no emphasis on setting loads and coordinating them with the body of the engaged person. Such student interest is not taken into account, student initiatives are not supported. These in turn reduce the interest of students in physical education and mass sports. As a result of this, low activity occurs in student activities, and as a result of low activity, various diseases develop in their body, immunityitet decreases, students will not have access to information about physical loads. In this article, we will talk about the importance of normalizing loads in physical education and mass sports-wellness training.
... In order to map the effects of training and the performance outcomes, we define a TL index that represents a quantitative measure of the effort done by the athlete and the underpinning induced stress. Accordingly, TL are commonly dissociated into i) an external load defined by the work completed by the athlete, independently of his internal characteristics (Wallace, Slattery, and Coutts 2009), and ii) an internal load that corresponds to the psycho-physiological stresses imposed on the athlete in response to the external load (Impellizzeri, Rampinini, and Marcora 2005). In other words, TL being quantified in both quantitative and qualitative ways, it would allow answering the questions: what amount of effort has been done by the athlete, and what does it really means, among others, in terms of physiological adaptations? ...
The first models of training effects on athletic performance emerged with the work of Banister and Calvert through the so-called Fitness-Fatigue model (FFM). One major drawback of FFMs is that the features stem from a single source of data. That is not in line with the existing consensus about a multifactorial aspect of athletic performance. Hence, multivariate modelling approaches from statistics and machine-learning (ML) emerged.
A research issue arises from the quantification of training Loads (TL) in resistance training (RT) which lack of physiological evidence. In the first study, we provided a new method of TL quantification in RT based on physiological observations. To achieve that, we initially modelled the torque-velocity profiles of fifteen participants during an isokinetic leg extension task and assessed a set of physiological responses to various resistance exercises intensities. Each session was volume-equated according to the formulation of volume load (i.e. the product of the number of repetitions and the relative intensity).
Higher led to greater muscular fatigue described by neuromuscular impairments. Conversely, systemic and local pulmonary responses (measured through oxygen uptake) and metabolic changes (according to blood lactate concentrations) were more significant at low intensities, suggesting different contributions of metabolic pathways.
From these results, we provided a new index of TL based on the neuromuscu- lar impairments observed at exercise. We showed that to exponentially weight TL by the average rate decay of force development rate yielded better correla- tions with any of the significant physiological responses to exercise. In addition, information compressed within a principal component could be a valuable TL index.
In the second study, we provided a robust modelling methodology that relies on model generalisation. Using data from elite speed skaters, we compared a dose-response model to regularisation methods and machine-learning models.
Regularisation procedures provided the greatest performances in both generalisa- tion and accuracy. Also, we highlighted the pertinence of computing one model over the group of athletes instead of a model per athlete in a context of a small sample size.
Finally, ML approaches could be a way of improving FFMs through ensemble learning methods.
In the third study, we modelled acceleration-velocity directly from global posi- tioning system (GPS) measurements and attempted to predict the coefficients of the relationship between acceleration and velocity.
First, a baseline model was defined by time-series forecasting using game data only. Then, we proceeded to multivariate modelling using commercial features. A regularised linear regression and a long short term memory neural network were compared. Finally, we extracted features directly from raw GPS data and compared these features to the commercial ones for prediction purposes.
The results showed only slight differences between model accuracy, and no models significantly outperformed the baseline in the prediction task. Given the multi- factorial nature of athletic performance, using only GPS data for predicting such athletic performance criterion provided an acceptable accuracy. Using time-domain and frequency-domain features extracted from raw data led to similar performances compared to the commercial ones, despite being evidence-based. It suggests that raw data should be considered for future athletic performance and injury occurrence analysis.
Lastly, we developed an athlete management system for long-distance runners. This application provided an athlete monitoring module and a predictive module based on a physiological model of running performance.
A second development was realised under the SAP analytics cloud solution. Team management and automated dashboards were provided herein, in close collaboration with a professional Rugby team.
... Additional strapping around the upper body may be necessary for athletes with disabilities, who may lack sufficient trunk control. Furthermore, we chose RPE instead of a speed-or power-based protocol, since athletes commonly use RPE to monitor training load and as a tool to target-specific exercise intensity zones (Foster et al., 1996;Wallace et al., 2009;Paulson et al., 2015). RPE as a measure of exercise intensity is particularly useful during upper-body exercise, especially in athletes with a disability, to account for the highly variable upper-body capacities. ...
Purpose : To investigate the test–retest reliability of physiological variables across four different test days and four different submaximal exercise intensities during seated upper-body poling (UBP).
Methods : Thirteen abled-bodied, upper-body trained men (age 29±3years; body mass 84±12kg; height 183±5cm) performed four submaximal 4-min stages of seated UBP on four separate test days. The four submaximal stages were set at individual power outputs corresponding to a rating of perceived exertion of 9, 11, 13, and 15. The absolute reliability for pairwise test-day comparisons of the physiological variables was investigated with the smallest detectable change percentage (%SDC) and the relative reliability with the interclass correlation coefficient (ICC).
Results : Absolute and relative reliability across test-day comparisons and submaximal stages were moderate to excellent for all variables investigated (V̇O 2 – %SDC range: 5–13%, ICC range: 0.93–0.99; HR – %SDC range: 6–9%, ICC range: 0.91–0.97) other than blood lactate, for which absolute reliability was poor and relative reliability highly variable (%SDC range: 26–69%, ICC range: 0.44–0.92). Furthermore, absolute and relative reliability were consistent across the low-to-moderate exercise intensity spectrum and across test days.
Conclusion : Absolute and relative test–retest reliability were acceptable for all investigated physiological variables but blood lactate. The consistent test–retest reliability across the exercise intensity spectrum and across test days indicates that a familiarization period to the specific exercise modality may not be necessary. For generalizability, these findings need to be confirmed in athletes with a disability by future large-scale studies.
... sRPE is also very commonly used in the practical setting likely due to its relative ease of implementation Akenhead and Nassis, 2016). The sRPE process is a non-invasive and simple method of calculating and quantifying an individual's TL, making it an ecologically valid and time-efficient practical tool for coaches (Edwards et al., 2018;Gomes et al., 2015;Wallace et al., 2009). It has also been suggested that sRPE is a useful tool to better guide periodisation through monitoring all type of training sessions and it is therefore key to successful training monitoring (Haddad et al., 2017). ...
Introduction: Amateur Rugby Union has an inherent risk of injury that is associated with detrimental effects on player welfare and team performance. The monitoring of players’ preparedness for, and response to, training has become an integral tool for coaches in injury risk management as it may aid in the prescription and design of training. A training monitoring system (TMS) should be both attainable and scientifically grounded, however, there is a paucity of information in relation to monitoring training at the amateur level and the inherent challenges this presents.
Aim: The aim of this doctoral research was to explore the associations between subjective measures of training load (TL) and wellness with injury occurrence in match-play and training sessions in amateur rugby in Ireland. Fundamentally, this programme of research aimed to offer practical methods of monitoring training that has the potential to mitigate injury risk and, in turn, benefit the health and wellbeing of players.
Methods: Five studies were conducted in this programme of research which: (1) systematically reviewed and critically appraised the existing relevant literature regarding associations between the acute:chronic workload ratio (ACWR), and injury in team sports (Chapter Three), (2) established the current training monitoring practices of practitioners working with in amateur Rugby Union clubs (Chapter Four), (3) developed and evaluated an online TMS (Chapter Five), examined methods of addressing missing TL using missing value imputation (MVI) (Chapter Six), and (5) explored possible associations between subjective self-reported measures of wellness, various training load metrics, and injury in amateur Rugby Union.
Results: The findings of the systematic review support the association between the ACWR and non-contact injuries and its use as a valuable tool for monitoring TL as part of a larger scale multifaceted monitoring system that includes other proven methods. 72.7% of practitioners working with amateur Rugby Union clubs monitored training with the most common method being the session rate of perceived exertion (sRPE), used in 83.3% of monitoring systems. The 3 most prominent challenges to motoring training were found to be lack of player compliance, data inconsistency and match-day challenges. Practitioners should strive to keep missing TL data at a minimum, however imputing missing data with the Daily Team Mean (DTMean) was the most accurate MVI method of the twelve MWI methods examined. Lastly, logistic regression found significant, strong associations (odds ratio (OR) = 6.172, 95% CI = 0.254 – 0.473, p < 0.001) between the occurrence of injury and the summative score of overall wellness (0-day lag). Significant weak associations were found between the occurrence of injury and the majority of ACWR calculations when 3-day and 7-day injury lag periods were applied.
Conclusion: The findings of this programme of research support the positive association between injury and both subjective wellness and TL. Monitoring training of amateur athletes has its own unique challenges and confounders (e.g., limited time with players, occupation of players, resources available). Practitioners must accept that due to the complexity of injury, a risk will always be present and instead focus on prescribing training that they deem will promote positive adaptations in a safe manner. However, a TMS consisting of subjective measures may mitigate injury risk in amateur Rugby Union by supporting decisions around training prescription.
... The sRPE method is a simple and valid method (Foster, 1998;Foster et al., 2001), and has already been applied in different endurance sports (Foster et al., 2001;Wallace et al., 2014;Roos et al., 2018;Sanders et al., 2018) including rowing (Tran et al., 2015) and has shown high reliability with different objective HRbased methods (Seiler and Kjerland, 2006;Rodríguez-Marroyo et al., 2012;Lupo et al., 2014;García-Ramos et al., 2015). In addition to general "overall internal load" parameters of the training session, previous studies have also used rating of perceived exertion (RPE) as effort-based quantification to distinguish between easy or hard training sessions based on RPE value using the same VT1/VT2 anchor points as for Lucia TRIMP (Seiler and Kjerland, 2006;Wallace et al., 2009). Accordingly, we can further calculate training load as Easy, Moderate, or Hard sessions (Pind et al., 2019). ...
Purpose: The aim of this study was to investigate the interaction of training load quantification using heart rate (HR) and rating of perceived exertion (RPE)-based methodology, and the relationship between internal training load parameters and subjective training status ( Fatigue ) in high-level rowers during volume increased low-intensity training period.
Methods: Training data from 19 high-level rowers (age 23.5 ± 5.9 years; maximal oxygen uptake 58.9 ± 5.8 ml·min ⁻¹ ·kg ⁻¹ ) were collected during a 4-week volume increased training period. All individual training sessions were analyzed to quantify training intensity distribution based on the HR time-in-zone method (i.e., HR Z1, HR Z2, and HR Z3) determined by the first and second ventilatory thresholds (VT1/VT2). Internal training load was calculated using session RPE (sRPE) to categorize training load by effort (i.e., sRPE1, sRPE2, and sRPE3). The Recovery-Stress Questionnaire for Athletes (RESTQ-Sport) questionnaire was implemented after every week of the study period.
Results: No differences were found between the respective HR and effort-based zone distributions during the baseline week ( p > 0.05). Compared to HR Z1, sRPE1 was significantly lower in weeks 2–4 ( p < 0.05), while sRPE2 was higher in weeks 2–3 compared to HR Z2 ( p < 0.05) and, in week 4, the tendency ( p = 0.06) of the higher amount of sRPE3 compared to HR Z3 was found. There were significant increases in RESTQ-Sport stress scales and decreases in recovery scales mostly during weeks 3 and 4. Increases in the Fatigue scale were associated with the amounts of sRPE2 and sRPE3 ( p = 0.011 and p = 0.008, respectively), while no associations with Fatigue were found for HR-based session quantification with internal or external training load variables.
Conclusion: During a low-intensity 4-week training period with increasing volume, RPE-based training quantification indicated a shift toward the harder rating of sessions with unchanged HR zone distributions. Moderate and Hard rated sessions were related to increases in Fatigue . Session rating of perceived exertion and effort-based training load could be practical measures in combination with HR to monitor adaptation during increased volume, low-intensity training period in endurance athletes.
... 2 Excessive workloads may produce adverse effects and a greater propensity to injury, overreaching, or overtraining, whereas insufficient workloads will not result in physiological adaptations. 3,4 Training workloads are divided into external, referring to the amount of workload irrespective of internal physiological characteristics, 5,6 and internal, described as individual changes caused by stimuli provided by the external workload. 6,7 External workloads make it possible to understand the athlete's skills before applying specific workloads. ...
Context:
Paracanoeing is one of the adapted sports eligible for different motor impairments. The acute:chronic workload ratio (ACWR) is an index between acute and chronic training workload. However, no studies have analyzed this variable in paracanoeing, relating it with training recovery markers.
Objective:
This study aimed to quantify the internal (session rating of perceived exertion) and external (distance traveled and total training time) training workloads in 4 experienced paracanoe athletes over 9 months and 5 canoeing events.
Design:
Cross-sectional study.
Setting:
Rehabilitation Hospital Network, Paralympic Program.
Participants:
Four experienced paracanoe athletes participated in 36 weeks of training for 5 events.
Main outcomes measures:
The daily and weekly training workload, monotony, ACWR, distance, and total training time were described for all the training phases. The perceived recovery status scale (PRS) and medicine ball throw (MBT) were used to quantify recovery.
Results:
The average daily and weekly training workload varied from 213.1 to 239.3 and 767.3 to 1036.8 arbitrary units, respectively. Average ACWR results ranged from 0.96 to 1.10 in the 4 athletes, findings that were outside the safety zone in 38% of the training weeks. All the correlations between MBT and PRS were classified as weak (ρ between .20 and .39, P > .05). ACWR showed a very weak correlation with MBT and moderately and highly significant correlations with PRS in 2 athletes, respectively.
Conclusions:
The training workloads of 4 paracanoe athletes may serve as a comparison with other periodization models. Pretraining recovery assessments (MBT and PRS) exhibited a low, nonsignificant correlation. However, ACWR correlated significantly with PRS in 2 athletes and might be a suitable tool for daily training adjustments.
... Although not directly related to biomechanics, the quantification of internal and external training loads within intensification and taper periods is critical for understanding training effects Hellard et al., 2019Hellard et al., , 2017Impellizzeri et al., 2019). For instance, the volume prescribed in different training intensities is a wellknown method for quantifying external load Hellard et al., 2017), whereas the internal load can be assessed by the session RPE method (Foster et al., 2001;Wallace et al. 2009;Barbosa et al., 2020c). These parameters should be of interest to the analyst as they can considerably affect drag and propulsion-related variables. ...
Swimming analysts aid coaches and athletes in the decision-making by providing evidence-based recommendations. The aim of this narrative review was to report the best practices of swimming analysts that have been supporting high-performance athletes. It also aims to share how swimming analysts can translate applied research into practice. The role of the swimming analyst, as part of a holistic team supporting high-performance athletes, has been expanding and is needed to be distinguished from the job scope of a swimming researcher. As testing can be time-consuming, analysts must decide what to test and when to conduct the evaluation sessions. Swimming analysts engage in the modelling and forecast of the performance, that in short- and mid-term can help set races target-times, and in the long-term provide insights on talent and career development. Races can be analysed by manual, semi-automatic or fully automatic video analysis with single or multi-cameras set-ups. The qualitative and quantitative analyses of the swim strokes, start, turns, and finish are also part of the analyst job scope and associated with race performance goals. Land-based training is another task that can be assigned to analysts and aims to enhance the performance, prevent musculoskeletal injuries and monitor its risk factors.
... At the same time, OTS is typically accompanied by high interindividual variability of symptoms. An athlete with a beginning or fully developed OTS may experience sympathetic as well as parasympathetic changes or combinations thereof (Wallace et al., 2009). Parasympathetic changes, ascribed to OTS, occur more often in endurance sports athletes, while sympathetic changes are more common in anaerobic sports (Urhausen & Kindermann, 2002). ...
The article presents an overview of important findings concerning the overtraining syndrome (OTS) in elite athletes. Although the scientific community agrees that OTS is a multifactorially determined and individually variable phenomenon, which can have a serious impact on the individual, there are still some inconsistencies. Therefore, in our study we focused on the terminology of the phenomenon, its prevalence, etiology and symptomatology. We paid specific attention to psychological instruments of detecting OTS indicators. Given that in the period of adolescence the training process in the majority of sport disciplines intensifies significantly, the context of developmental changes during this period in relation to OTS is discussed. The final part of the study summarizes the basic principles of prevention of this pathological phenomenon.
... In this context, external load is characterized as the work that an individual performs regardless of internal characteristics, whereas the internal load is defined as the individual and acute psychophysiological response (e.g., physiological, psychological, motor, and biomechanical responses) to the external load. This response is influenced by lifestyle (e.g., diet and sleep) and environmental factors (e.g., climate and equipment) (Wallace et al., 2009;Halson, 2014;Soligard et al., 2016;Bourdon et al., 2017;Burgess, 2017;Vanrenterghem et al., 2017;McLaren et al., 2018;Impellizzeri et al., 2019). In the context of exercise prescription, the external load should be carefully adjusted to obtain an interindividually comparable internal load which is important to achieve a certain "dose" Herold et al., 2019Herold et al., , 2020bGronwald et al., 2020b). ...
The different responses of humans to an apparently equivalent stimulus are called interindividual response variability. This phenomenon has gained more and more attention in research in recent years. The research field of exercise-cognition has also taken up this topic, as shown by a growing number of studies published in the past decade.
In this perspective article, we aim to prompt the progress of this research field by (i) discussing the causes and consequences of interindividual variability, (ii) critically examining published studies that have investigated interindividual variability of neurocognitive outcome parameters in response to acute physical exercise, and (iii) providing recommendations for future studies, based on our critical examination.
The provided recommendations, which advocate for a more rigorous study design, are intended to help researchers in the field to design studies allowing them to draw robust conclusions. This, in turn, is very likely to foster the development of this research field and the practical application of the findings.
... The external load is monitored as objective comparable measures of the exercise done [ 5 ], such as overall distances, training and match participation, accelerations and decelerations, impacts and metabolic power [ 6 ]. However, external load measures of the exercise done do not consider the internal processes of training assimilation [ 7 ]. The internal load is the individual and relative physiological and psychological stress felt by soccer players as a result of the training and competitive sessions and the rest of demands present in their daily lives [ 5,8 ]. ...
BACKGROUND
Heavy physical and mental loads are typical for professional soccer players during the competitive season. COVID-19 lockdowns had recently forced competitions to be interrupted and later disputed in a shrunken calendar. Wearable sensors and mobile phones could be potentially useful in monitoring players’ training load in such highly demanding environments.
OBJECTIVE
The aim of this study was to explore whether remote heart rate variability (HRV) monitoring and self-reported wellness of professional soccer players could be useful to monitor players’ internal training load and to estimate their performance during the continuation of the 2020 season after the COVID-19 lockdown in Spain.
METHODS
A total of 21 professional soccer players participated in a 6-week study. Participants used an Android or iOS-based smartphone and a Polar H10 wearable ECG monitor for the duration of the study. Every morning they recorded their HRV and answered a questionnaire about their perceived recovery, muscle soreness, stress and sleep satisfaction. Smallest worthwhile change (SWC) and coefficient of variation (CV) were calculated for the logarithm of the root mean square of the successives differences (LnRMSSD) of the HRV. Players’ in-game performance was evaluated subjectively by independent observers and classified as high, normal and low. In order to find which variables could be potentially linked to performance, we studied their correlation and tested for significant differences among distributions. We also trained random forest models with cross-validation and bootstrapping to find the wellness and HRV features with best predictive ability for performance.
RESULTS
We found the usability of Readiness Soccer in a real scenario to be very good, with 81.36 points in the System Usability Scale. A total of 241 measurements of HRV and self-reported wellness were recorded. For a entire training microcycle (ie, time in between matches), self-reported high recovery (Mann-Whitney U, P=.003), low muscle soreness (P=.002), high sleep satisfaction (P=.02), low stress (Anderson-Darling, P=.03), and not needing more than 30 minutes to sleep since going to bed (Chi-Squared, P=.02), were found significant to differentiate high from normal match performance. Performance estimation models achieved the highest accuracy (73.4%) when combining self-reported wellness and HRV features.
CONCLUSIONS
HRV and self-reported wellness data were useful to monitor the evolution of professional soccer players’ internal load and to predict match performance levels out of measures in a training microcycle. Despite the limitations, these findings highlight opportunities for long-term monitoring of soccer players during the competitive season as well as real-time interventions aimed at early management of overtraining and boosting individual performance.
In der Trainingswissenschaft werden seit Längerem die spezifischen physiologischen Reaktionen auf unterschiedliche Trainingsbelastungen untersucht. Hierbei wird der induzierte Belastungsreiz mit der individuellen Beanspruchung in Relation gesetzt, um abschätzen zu können, welche extern induzierte Reizart („Dosis“) zu welcher individuellen psycho-physiologischen Beanspruchung und final zu spezifischen Adaptation (Wirkung) führt. Letztlich ist es das Ziel, die individuelle Dosis-Wirkungsbeziehung zu identifizieren. In den vergangenen Jahrzehnten wurde hierfür eine Vielzahl von Belastungs- und Beanspruchungsmarkern entwickelt sowie evaluiert, durch den der Reiz-Wirkungszusammenhang gemessen und quantifiziert werden kann. Dieser Beitrag ist Teil der Sektion Sportmotorische Fähigkeiten und sportliches Training, herausgegeben vom Teilherausgeber Michael Fröhlich, innerhalb des Handbuchs Sport und Sportwissenschaft, herausgegeben von Arne Güllich und Michael Krüger.
Evans, SL, Whittaker, G, Elphinstone Davis, E, Jones, ES, Hardy, J, and Owen, JA. Noncontact injury distribution and relationship with preseason training load and non-modifiable risk factors in Rugby Union players across multiple seasons. J Strength Cond Res XX(X): 000-000, 2022-This study examined the distribution of noncontact injury during phases of the competitive season and the association between preseason training load (TL) and nonmodifiable risk factors on injury risk during these phases. Injury data were recorded from 1 senior academy team over 3 seasons (2017-2020) and analyzed across early-season, midseason, and late-season phases. A generalized estimating equation was used to model risk factors with noncontact injury for selected phases. The highest noncontact injury incidence occurred in the late-season phase (22.2 per 1,000 hours) compared with early (13.7 per 1,000 hours, p < 0.001) and midseason phases (15.5 per 1,000 hours, p = 0.001). Low preseason TL (8,949-12,589 arbitrary units; odds ratio [OR], 95% confidence interval [CI] = 4.7, 1.0-21.6; p = 0.04) and low preseason TL combined with high early-season TL and injury in the early-season phase (OR, 95% CI = 6.5, 1.1-35.5; p = 0.03) were associated with greater midseason noncontact injury risk. In addition, low preseason TL combined with previous injury was associated with increased risk of noncontact injury risk in the late season (OR, 95% CI = 12.2, 0.9-15.6, p = 0.05). Our results suggest players are at a greater injury risk during the late-season phase, with low preseason cumulative loads combined with a history of previous injury associated with increased in-season injury risk. Strength and conditioning coaches should therefore monitor cumulative preseason TL alongside screening for previous injury history to identify athletes at greater risk of noncontact injury risk during the competitive season.
Kasb-hunar ta'limi №2, 2022 КАСБИЙ ТАЪЛИМ А.М.МУХАМЕТОВ Тошкент молия институти "Жисмоний маданият ва спорт фаолияти" ка-федраси в.в.б. доцент Личностно-ориентированный подход к процессу повышения квалификации пе-дагогических работников осуществлялся с учетом индивидуализации, в которой были выделены следующие структурные компо-ненты: • цели: повышение уровня компетент-ности каждого педагога: • установление исходного состояния компетентности педагога; • определение программы воздействий, предусматривающей основные направле-ния коррекции и развития деятельности и личности педагога (составление индивиду-альной траектории развития); • обеспечение получения информации о промежуточном состоянии деятельности и личности педагога (обеспечение система-тической обратной связи); • обеспечение переработки информа-ции, полученной по каналу обратной связи, выработки корректирующих (регулирую-Аннотация.Таълим муассасалари амалиётида жисмоний тарбия ва оммавий спорт билан талабаларнинг мустақил шуғулланишига аксари ҳолатларда етарлича эътибор берилмайди, уларнинг қизиқишларига мос тўгараклар йўқ, барча учун бир хил дастур асосида машғулотлар олиб борилади. Шунинг учун бу машғулотларда юкламаларни белгилаш ва уларни шуғулла-нувчилар организмига мувофиқлаштиришга эътибор йўқ. Бунда талабаларнинг қизиқиши эъ-тиборга олинмайди, талабаларнинг ташаббуслари қўллаб-қувватланмайди. Булар эса ўз на-вбатида талабаларниг жисмоний тарбия ва оммавий спортга қизиқишларини камайтиради. Бунинг натижасида талабалар фаолиятида камҳаракатлилик вужудга келади ва камҳаракат-лилик натижасида улар организмида турли хил касалликлар ривожланади, иммунитет пасай-ади, талабалар жисмоний юкламалар тўғрисида маълумотларга эга бўлмайди. Ушбу мақолада жисмоний тарбия ва оммавий спорт-соғломлаштириш машғулотларида юкламаларни меъёрлаштиришнинг аҳамияти ҳақида сўз боради. Калит сўзлар: жисмоний маданадият, спорт, жисмоний тарбия, жисмоний ривожланиш, жисмоний тайёргарлик, жисмоний юлама, талабағёшлар, меёрлаш, спорт машғулотлари, машқлар. ЖИСМОНИЙ ТАРБИЯ ВА ОММАВИЙ СПОРТ-СОҒЛОМЛАШТИ-РИШ МАШҒУЛОТЛАРИДА ЮКЛАМАЛАРНИ МЕЪЁРЛАШТИ-РИШНИНГ ИЛМИЙ-МЕТОДИК АСОСЛАРИ щих) мероприятий и способов их реализа-ции. Эти компоненты мы использовали при проектировании личностно-ориентирован-ной модели повышения квалификации пе-дагогических работников профессиональ-ного лицея. Проанализировав основные направления реализации компетентност-ного подхода, участвуя в научно-прак-тических конференциях и семинарах на разработке стандартов на модульно-компе-тентностной основе, мы определили, что в условиях разработки стандартов можно провести самостоятельный анализ неко-торых специальностей и, не претендуя на полноту исследований, выделить наиболее значимые профессиональные компетенции у учащихся и организовать методическую работу по освоению педагогических техно-логий, обеспечивающих их формирование. Таким образом, в рамках личностно-о-риентированной методической работы, на
O exercício físico traz inúmeros benefícios aos praticantes, sendo fundamental o controle de algumas variáveis, como a intensidade e o volume das sessões de treinamento. A natação tem como variáveis de controle de intensidade, principalmente a Frequência Cardíaca (FC), a Velocidade Crítica (VC) e a Percepção de Esforço (PE), sendo que poucos estudos investigaram a utilização da PE em nadadores amadores. O objetivo deste estudo foi analisar a relação entre a PE com a FC e com a Velocidade de Nado (VN) em nadadores amadores. Foram selecionados 20 sujeitos de ambos os sexos, com faixa etária entre 18 e 59 anos, nadadores não-atletas. Nas sessões experimentais, os sujeitos nadaram o estilo Crawl em 4 distâncias de 100 metros, nas intensidades dos índices de 11,13,15 e 17 da Escala de Percepção de Esforço de Borg, além da aferição da FC e do tempo de duração após a chegada. As correlações foram estabelecidas por meio do teste de Correlação de Pearson (p≤0,05), entre as PE e a FC absoluta e relativa, e pela VN absoluta e relativa (%VC). Os resultados encontrados apresentaram uma correlação moderada e significativa (p<0,05) entre PE com a FC (r= 0,712), com %FC máxima (0,758), com a VN (0,615) e com o %VC (0,659), indicando um aumento linear destas variáveis conforme o aumento da PE. Concluímos que a PE apresenta boas correlações com FC e VC e pode ser uma ferramenta útil, de baixo custo e acessível para prescrever a intensidade de treinamento em atletas amadores de natação.
These days, the visual analysis of the literature (using the Web of Science as the data source) in the field of international swimming has been used to clarify the current status and patterns of research in this field. The data source of web of science provides a reference for the dynamic update of international swimming research. In this paper, we have used CiteSpace software and applied it to analyze the core literature related to international swimming from 1998 to 2020 in terms of overall literature measurement, core authors, source institutions, country distribution, discipline distribution, research hotspots, frontiers, and so on. We performed numerous experimental works for dynamic analysis of international swimming research using this tool. The findings indicate that international swimming research is in the second (growth) stage of the “Lepus curve,” and that there is a “head effect” in the distribution of journals (primarily in sports medicine). We obtained these large core cooperative networks, forming some high-production institutions as the core of large-scale cooperative networks and comprehensive university high-production institutions. In the future, we plan to focus on sports injury and rehabilitation, physiological characteristics, biomechanical analysis, and reaction in the future.
In the practice of educational institutions, the independent involvement of students in physical education and mass sports is not given enough attention in the case of the opposite, there are no circles of interest to them, classes are conducted for all on the basis of the same program. Therefore, in these exercises, there is no emphasis on setting loads and coordinating them with the body of the engaged person.Bunda student interest is not taken into account, student initiatives are not supported. These in turn reduce the interest of students in physical education and mass sports. As a result of this, low activity occurs in student activities, and as a result of low activity, various diseases develop in their body, immunityitet decreases, students will not have access to information about physical loads. The modern way of life requires a radical renewal and development of reform education and personnel training in socioeconomic , political, spiritual and cultural spheres. Therefore, by developing the education system at the level of modern requirements and on the basis of the experience gained, educating the growing younger generation as mature and high-spiritually competent people who actively participate in the life of society is one of the priority directions of our state. Taking into account the modern demand, school programs in all disciplines have changed, including physical education, high-level requirements have been put before the students. In order to meet the requirements of this program, students are engaged in educational work at school and at home in order to gain knowledge. Of course, in order to perform such a great mental loading work, it is necessary to be energetic and jismonan healthy. It's no secret that a healthy child will perform all tasks at a high level of quality, he will have free will, aspiration, curiosity. One of the priceless drugs is physical exercises. To this end, Abu Ali Ibn Sina was the first to scientifically substantiate that" to a person who is regularly engaged in Physical Education, there is no need for medication." Axoli's "health" is a phrase from many factors. In the period of economic policy of the Republic of Uzbekistan, the structure of the physical education system should be based primarily on taking into account the climatic conditions and ethnic conditions of the Republic. On the second hand, the main factor of "Health"is physical preparation. Practice in this matter has a great experience. They are aimed at improving the results of performing various exercises, forming movement skills and skills, increasing movement activity, raising the quality of teaching movement techniques and training the qualities of physical activity.
El objetivo de este estudio ha sido analizar si la modificación de las tareas de entrenamiento, en concreto la orientación del espacio, tiene consecuencias en los diferentes parámetros que identifican la carga de trabajo en el fútbol femenino. En el estudio participaron 18 jugadoras de fútbol femenino (M = 21.89; DT = 6.20), que realizaron dos sesiones con cuatro tareas cada una. Las tareas estaban contrabalanceadas para cada sesión para evitar el efecto del orden de las mismas. Se utilizaron GPS Polar Team Pro para medir la carga física y cuestionarios para la carga mental. Para comparar los resultados de cada sesión se llevó a cabo una prueba T de medidas relacionadas. Los resultados muestran que la carga física fue mayor en las tareas donde no hubo orientación, al igual que la carga mental. Por tanto, el espacio en el que se desarrollan las tareas de entrenamiento resulta determinante en la carga mental percibida en fútbol femenino.
This study aims to provide a transferable methodology in the context of sport performance modelling, with a special focus to the generalisation of models. Data were collected from seven elite Short track speed skaters over a three months training period. In order to account for training load accumulation over sessions, cumulative responses to training were modelled by impulse, serial and bi-exponential responses functions. The variable dose-response (DR) model was compared to elastic net (ENET), principal component regression (PCR) and random forest (RF) models, while using cross-validation within a time-series framework. ENET, PCR and RF models were fitted either individually (M_I) or on the whole group of athletes (M_G). Root mean square error criterion was used to assess performances of models. ENET and PCR models provided a significant greater generalisation ability than the DR model ( p = 0.018, p < 0.001, p = 0.004 and p < 0.001 for ENET_I , ENET_G, PCR_I and PCR_G, respectively). Only ENET_G and RF_G were significantly more accurate in prediction than DR (p < 0.001 and p < 0.012). In conclusion, ENET achieved greater generalisation and predictive accuracy performances. Thus, building and evaluating models within a generalisation enhancing procedure is a prerequisite for any predictive modelling.
Importance
Therapeutic aquatic exercise is frequently offered to patients with chronic low back pain, but its long-term benefits are unclear.
Objective
To assess the long-term effects of therapeutic aquatic exercise on people with chronic low back pain.
Design, Setting, and Participants
This 3-month, single-blind randomized clinical trial with a 12-month follow-up period was performed from September 10, 2018, to March 12, 2019, and the trial follow-up was completed March 17, 2020. A total of 113 people with chronic low back pain were included in the experiment.
Interventions
Participants were randomized to either the therapeutic aquatic exercise or the physical therapy modalities group. The therapeutic aquatic exercise group received aquatic exercise, whereas the physical therapy modalities group received transcutaneous electrical nerve stimulation and infrared ray thermal therapy. Both interventions were performed for 60 minutes twice a week for 3 months.
Main Outcomes and Measures
The primary outcome was disability level, which was measured using the Roland-Morris Disability Questionnaire; scores range from 0 to 24, with higher scores indicating more severe disability. Secondary outcomes included pain intensity, quality of life, sleep quality, recommendation of intervention, and minimal clinically important difference. Intention-to-treat and per-protocol analyses were performed.
Results
Of the 113 participants, 59 were women (52.2%) (mean [SD] age, 31.0 [11.5] years). Participants were randomly allocated into the therapeutic aquatic exercise group (n = 56) or the physical therapy modalities group (n = 57), and 98 patients (86.7%) completed the 12-month follow-up. Compared with the physical therapy modalities group, the therapeutic aquatic exercise group showed greater alleviation of disability, with adjusted mean group differences of −1.77 (95% CI, −3.02 to −0.51; P = .006) after the 3-month intervention, −2.42 (95% CI, −4.13 to −0.70; P = .006) at the 6-month follow-up, and −3.61 (95% CI, −5.63 to −1.58; P = .001) at the 12-month follow-up (P < .001 for overall group × time interaction). At the 12-month follow-up point, improvements were significantly greater in the therapeutic aquatic exercise group vs the physical therapy modalities group in the number of participants who met the minimal clinically important difference in pain (at least a 2-point improvement on the numeric rating scale) (most severe pain, 30 [53.57%] vs 12 [21.05%]; average pain, 14 [25%] vs 11 [19.30%]; and current pain, 22 [39.29%] vs 10 [17.54%]) and disability (at least a 5-point improvement on the Roland-Morris Disability Questionnaire) (26 [46.43%] vs 4 [7.02%]). One of the 56 participants (1.8%) in the therapeutic aquatic exercise group vs 2 of the 57 participants (3.5%) in the physical therapy modalities group experienced low back pain and other pains related to the intervention.
Conclusions and Relevance
The therapeutic aquatic exercise program led to greater alleviation in patients with chronic low back pain than physical therapy modalities and had a long-term effect up to 12 months. This finding may prompt clinicians to recommend therapeutic aquatic exercise to patients with chronic low back pain as part of treatment to improve their health through active exercise rather than relying on passive relaxation.
Trial Registration
Chinese Clinical Trial Registry: ChiCTR1800016396
Advancements in wearable technologies such as Global Positioning System (GPS) and accelerometers allow coaches and practitioners to gain a better understanding of the physiological and biomechanical demands of a sport. This study documents and describes the movement demands of Canadian university football during training and competition over
the course of two seasons. GPS data from sixteen players were collected daily during 29 training sessions and 8 games in 2016 and 31 training sessions and 9 games in 2017, respectively. Data revealed that players covered on average 3006 +/- 1536 and 3860 +/- 1189 meters of total distance during training sessions in 2016 and 2017, respectively. Of this distance, high-speed running (165 +/- 141; 287 +/- 181 m), high metabolic load distance (370 +/- 243; 548 +/- 247 m), sprints(10 +/- 9; 17 +/- 10); acceleration (216 +/- 113; 200 +/- 67) and deceleration efforts (191+/- 99; 180 +/- 64) were also obtained. Movements demands were higher during games, revealing that players covered on average 5954 +/-1053 and 6155 +/- 509 meters of total distance in 2016 and 2017, respectively. High-speed running (445 +/- 128; 541 +/- 74 m), high metabolic load distance (784 +/- 184; 900 +/-103 m), sprints (23 +/- 5; 26 +/- 3); acceleration (277 +/- 49; 316 +/- 35) and deceleration efforts (263 +/- 49; 295 +/- 35) were also higher in games than in training sessions. This study provides novel insight into the movement demands of Canadian university football, which should be supported by the regular assessment and training of lower-body muscular strength, sprinting speed and repeated-sprint ability.
McFadden, BA, Walker, AJ, Bozzini, BN, Hofacker, M, Russell, M, and Arent, SM. Psychological and physiological changes in response to the cumulative demands of a women's division I collegiate soccer season. J Strength Cond Res XX(X): 000-000, 2021-This study sought to determine the effects of a women's collegiate soccer season on psychological markers, biomarkers, sleep, and performance. Athletes participated in maximal countermovement vertical jump height (CMJ) assessments and biomarker monitoring in conjunction with subjective measures of psychological wellness and sleep questionnaires before preseason (S1) and every 4 weeks following (S2, S3, and S4). Training was monitored during practices and games using global positioning satellite systems and heart rate technology. Total training load was highest from S1 to S2, decreased from S2 to S3 (effect size [ES] = -2.5; p < 0.001), and remained stable from S3 to S4. CMJ declined at S2 (ES1-2 = -0.51; p = 0.001) and returned to baseline at S3. Increases from S1 to S2 were seen for creatine kinase (ES1-2 = 1.74), free testosterone (ES1-2 = 1.27), total testosterone (ES1-2 = 3.5), and free cortisol (ES1-2 = 0.88) (p < 0.03) before returning to baseline by S3 and S4 (free cortisol). Total cortisol was elevated throughout the season before declining at S4 (ES1-4 = -0.41; p = 0.03). Iron declined from S1 to S2 (ES1-2 = -0.73; p = 0.01) and returned to baseline values at S4, whereas growth hormone declined at S2 (ES1-2 = -0.50; p = 0.01) and remained depressed. Interleukin-6 increased at S4 (ES1-4 = 0.71; p = 0.02). Total training distress decreased from S1 to S2 (ES1-2 = -0.38; p = 0.02), returned to baseline by S3, and increased by S4 (ES1-4 = 0.57; p = 0.01). No changes were observed in markers of sleep (p > 0.05). Biomarkers showed notable changes after the highest workload period (S1-S2), which coincided with CMJ decrements. Biomarker perturbations preceded declines in subjective psychological wellness (S4) which occurred in the latter half of the season, indicating an accumulation of fatigue as the season progressed.
This paper focuses on the characteristics of a model interpreting the effect of training on athletic performance. The model theory is presented both mathematically and graphically. In the model, a systematically quantified impulse of training produces dual responses: fitness and fatigue. In the absence of training, both decay exponentially with time. With repetitive training, these responses satisfy individual recurrence equations. Fitness and fatigue are combined in a simple linear difference equation to predict performance levels appropriate to the intensity of training being undertaken. Significant observed correlation of model-predicted performance with a measure of actual performance during both training and tapering provides validation of the model for athletes and nonathletes alike. This enables specific model parameters to be estimated and can be used to optimize future training regimens for any individual.
The cross-training (XT) hypothesis suggests that despite the principle of specificity of training, athletes may improve performance in one mode of exercise by training using another mode. To test this hypothesis we studied 30 well-trained individuals (10 men, 20 women) in a randomized longitudinal trail. Subjects were evaluated before and after 8 weeks of enhanced training (+10%/week), accomplished by adding either running (R) or swimming (XT) to baseline running, versus continued baseline running (C). Both R (-26.4s) and XT (-13.2s) improved time trial (3.2 km) performance, whereas C did not (-5.4s). There were no significant changes during treadmill running in maximum oxygen uptake (VO2peak; -0.2, -6.0, and +2.7%), steady state submaximal VO2 at 2.68 m.s-1 (-1.2, -3.3 and +0.2 ml.kg-1.min-1), velocity at VO2peak (+0.05, +0.25 and +0.09 m.s-1) or accumulated O2 deficit (+11.2, -6.1 and +9.4%) in the R, XT or C groups, respectively. There was a significant increase in velocity associated with a blood lactate concentration of 4 mmol.l-1 in R but not in XT or C (+0.32, +0.07 and +0.08 m.s-1). There were significant changes in arm crank VO2peak (+5%) and arm crank VO2 at 4 mmol.l-1 (+6.4%) in XT. There was no significant changes in arm crank VO2peak (+1.3 and -7.7%) or arm crank VO2 at 4 mmol.l-1 (+0.8 and +0.4%) in R or C, respectively. The data suggest that muscularly non-similar XT may contribute to improved running performance but not to the same degree as increased specific training.
Athletic performance generally is thought to improve with increases in training load. However, few data exist showing the quantitative relationship between training load and performance. We followed 56 athletes (16 runners; 40 cyclists/speed skaters) during 12 weeks of training. We recorded index performances (3.2 km time trial or 5 or 10 km bicycle ergometry) after 6 weeks of baseline training and 6 weeks of a self-selected training increases. Training load was quantitated as the product of intensity (global rating of perceived exertion (RPE)) and the duration (time) of each training session. Load was expressed as the weekly average over the 6 weeks preceding each index performance. We also recorded the duration of high intensity training (RPE>5, hard) (inten). From 6 to 12 weeks, performance improved 12.95 +/- 3.83 to 12.66 +/- 3.00 min (p < .01). Training time (345 +/- 282 to 355 +/- 273 min/wk) and inten (61 +/- 88 to 71 +/- 91 min/wk) did not change significantly, although RPE (3.8 +/- 0.7 to 4.0 +/- 0.8) and load (1242 +/- 957 to 1386 +/- 978) increased significantly. No strong correlations existed between changes in performance and changes in any training measure (TIME, r = -0.031, RPE, r = -0.039, LOAD, r = 0.29, INTEN, r = 0.025.) Data suggest that improved performance in events of 7-20 minutes duration in response to intensified training is primarily dependent upon increases in total load and overall RPE during training and; that a 10-fold increase in training load may be associated with an approximately 10% improvement in performance. These data suggest the possibility of understanding the training responses of athletes on a quantitative basis.
The ability to monitor training is critical to the process of quantitating training periodization plans. To date, no method has proven successful in monitoring training during multiple types of exercise. High-intensity exercise training is particularly difficult to quantitate. In this study we evaluate the ability of the session rating of perceived exertion (RPE) method to quantitate training during non-steady state and prolonged exercise compared with an objective standard based on heart rate (HR). In a 2-part design, subjects performed steady state and interval cycle exercise or practiced basketball. Exercise bouts were quantitated using both the session RPE method and an objective HR method. During cycle exercise, the relationship between the exercise score derived using the session RPE method and the HR method was highly consistent, although the absolute score was significantly greater with the session RPE method. During basketball, there was a consistent relationship between the 2 methods of monitoring exercise, although the absolute score was also significantly greater with the session RPE method. Despite using different subjects in the 2 parts of the study, the regression relationships between the session RPE method and the HR method were nearly overlapping, suggesting the broad applicability of this method. We conclude that the session RPE method is a valid method of quantitating exercise training during a wide variety of types of exercise. As such, this technique may hold promise as a mode and intensity-independent method of quantitating exercise training and may provide a tool to allow the quantitative evaluation of training periodization plans.
To compare the total exercise loads (intensity x volume) of the Vuelta a España and Tour de France during the last year.
Seven professional road cyclists (28 +/- 1 yr; [OV0312]O(2max): 74.6 +/- 2.2 mL.kg-1.min-1) who participated in both Tour and Vuelta during the years 1997, 1999, 2000, or 2001 were collected as subjects. They wore a heart rate (HR) telemeter during each stage of the two races, and exercise intensity was divided into three phases according to the reference HR values obtained during a previous ramp cycle-ergometer test: phase I (<ventilatory threshold (VT)), phase II (between VT and the respiratory compensation point (RCP)) and phase III (>RCP). Total volume and intensity were integrated as a single variable. The score for volume x intensity in each phase was computed by multiplying the accumulated duration in this phase by a multiplier for this particular phase. The total score for Tour and Vuelta was obtained by summating the results of the three phases.
The total loads (volume x intensity) did not significantly differ between the two races (P > 0.05), despite a significantly longer total exercise time of the Tour (P < 0.05) (5552 +/- 176 vs 5086 +/- 290 min).
The physiological loads imposed on cyclists' bodies do not differ between the Tour and Vuelta, despite the longer duration of daily stages in the former race.
Over the last 20 years, heart rate monitors (HRMs) have become a widely used training aid for a variety of sports. The development of new HRMs has also evolved rapidly during the last two decades. In addition to heart rate (HR) responses to exercise, research has recently focused more on heart rate variability (HRV). Increased HRV has been associated with lower mortality rate and is affected by both age and sex. During graded exercise, the majority of studies show that HRV decreases progressively up to moderate intensities, after which it stabilises. There is abundant evidence from cross-sectional studies that trained individuals have higher HRV than untrained individuals. The results from longitudinal studies are equivocal, with some showing increased HRV after training but an equal number of studies showing no differences. The duration of the training programmes might be one of the factors responsible for the versatility of the results.HRMs are mainly used to determine the exercise intensity of a training session or race. Compared with other indications of exercise intensity, HR is easy to monitor, is relatively cheap and can be used in most situations. In addition, HR and HRV could potentially play a role in the prevention and detection of overtraining. The effects of overreaching on submaximal HR are controversial, with some studies showing decreased rates and others no difference. Maximal HR appears to be decreased in almost all 'overreaching' studies. So far, only few studies have investigated HRV changes after a period of intensified training and no firm conclusions can be drawn from these results. The relationship between HR and oxygen uptake (VO(2)) has been used to predict maximal oxygen uptake (VO(2max)). This method relies upon several assumptions and it has been shown that the results can deviate up to 20% from the true value. The HR-VO(2) relationship is also used to estimate energy expenditure during field conditions. There appears to be general consensus that this method provides a satisfactory estimate of energy expenditure on a group level, but is not very accurate for individual estimations. The relationship between HR and other parameters used to predict and monitor an individual's training status can be influenced by numerous factors. There appears to be a small day-to-day variability in HR and a steady increase during exercise has been observed in most studies. Furthermore, factors such as dehydration and ambient temperature can have a profound effect on the HR-VO(2) relationship.
The anaerobic threshold (AnT) is defined as the highest sustained intensity of exercise for which measurement of oxygen uptake can account for the entire energy requirement. At the AnT, the rate at which lactate appears in the blood will be equal to the rate of its disappearance. Although inadequate oxygen delivery may facilitate lactic acid production, there is no evidence that lactic acid production above the AnT results from inadequate oxygen delivery. There are many reasons for trying to quantify this intensity of exercise, including assessment of cardiovascular or pulmonary health, evaluation of training programs, and categorization of the intensity of exercise as mild, moderate, or intense. Several tests have been developed to determine the intensity of exercise associated with AnT: maximal lactate steady state, lactate minimum test, lactate threshold, OBLA, individual anaerobic threshold, and ventilatory threshold. Each approach permits an estimate of the intensity of exercise associated with AnT, but also has consistent and predictable error depending on protocol and the criteria used to identify the appropriate intensity of exercise. These tests are valuable, but when used to predict AnT, the term that describes the approach taken should be used to refer to the intensity that has been identified, rather than to refer to this intensity as the AnT.
The ability to accurately control and monitor internal training load is an important aspect of effective coaching. The aim of this study was to apply in soccer the RPE-based method proposed by Foster et al. to quantify internal training load (session-RPE) and to assess its correlations with various methods used to determine internal training load based on the HR response to exercise.
Nineteen young soccer players (mean +/- SD: age 17.6 +/- 0.7 yr, weight 70.2 +/- 4.7 kg, height 178.5 +/- 4.8 cm, body fat 7.5 +/- 2.2%, VO2max, 57.1 +/- 4.0 mL x kg x min) were involved in the study. All subjects performed an incremental treadmill test before and after the training period during which lactate threshold (1.5 mmol x L above baseline) and OBLA (4.0 mmol x L) were determined. The training loads completed during the seven training weeks were determined multiplying the session RPE (CR10-scale) by session duration in minutes. These session-RPE values were correlated with training load measures obtained from three different HR-based methods suggested by Edwards, Banister, and Lucia, respectively.
Individual internal loads of 479 training sessions were collected. All individual correlations between various HR-based training load and session-RPE were statistically significant (from r = 0.50 to r = 0.85, P < 0.01).
The results of this study show that the session-RPE can be considered a good indicator of global internal load of soccer training. This method does not require particular expensive equipment and can be very useful and practical for coaches and athletic trainer to monitor and control internal load, and to design periodization strategies.
Over the last 20 years, heart rate monitors (HRMs) have become a widely used training aid for a variety of sports. The development of new HRMs has also evolved rapidly during the last two decades. In addition to heart rate (HR) responses to exercise, research has recently focused more on heart rate variability (HRV). Increased HRV has been associated with lower mortality rate and is affected by both age and sex. During graded exercise, the majority of studies show that HRV decreases progressively up to moderate intensities, after which it stabilises. There is abundant evidence from cross-sectional studies that trained individuals have higher HRV than untrained individuals. The results from longitudinal studies are equivocal, with some showing increased HRV after training but an equal number of studies showing no differences. The duration of the training programmes might be one of the factors responsible for the versatility of the results. HRMs are mainly used to determine the exercise intensity of a training session or race. Compared with other indications of exercise intensity, HR is easy to monitor, is relatively cheap and can be used in most situations. In addition, HR and HRV could potentially play a role in the prevention and detection of overtraining. The effects of overreaching on submaximal HR are controversial, with some studies showing decreased rates and others no difference. Maximal HR appears to be decreased in almost all ‘overreaching’ studies. So far, only few studies have investigated HRV changes after a period of intensified training and no firm conclusions can be drawn from these results. The relationship between HR and oxygen uptake (V̇O2) has been used to predict maximal oxygen uptake (V̇O2max). This method relies upon several assumptions and it has been shown that the results can deviate up to 20% from the true value. The HR-V̇O2 relationship is also used to estimate energy expenditure during field conditions. There appears to be general consensus that this method provides a satisfactory estimate of energy expenditure on a group level, but is not very accurate for individual estimations. The relationship between HR and other parameters used to predict and monitor an individual’s training status can be influenced by numerous factors. There appears to be a small day-to-day variability in HR and a steady increase during exercise has been observed in most studies. Furthermore, factors such as dehydration and ambient temperature can have a profound effect on the HR-V̇O2 relationship.
1. The pattern of elevation of several serum biochemical indices (BL) of training stress (creatine kinase, CK; lactate dehydrogenase, LDH; aspartate aminotransferase, AST, Ca2+; urate, Ur; urea, U; total protein, Prot; cholesterol, C) were measured serially through two extended periods of training, including taper (50 days each) separated by a period of complete non-training (90 days) in two male subjects. 2. The patterns of variation in BI were compared with similar variation in elements of a two compartment model predicting performance from training. 3. These elements arbitrarily described as Fitness [g(t)] and Fatigue [h(t)] were estimated daily from a daily training impulse [w(t)] defined from the duration time and heart rate elevation of an individual in a training session. 4. g(t) and h(t) were used to predict performance [p(t)] which might be expected from the training undertaken. So that: p(t)=k(1)g(t)-k(2)h(t) where k(1) and k(2) are arbitrary constants. 5. performance p(t) when iteratively modelled against a Criterion running Performance, Cp(t) measured serially throughout training, over a standard distance, then defines the pattern of variation in the elements g(t) and h(t) (Morton er al., 1990). 6. Hard training for 28 days and a succeeding 22 days of taper in each training period produced a rise and fall in elevated serum enzyme activity, ESEA, (CK, LDH and AST) which mirrored the time-course pattern of h(t), the fatigue element of the dose/response model of training, with a slight phase delay. 7. Thus ESEA was already declining during hard training. 8. During the taper period ESEA declined rapidly to base line. This response was remarkably symmetrical in each, separate training period. 9. The Criterion running performance (CP) declined during hard training and rebounded throughout the taper period reaching an asymptote before beginning to decline again as training fitness [g(t)] was lost, although the fatigue [h(t)] state was now minimal. 10. Serum Prot, U, Ur respectively were also elevated throughout hard training, first following the hypothesized h(t) curve but showing a biphasic response, declining during the later phase of hard training, and rising again during taper. 11. The symmetry of response of these indices in each period was less evident than the ESEA response. None of the BI patterns measured was in phase with g(t), all, seemingly, reflected the catabolic rather than the anabolic process of hard training.
To compare some psychophysiological responses to arm exercise with those to leg exercise, an experiment was carried out on electronically braked bicycle ergometers, one being adapted for arm exercise. Eight healthy males took part in the experiment with stepwise increases in exercise intensity every 4 min: 40—70—100—150—200 W in cycling and 20—35—50—70—100 W in arm cranking. Towards the end of each 4 min period, ratings of perceived exertion were obtained on the RPE scale and on a new category ratio (CR) scale: heart rate (HR) and blood lactate accumulation (BL) were also measured.
The responses obtained were about twice as high or more for arm cranking than for cycling. The biggest difference was found for BL and the smallest for HR and RPE. The incremental functions were similar in both activities, with approximately linear increases in HR and RPE and positively accelerating functions for CR (exponents about 1.9) and BL (exponents 2.5 and 3.3 respectively). When perceived exertion (according to the CR scale) was set as the dependent variable and a simple combination of HR and BL was used as the independent variable, a linear relationship was obtained for both kinds of exercise, as has previously been found in cycling, running, and walking. The results thus give support for the following generalization: For exercise of a steady state type with increasing loads the incremental curve for perceived exertion can be predicted from a simple combination of HR and BL.
To evaluate markers for overtraining, seven male race horses were subjected to 272 days of training consisting of daily exercise bouts of either endurance running (heart rate 140/min) or interval training (maximal heart rate), both increasing in duration and intensity. An incremental exercise test was held every 4 wk, and from day 187 it was held every 2 wk. Muscle glycogen, muscle lactate, energy-rich phosphates, adrenal response to adrenocorticotropic hormone, plasma and red blood cell volumes, and a number of blood chemical variables were measured. The horses showed symptoms of weight loss, irritability, and an inability to complete the training after the intensity of the endurance exercise was increased. Test performance was not decreased. The adrenal response to adrenocorticotropic hormone was not changed during overtraining. The decline in muscle ATP concentration during maximal exercise was less during the period of staleness, whereas plasma volume, red blood cell volume, and blood chemical variables were unchanged. It was concluded that as long as exhaustive training is alternated by light exercise, overtraining is unlikely to occur. Furthermore, no single parameter can be used to detect early overtraining.
Overtraining is primarily related to sustained high load training, often coupled with other stressors. Studies in animal models have suggested that unremittingly heavy training (monotonous training) may increase the likelihood of developing overtraining syndrome. The purpose of this study was to extend our preliminary observations by relating the incidence of illnesses and minor injuries to various indices of training.
We report observations of the relationship of banal illnesses (a frequently cited marker of overtraining syndrome) to training load and training monotony in experienced athletes (N = 25). Athletes recorded their training using a method that integrates the exercise session RPE and the duration of the training session. Illnesses were noted and correlated with indices of training load (rolling 6 wk average), monotony (daily mean/standard deviation), and strain (load x monotony).
It was observed that a high percentage of illnesses could be accounted for when individual athletes exceeded individually identifiable training thresholds, mostly related to the strain of training.
These suggest that simple methods of monitoring the characteristics of training may allow the athlete to achieve the goals of training while minimizing undesired training outcomes.
The aim of this study was to devise a laboratory-based protocol for a motorized treadmill that was representative of work rates observed during soccer match-play. Selected physiological responses to this soccer-specific intermittent exercise protocol were then compared with steady-rate exercise performed at the same average speed. Seven male university soccer players (mean ± s: age 24 ± 2 years, height 1.78 ± 0.1 m, mass 72.2 ± 5.0 kg, V̇O(2max) 57.8 ± 4 ml/kg-1/min-1) completed a 45-min soccer-specific intermittent exercise protocol on a motorized treadmill. They also completed a continuous steady-rate exercise session for an identical period at the same average speed. The physiological responses to the laboratory-based soccer-specific protocol were similar to values previously observed for soccer match-play (oxygen consumption approximately 68% of maximum, heart rate 168 ± 10 beats/min-1). No significant differences were observed in oxygen consumption, heart rate, rectal temperature or sweat production rate between the two conditions. Average minute ventilation was greater (P < 0.05) in intermittent exercise (81.3 ± 0.2 l/min-1) than steady-rate exercise (72.4 ± 11.4 l/min-1). The rating of perceived exertion for the session as a whole was 15 ± 2 during soccer-specific intermittent exercise and 12 ± 1 for continuous exercise (P < 0.05). The physiological strain associated with the laboratory-based soccer-specific intermittent protocol was similar to that associated with 45 min of soccer match-play, based on the variables measured, indicating the relevance of the simulation as a model of match-play work rates. Soccer-specific intermittent exercise did not increase the demands placed on the aerobic energy systems compared to continuous exercise performed at the same average speed, although the results indicate that anaerobic energy provision is more important during intermittent than during continuous exercise at the same average speed.
To determine whether lactate profiling could detect changes in discrete aspects of endurance fitness in world-ranked swimmers during a season.
Eight male and four female Australian National Team swimmers aged 20--27 yr undertook a 7 x 200-m incremental swimming step test on four occasions over an 8-month period before the 1998 Commonwealth Games (CG): January (10 d before the World Championships), May (early-season camp), July (midseason), and August (16 d before the CG). The lactate threshold (LT) was determined by a mathematical formula that calculated the threshold as a function of the slope and y-intercept of the lactate-velocity curve.
Maximal 200-m test time declined initially from 127.7 +/- 4.2 s (January 1998) to 130.2 +/- 4.5 s (May 1998) and 129.1 +/- 4.3 s (July 1998) before improving to 126.8 +/- 4.2 s (August 1998) (P < 0.005). The swimming velocity at LT (s.100 m(-)1) also declined midseason before improving before the CG (P < 0.02) (January 1998: 70.5 +/- 2.1; May 1998: 72.0 +/- 2.2; July 1998: 72.2 +/- 2.2; and August 1998: 70.8 +/- 2.1). The blood lactate concentration at the LT decreased (P < 0.02) from 3.6 +/- 0.2 mM to 3.2 +/- 0.1 mM and 2.9 +/- 0.2 mM before returning to 3.4 +/- 0.2 mM for January, May, July, and August, respectively. The lactate tolerance rating (LT(5--10)), defined as the differential velocity between lactate concentrations of 5.0 and 10.0 mM, declined midway through the season (P < 0.015): 6.6 +/- 0.5 s.100 m(-1), 7.7 +/- 0.5 s.100 m(-1), 8.5 +/- 0.5 s.100 m(-1), and 6.9 +/- 0.4 s.100 m(-1), for January, May, July, and August, respectively. Despite these improvements in indicators of fitness, there was no significant improvement in competition performance across the season.
Maximal effort 200-m time, lactate tolerance rating, and swimming velocity at LT (s.100 m(-1)) all improved in world-ranked swimmers with training, but these changes were not directly associated with competition performance.
This study investigated the reliability of the session rating of perceived exertion (RPE) scale to quantify exercise intensity during high-intensity (H), moderate-intensity (M), and low-intensity (L) resistance training. Nine men (24.7 +/- 3.8 years) and 10 women (22.1 +/- 2.6 years) performed each intensity twice. Each protocol consisted of 5 exercises: back squat, bench press, overhead press, biceps curl, and triceps pushdown. The H consisted of 1 set of 4-5 repetitions at 90% of the subject's 1 repetition maximum (1RM). The M consisted of 1 set of 10 repetitions at 70% 1RM, and the L consisted of 1 set of 15 repetitions at 50% 1RM. RPE was measured following the completion of each set and 30 minutes postexercise (session RPE). Session RPE was higher for the H than M and L exercise bouts (p < or = 0.05). Performing fewer repetitions at a higher intensity was perceived to be more difficult than performing more repetitions at a lower intensity. The intraclass correlation coefficient for the session RPE was 0.88. The session RPE is a reliable method to quantify various intensities of resistance training.
Athletic performance in relation to training load A new approach to monitoring exercise training
- C Foster
- E Daines
- L Hector
- Ac Snyder
- R Foster
- C Florhaug
- Ja Franklin
- J Gottschall
- L Hrovatin
- La Parker
- S Doleshal
- P Dodge
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Physiological correlates of perceived exertion during soccerspecific exercise
- A J Coutts
- E Rampinini
- S Marcora
- C Castagna
- F M Impellizzeri
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Coutts, AJ, Reaburn, PRJ, Murphy, AJ, Pine, MJ, and Impellizzeri, FM. Validity of the session-RPE method for determining training load in team sport athletes.
Foster, C, Hector, LL, Welsh, R, Schrager, M, Green, MA, and Snyder, AC. Effects of specific versus cross-training on running performance.
Morton, RH, Fitz-Clarke, JR, and Banister, EW. Modeling human performance in running.
Impellizzeri, FM, Rampinini, E, Coutts, AJ, Sassi, A, and Marcora, SM. The use of RPE-based training load in soccer.
Lucia, A, Hoyos, J, Santalla, A, Earnest, C, and Chicharro, JL. Tour de France versus Vuelta a Espana: which is harder?