Training Impulse Research Articles

Morning versus Nocturnal Heart Rate and Heart Rate Variability Responses to Intensified Training in Recreational Runners

BackgroundResting heart rate (HR) and HR variability (HRV) are widely used parameters to assess cardiac autonomic nervous system function noninvasively. While resting assessments can be performed during sleep or after awakening, it would be relevant to know how interchangeable the results of these measurements are. This study aimed at examining the alignment between nocturnal and morning assessments during regular endurance training and in response to intensive training. A total of 24 recreational runners performed a 3-week baseline period (BL) and a 2-week overload (OL) period (Lucia’s training impulse + 80%). Their running performance was assessed with a 3000-m running test after the BL and OL. The participants recorded daily their nocturnal HR and HRV (the natural logarithm of the root mean square of successive differences; LnRMSSD) with a photoplethysmography-based wrist device and performed an orthostatic test (2-min supine, 2-min standing) every morning with a chest-strap HR sensor. The HR and LnRMSSD segments that were analyzed from the nocturnal recordings included start value (SleepStart), end value (SleepEnd), first 4-h segment 30 min after detected sleep onset (Sleep4h), and full sleep time (SleepFull). The morning segments consisted of the last-minute average in both body positions. All segments were compared at BL and in response to the 3000-m test and OL.ResultsAll nocturnal HR and LnRMSSD segments correlated with supine and standing segments at BL (r = 0.42 to 0.91, p < 0.05). After the 3000-m test, the HR increased and LnRMSSD decreased only in the SleepStart, Sleep4h, and SleepFull segments (p < 0.05). In response to the OL, the standing HR decreased (p < 0.01), while the LnRMSSD increased (p < 0.05) in all segments except for SleepStart. The Pearson correlations between relative changes in nocturnal and morning segments were − 0.11 to 0.72 (3000-m) and − 0.25 to 0.79 (OL). The OL response in Sleep4h HR and LnRMSSD correlated with the relative change in 3000-m time (r = 0.63, p = 0.001 and r=-0.50, p = 0.013, respectively).ConclusionsNocturnal and morning HR and LnRMSSD correlated moderately or highly in the majority of cases during the BL, but their responses to intensive training were not similarly aligned, especially in LnRMSSD. The nocturnal segments seemed to be sensitive to physical loading, and their responses were associated with the performance-related training responses.

Differences in Workloads of Maximal Tasks in Active-Duty Firefighters.

The purpose of this study was to compare the workload of a maximal treadmill test (TREAD) and a fire suppression task (BURN) in firefighters and to examine their relationships to fitness as measured by body mass index (BMI), percent body fat (BF%), and peak aerobic capacity (VO2PEAK). The amount of time spent in the heart rate (HR) intensity ranges of 50-59% HRMAX (ZONE1), 60-69% HRMAX (ZONE2), 70-79% HRMAX (ZONE3), 80-89% HRMAX (ZONE4), and ≥90% HRMAX (ZONE5) quantified the workload as the Edward's Training Impulse for TREAD (ETRIMPTREAD) and BURN (ETRIMPBURN). The ETRIMPTREAD was significantly less than ETRIMPBURN. For TREAD, ZONE5 > ZONE2 and ZONE3. For BURN, ZONE4 > ZONE1, ZONE2, and ZONE5 > ZONE1, ZONE2, and ZONE3. A lower BF% and greater VO2PEAK were related to a greater ETRIMPTREAD and unrelated to ETRIMPBURN. For BURN only, a lower BF% and greater VO2PEAK were related to less time in ZONE5. BMI was unrelated to all workload measures. Laboratory-based maximal exercise testing does not adequately reflect the workload of simulated fire suppression and therefore may not be indicative of firefighter readiness to meet job demands. Less-fit firefighters rely on higher cardiovascular intensities to complete the same workload, and practitioners should consider this when selecting strategies to reduce job-associated cardiovascular risk.

Workloads in Collegiate Women's Lacrosse Athletes During a Division II National Championship Season.

Sutton, PJ, Mumford, PW, and Sunderland, KL. Workloads in collegiate women's lacrosse athletes during a Division II national championship season. J Strength Cond Res 38(9): 1651-1657, 2024-A comprehensive examination of the external and internal workloads in collegiate women's lacrosse athletes has yet to be reported. Thus, the primary purpose of this study was to determine the absolute and relative external and internal training and game workloads of National Collegiate Athletic Association (NCAA) Division II women's lacrosse athletes throughout an entire season. Data from 19 Division II women's lacrosse athletes were analyzed, encompassing each training session and game across an entire competitive season (February-May). External workloads were assessed using a wearable global positioning system, whereas internal workloads were determined through heart rate (HR) variables and session rating of perceived exertion. Game days were associated with significantly ( p < 0.05) greater absolute external and internal workloads. However, when comparing workloads relative to session duration, relative workloads between training and games were no longer significant ( p > 0.05) for total distance, high-speed running (≥15 km·h -1 ), HR-derived training impulse, or caloric expenditure. Nonetheless, relative sprint distance (>19 km·h -1 ) was significantly lower during games, whereas high-intensity accelerations (>2 m·s -2 ) and decelerations (<-2 m·s -2 ) were significantly greater during training compared with games ( p < 0.05). Practical applications of these findings suggest that coaches can better prepare athletes for game day conditions by adjusting training plans to replicate the duration and intensity of games. Overall, this comprehensive examination of internal and external workloads provides valuable data for coaches and practitioners to support performance comparisons, rehabilitation protocols, and workload analyses in collegiate women's lacrosse athletes.

Analyzing Key Factors on Training Days within a Standard Microcycle for Young Sub-Elite Football Players: A Principal Component Approach.

Utilizing techniques for reducing multivariate data is essential for comprehensively understanding the variations and relationships within both biomechanical and physiological datasets in the context of youth football training. Therefore, the objective of this study was to identify the primary factors influencing training sessions within a standard microcycle among young sub-elite football players. A total of 60 male Portuguese youth sub-elite footballers (15.19 ± 1.75 years) were continuous monitored across six weeks during the 2019-2020 in-season, comprising the training days from match day minus (MD-) 3, MD-2, and MD-1. The weekly training load was collected by an 18 Hz global positioning system (GPS), 1 Hz heart rate (HR) monitors, the perceived exertion (RPE) and the total quality recovery (TQR). A principal component approach (PCA) coupled with a Monte Carlo parallel analysis was applied to the training datasets. The training datasets were condensed into three to five principal components, explaining between 37.0% and 83.5% of the explained variance (proportion and cumulative) according to the training day (p < 0.001). Notably, the eigenvalue for this study ranged from 1.20% to 5.21% within the overall training data. The PCA analysis of the standard microcycle in youth sub-elite football identified that, across MD-3, MD-2, and MD-1, the first was dominated by the covered distances and sprinting variables, while the second component focused on HR measures and training impulse (TRIMP). For the weekly microcycle, the first component continued to emphasize distance and intensity variables, with the ACC and DEC being particularly influential, whereas the second and subsequent components included HR measures and perceived exertion. On the three training days analyzed, the first component primarily consisted of variables related to the distance covered, running speed, high metabolic load, sprinting, dynamic stress load, accelerations, and decelerations. The high intensity demands have a high relative weight throughout the standard microcycle, which means that the training load needs to be carefully monitored and managed.

Monitoring the Breath-Hold Training Load during an Ecological Session: A Pilot Study.

This study aimed to create a training load index to measure physiological stress during breath-hold (BH) training and examine its relationship with memory performance. Eighteen well-trained BH divers (Age: 35.8±6.6 years, BH training practice: 5.3±4.5 years) participated in this study. During a standard 1.5-hour BH training in the pool, perceived exertion, heart rate, distance, and duration were measured. The training load index was modelled on the basis of a TRIMP (TRaining IMPulse) with four different equations and was used to measure the stress induced by this BH training. A reference value, based on the ratio between the average heart rate during all BHs and the lowest heart rate during BH training, was used for comparing training load index. Memory assessment was conducted both before and after this training. Of the four equations proposed, equation no. 4, named aTRIMP for "apnoea," showed the strongest correlation with our reference value (r=0.652, p<0.01). No difference was found between any of the memory tests before and after the BH training. The aTRIMP was a new representative index for monitoring habitual training of well-trained BH divers. Furthermore, this training had no negative impact on memory performance.

Identifying Key Training Load and Intensity Indicators in Ice Hockey Using Unsupervised Machine Learning

ABSTRACT To identify key training load (TL) and intensity indicators in ice hockey, practice, and game data were collected using a wearable 200-Hz accelerometer and heart rate (HR) recording throughout a four-week (29 days) competitive period (23 practice sessions and 8 competitive games in 17 elite Danish players (n = 427 observations). Within-individual correlations among accelerometer- (total accelerations [Acctot], accelerations >2 m·s−2 [Acc2], total accelerations [Dectot], decelerations <- 2 m·s−2 [Dec2]), among HR-derived (time >85% maximum HR [t85%HRmax], Edwards’ TL and modified training impulse) TL indicators, and between acceleration- and HR-derived TL parameters were large to almost perfect (r = 0.69–0.99). No significant correlations were observed between accelerometer- and HR-derived intensity indicators. Three between- and two within-components were found. The K-means++ cluster analysis revealed five and four clusters for between- and within-loadings, respectively. The least Euclidean distance from their centroid for each cluster was reported by session-duration, Acctot, Dec2, TRIMPMOD, %t85HRmax for between-loadings, whereas session-duration, Acc2, t85HRmax and Dec2/min for within-loadings. Specific TL or intensity variables might be relevant to identify similar between-subject groups (e.g. individual player, playing positions), or temporal patterns (e.g. changes in TL or intensity over time). Our study provides insights about the redundancy associated with the use of multiple TL and intensity variables in ice hockey.

Monitoring Within-Individual Dose-Response Relationships in Professional Soccer Players: The Importance of Fitness Level.

To (1)examine within-individual player dose-response associations between selected training-load measures and changes in aerobic fitness level via submaximal exercise heart rate (HRex%) and (2)measure the relationships between these dose-response associations with basal HRex% (to study the influence of fitness level on dose-response relationship). During an in-season phase, selected training-load measures including total minutes, total distance, mechanical work (the sum number of accelerations and decelerations > 3m2), high metabolic load distance, and Edwards' training impulse were collected via Global Positioning System and heart-rate sensors for analyzing accumulated load. A submaximal warm-up test was used repeatedly before and after 9 phases to elicit HRex% and track fitness changes at an individual level. Negative to positive extensive ranges of within-individual associations were found among players for different metrics (r = -.84 to .89). The relationship between pooled HRex% (basal fitness) and dose-response correlations showed inverse very large (r = -.71) and large (r = -.65) values for accumulated weekly minutes and distance. However, moderate values were found for all other measures (r = -.35 to -.42). Individual players show extensive different ranges of dose-response associations with training measures. The dose-response association is influenced by players' fitness level, and players with lower fitness levels show stronger inverse relationships with accumulated minutes and total distance.

Timing of cardio-oncological rehabilitation and cardiorespiratory fitness in patients receiving cardiotoxic chemotherapy: a longitudinal observational study.

Anthracycline-based chemotherapy has well-known cardiotoxic effects, butmay also cause skeletal muscle myopathy and negatively affect cardiorespiratory fitness and quality of life. The effectiveness of exercise training in improving cardiorespiratory fitness and quality of life during chemotherapy is highly variable. We set out to determine how the effect of exercise training on cardiorespiratory fitness (primary outcome) and quality of life (secondary outcome) in cancer patients is affected by the type of therapy they receive (cardiotoxic therapy with or without anthracyclines; non-cardiotoxic therapy) and the timing of the exercise training (during or after therapy). Consecutive patients with cancer who participated in an exercise-based cardio-oncology rehabilitation programme at a university hospital in Switzerland between January 2014 and February 2022 were eligible. Patients were grouped based on chemotherapy (anthracycline vs non-anthracycline) and timing of exercise training (during vs after chemotherapy). Peak oxygen uptake (VO2) was assessed with cardiopulmonary exercise testing (n = 200), and quality of life with the Functional Assessment of Cancer Therapies questionnaire (n = 77). Robust linear models were performed for change in peak VO2including type and timing of cardiotoxic therapies, age, training impulse and baseline peak VO2; change in quality of life was analysed with cumulative linked models. In all patients with valid VO2(n = 164), median change in peak VO2from before to after exercise training was 2.3 ml/kg/min (range: -10.1-15.9). The highest median change in peak VO2was 4.1 ml/kg/min (interquartile range [IQR]: 0.7-7.7) in patients who completed exercise training during non-anthracycline cardiotoxic or non-cardiotoxic therapies, followed by 2.8 ml/kg/min (IQR: 1.2-5.3) and 2.3 ml/kg/min (IQR: 0.1-4.6) in patients who completed exercise training after anthracycline and after non-anthracycline cardiotoxic or non-cardiotoxic therapies, respectively. In patients who completed exercise training during anthracycline therapy, peak VO2decreased by a median of -2.1 ml/kg/min (IQR: -4.7-2.0). In the robust linear model, there was a significant interaction between type and timing of cancer treatment for anthracycline therapy, with greater increases in peak VO2when exercise training was performed after anthracycline therapy. For quality of life, higher baseline scores were negatively associated with changes in quality of life. In our cohort, the increase in cardiorespiratory fitness was diminished when exercise training was performed concurrently with anthracyclines. For patients with cardiotoxic treatments other than anthracyclines, cardiorespiratory fitness and quality of life was not associated with timing of exercise training.

Comparison of time-motion, heart rate responses, and training load measurement in Brazilian jiu-jitsu heavyweight and lightweight fighters: a cross-sectional study

ABSTRACT This study compares technical-tactical and physiological parameters between lightweight and heavyweight male Brazilian Jiu-Jitsu (BJJ) fighters. We included 11 adult BJJ fighters (lightweight: age = 28 ± 7 years; body mass = 73 ± 2 kg; height = 1.72 ± 0.7 m; body mass index = 25 ± 2 kg/m2; heavyweight: age = 27 ± 3 years; body mass = 95 ± 6 kg; height = 1.87 ± 0.6 m; body mass index = 27 ± 2 kg/m2). Six participants were considered lightweight (71 to 77 kg) and five heavyweight divisions (88 to 101 kg). Initially, sample characteristics and a graded exercise test determined the physiological parameters. A simulated competition (10 minutes maximum) assessed technical-tactical characteristics, Heart Rate (HR), Rate of Perceived Exertion (RPE), TRaining IMPulse based on HR, session-RPE, and time at HR intensity zones (Z1, Z2, and Z3). A comparison test revealed that heavyweight athletes exhibited a higher height, body mass, total time in low-intensity efforts per block, number of standing combat blocks, and less time in high-intensity efforts per block and lower VO2MAX than lightweight (p < 0.05). The HR showed a nonlinear increase throughout each minute of the fights, with the heavyweight division demonstrating predominantly higher HR values. All fighters accumulated more time in training zone 3. The physiological and temporal differences between divisions suggest that BJJ training must be designed specifically for lightweight or heavyweight divisions.

Acute Response to Training after Returning from the Off-Season in Elite Rugby League Athletes.

The purposes of this study were to quantify the physiological response to the initial two-week preseason period in elite male rugby league (RL) athletes, and to determine if a repeated bout effect (RBE) occurs. Eighteen RL players were monitored for the initial two-week preseason period. Blood samples were collected on days (D)1, D2, D4, D5, D8, D9, D11 and D12 to measure creatine kinase (CK). Neuromuscular power was assessed on D1, D5, D8 and D12. During field-based sessions, the external training load was quantified using global positioning system technology, whilst the internal load was quantified using the training impulse and the session rating of perceived exertion. Resistance-based gym session volume was quantified by total repetitions x weight lifted. Perceived measures of fatigue and muscle soreness were assessed on all training days. Two-way (day x week) repeated measures analysis of variance and Bonferroni's corrected post-hoc tests identified significant changes. There were no significant changes in CK activity (649.2 ± 255.0 vs. 673.8 ± 299.1 µL; p = 0.63) or internal training load measures from week 1 to week 2. External training load measures including total distance (4138.1 ± 198.4 vs. 4525.0 ± 169.2 m; p < 0.001) and repeated high-intensity efforts (12.6 ± 1.8 vs. 17.5 ± 1.8 au; p < 0.001) significantly increased in week 2 compared to week 1. Internal training loads and CK activity did not change in response to an increase in external training loads during the initial preseason. The current results provide support for a 'real world' perspective of the RBE phenomenon that may be more applicable for team sport practitioners.

Analysis of Sleep, Nocturnal Physiology, and Physical Demands of NCAA Women's Ice Hockey Across a Championship Season.

Merrigan, JJ, Stone, JD, Kraemer, WJ, Friend, C, Lennon, K, Vatne, EA, and Hagen, JA. Analysis of sleep, nocturnal physiology, and physical demands of NCAA women's ice hockey across a championship season. J Strength Cond Res 38(4): 694-703, 2024-The aims of this study were to evaluate the (a) relationships between daily physical demands and nighttime sleep, heart rate (HR), and heart rate variability (HRV); (b) weekly changes in physical demands and sleep; and (c) differences among positions and between training and competition during a competitive season in National Collegiate Athletic Association (NCAA) women's ice hockey. Twenty-five NCAA Division I women's ice hockey athletes wore a sensor at night to monitor sleep quantity or quality (e.g., time asleep and sleep efficiency) and physiology (e.g., HR and HRV). During training and competitions (31 regular season and 7 postseason), athletes wore performance monitoring systems to assess workload demands (e.g., training impulse and TRIMP). As internal workload (TRIMP, Time >80% of HRmax, Average HR) during training or competition increased, nocturnal HRV decreased, HR increased, and Sleep Duration, Sleep Score, and Readiness Score decreased that night. Across the season, athletes experienced lower HRV, but exhibited longer sleep durations. Training Distance, Duration, Time >80% HRmax, Average HR, and TRIMP decreased, whereas competition Total Distance, Duration, and TRIMP increased across weeks throughout the season. There were differences across positions and season blocks when evaluating these data at the mesocycle level. Athletes slept longer before competition compared with training, but physiological data did not differ. Competitions had greater physiological demands than training. We speculate that the increased focus on sleep hygiene, as evidenced by the increase in sleep over the season, may have served as a recovery aid to combat physiological stress of accumulated demands of competitions that increased over time into postseason tournaments.

Internal load and wellness responses between consecutive collegiate female field hockey matches

This study evaluated internal load (IL) and wellness between consecutive field hockey matches played over a 2-day period across a 7-week season consisting of 12 total matches. Twelve NCAA Division I hockey players’ IL was assessed by heart rate (HR) zones (zone 1 = 50–60% HRmax, zone 2 = 60–70% HRmax, zone 3 = 70–80% HRmax, zone 4 = 80–90% HRmax, and zone 5 &gt; 90% HRmax) and HR-derived training impulse. Wellness items (sleep, stress, fatigue, soreness, and total wellness) were obtained to measure the players’ subjective responses. Linear mixed models were used to examine the main effects of time (matched pairs of games) and the interaction between match (match 1 vs 2) and week (week 1–6) for IL. For wellness, main effects for time (mid-week, post-match 1, and post-match 2) and the interaction between day (mid-week, post-match 1, and post-match 2) and week (week 1–5) were examined. More time was spent in HR zone 1 in match 2 versus 1 (mean difference (MD) = 4.2 ± 3.0 minutes). Total wellness, fatigue, and soreness were all worse post-match 2 compared to mid-week (MD = 1.8 ± 1.4 AU, MD = 0.4 ± 0.6 AU, and MD = 0.8 ± 0.4 AU, respectively). Our results indicate that evaluation of specific wellness items may help practitioners determine the source of decreased wellness and adjust the weekly training load or recovery strategies based off the results of the changes in IL.

Validity of information integration based on subjective and physiological data from a real sports condition: application to the judgment of fatigue in sport.

The objective of the present study was to confirm the convergent validity of information integration theory in the judgment of fatigue in sport, using information integration, subjective, and physiological data. Twenty healthy athletes were confronted with six cycling scenarios in two experimental conditions. In the laboratory condition, the athletes imagined the scenarios and had to cognitively combine the exercise intensity (30%, 50%, and 70% of the maximal intensity) and the exercise duration (15 and 30 min) when judging their expected level of fatigue. In the real sports condition, the athletes enacted each scenario and then rated their subjective fatigue. The heart rate was recorded continuously, so that the physiological training impulse could be calculated. We applied analyses of variance to the data and analyzed correlations between variables. The information integration data from the laboratory condition, the subjective data from the real sports condition, and the objective (physiological) data from the real sports condition were strongly correlated. The information integration patterns concerning fatigue as a function of the exercise duration and intensity obtained respectively from the three data sets were extremely similar.

Non-Invasive HRV Protocol and New Index to Assess Internal Training Load During Basketball Warm Up

The aim is to establish an specific, non-invasive, sub-maximum and applicable day-to-day protocol to assess the internal training load (IL) for basketball players using Heart Rate Variability (HRV) analysis before practice or competitions. Another aim is to propose a new IL index as a standardized parameter (%), to manage IL before practice sessions or competition. Twelve amateur male basketball players (age: 26.5 ± 8.8 years) completed HRV tests before a submaximal and intermittent drill (Activity Lay Up Wheel; ALUWIL 6min-test). Players performed a 5on5 scrimmage (MATCH) the following day during 10 min, completing rate of perceived exertion (RPE), total quality recovery (TQR) and wellness questionnaires, and continuous heart rate recordings. Players showed higher values of IL parameters based on heart rate (summatory heart rate zones, SHRZ; and training impulse, TRIMP), higher RPE values and lower recovery values during MATCH than ALUWIL (p&lt;0.01). The parameter % of summatory of heart rate zones (SHRZ) showed stronger correlations than SHRZ and TRIMP during MATCH (p&lt;0.001), and significant relations with RMSSD (square of the mean root of the adjacent R-R intervals) during the HRV test (p&lt;0.05). During the ALUWIL test, %SHRZ shows higher and stronger correlations than SHRZ with RRmean (mean of the R-R intervals) (-.807) but similar than SHRZ with RMSSD. In this specific context, ALUWIL test could offer reliable and applied information as a standardized and integrated protocol to assess internal training load in basketball players using cardiac parameters before practice and games. The parameters RRMean, RMSSD and %SHRZ could be a specific indicator for IL management on basketball. However, more research is needed to validate these proposals in a complex context. Key words: HRV, internal training load, basketball, heart rate, submaximal test, SHRZ.

Daily cardiac autonomic responses during the Tour de France in a male professional cyclist.

Heart rate variability (HRV) is a common means of monitoring responses to training, yet in professional cycling, one may question its usefulness, particularly during multi-day competitions such as Grand Tours. This study aims to report and analyze HRV responses in a male professional cyclist over a season, including the Tour de France. A professional cyclist recorded resting and exercise inter-beat intervals during 5 months, comprising a training period with two altitude sojourns and two competition blocks, including the Tour de France. Resting recordings lasted 5 min in the supine position and were used for computation of mean heart rate (HR), root mean square of the successive differences (RMSSDs), and power in the low- and high-frequency bands (LF and HF, respectively). Training load quantification was based on recorded HR during exercise and expressed as training impulses (TRIMPSs). LF (3,319 ± 2,819 vs. 1,097 ± 1,657 ms2), HF (3,590 ± 1858 vs. 1,267 ± 1,683 ms2), and RMSSD (96 ± 26 vs. 46 ± 30 ms) were higher and HR (47 ± 4 vs. 54 ± 2 bpm) was lower during the training period when compared to the two competition blocks. The coefficient of variation (CV) was significantly lower during the training period than during the two competition blocks for RMSSD (26 vs. 72%), LF (85 vs. 160%), and HF (58 vs. 141%). The present study confirms that monitoring daily HRV responses during training periods is valuable in professional cycling, but questions its usefulness during the Tour de France. Moreover, the previous suggestion that CV in RMSSD would help to predict poor performance was not confirmed in a professional cyclist.

Using training impulse and monotony methods to monitor aerobic training load in rats.

This study is the first to apply training impulse (TRIMP) and Training Monotony (TM) methodologies, within the realm of sport science, in animal model studies. Rats were divided into Sedentary (SED, n=10) and Training (TR, n=13). TR performed a four-week moderate-intensity interval training with load progression. Lactate kinetics, lactate training impulse (TRIMPLac), maximal speed training impulse (TRIMPSmax) and TM were utilized to develop and monitor training protocol. TR showed an 11.9% increase in time to exhaustion at the second maximum incremental test and a 17.5% increase at the third test. External work was increased by 17.8% at the second test and 30.3% at the third. There was a 10.6% increase in external work at the third test compared to the second for TR. No difference in TRIMPLac between the 1st week (94±9 A.U) and 3rdweek (83±10 A.U) were seen. TRIMPSmax was 2400 A.U. in the 1st week, 2760 A.U. in the 2nd and 3rd weeks, and 3120 A.U. in the 4th week. The TM remained at 1.24 A.U throughout the protocol and there was no dropouts. TRIMPLac and TRIMPSmax contributed to the development and monitoring loads, demonstrating their potential to improve the accuracy of training protocols in animal model research.

Relationship Between External Training Load and Session Rating of Perceived Exertion Training Impulse in Elite Sprinters.

To quantify the change in session rating of perceived exertion training impulse (RPE-TRIMP) that may occur in response to increased running distance at 3 running velocity ranges in elite sprinters. We monitored training load in elite sprinters (women: n = 7; men: n = 11) using wearable Global Positioning System technology and RPE-TRIMP for a total of 681 individual training sessions during a 22-week competition-preparation period. Internal training load was operationalized by RPE-TRIMP, and external training load was operationalized by distance covered in 3 velocity ranges. A linear mixed-effects model with athlete as a random effect was fit to RPE-TRIMP with total distance covered at ≤69.99% (low-velocity running [LVR]), 70% to 84.99% (high-velocity running [HVR]), and 85% to 100% (very-high-velocity running [VHVR]) of individual maximum velocity. Increased running distance in all 3 velocity ranges (LVR, HVR, and VHVR) resulted in a significant (P < .001) increase in RPE-TRIMP. Coefficients (95% CIs) were .10 (.08-.11) for LVR, .23 (.18-.28) for HVR, and .44 (.35-.53) for VHVR. A 50-m increase in running distance covered in the LVR, HVR, and VHVR velocity ranges was associated with increases in RPE-TRIMP of 5, 11.5, and 22 arbitrary units, respectively. Internal training load, calculated as RPE-TRIMP, increased with increases in total distance covered in the LVR, HVR, and VHVR velocity ranges (P < .001). RPE-TRIMP can be a practical solution for monitoring global training-session load in elite sprinters.

The Profile of the Internal Load of Amateur Soccer Players during Official Matches with Formation 1-4-3-3 and Relationships with Indexes of External Load

The purpose of this study was to investigate the internal load of amateur soccer players during official championship matches when playing with the 1-4-3-3 formation. Additionally, the possible relationship between internal load variables and external load indices was explored. The study involved 18 amateur soccer players, and the Polar Team Pro GPS system was used to record external load and heart rate (HR) during official championship matches. Internal load was assessed using %HRmax and Edward’s training impulse (TRIMPEdw). External load indices included total distance (TD), pace (distance/min), number of sprints, distance covered in different speed zones, accelerations (&gt;2 m/s2), and decelerations (&lt;−2 m/s2). Players were categorized as central defenders (CD), side defenders (SD), central midfielders (CM), side midfielders (SM), and forwards (F). The results indicated no differences in internal load indices among playing positions. During matches, SM performed the most sprints, while CD performed the fewest (p &lt; 0.05). CD covered the shortest distances in speed zones &gt;7.20 km/h, whereas CM and SM covered the longest distances (p &lt; 0.05). Additionally, CD had fewer accelerations and decelerations compared to SM (p &lt; 0.05). In the first half, differences were observed in pace (distance/min) (p &lt; 0.05), but not in the second half. Between halves, differences in %HRmax were observed for all positions, while TRIMPEdw differed in CM and F. CM showed the most differences between halves. Throughout the matches, a high correlation was found between %HRmax and pace (distance/min), while TRIMPEdw correlated with TD, as well as distances in high-speed zones (14.40–25.19 km/h). This suggests that TRIMPEdw is a comprehensive indicator dependent on volume (TD) and on high-intensity actions, which are crucial in soccer, influencing players’ and teams’ performances. Therefore, for assessing the internal load of amateur soccer players, TRIMPEdw may be a more useful indicator. This study provides valuable information for coaches of amateur soccer teams using the 1-4-3-3 formation regarding running profiles, accelerations/decelerations, and the profile of internal load in each playing position. This information can be used to individualize training based on players’ playing positions.

Recommendations for Measurement of Bodybuilding Internal Training Load by eTRIMP Method

Currently, analysis of training data metrics has become increasingly important in characterizing high throughput. In fact, in bodybuilding, the RPE (rate of perceived exertion) assessment is the metric commonly used to calculate training volume. Therefore, this study demonstrates another way for bodybuilding athletes to evaluate their training through heart rate using the TRIMP (training impulse) method proposed by Edwards to analyze the intensity of a given training model. For this athlete, it is important to stay most of the time outside heart rate zone 1, not have more than 10% of total training time in zone 5 and contain the largest proportion of total training time in zones 2, 3 and 4.

Acute Responses of Youth Elite Players to a Football Match in Terms of Blood Markers.

The current study verified the acute responses of participants to a football match in terms of blood markers. Sixteen elite U-18 male football players were divided into two groups: experimental (EG, n = 10), who played a friendly football match; and control (CG), who were not exposed to any physical exertion. Intravenous blood samples were collected from both groups at baseline, pre-match, half-time, and post-match. The blood analysis consisted of four groups: immunological (leukocytes, platelets, and cortisol), muscle damage (creatine kinase and lactate dehydrogenase), metabolic (lactate, glucose, erythrocytes, hematocrit, hemoglobin, and urea), and electrolytic (sodium, calcium, and potassium). Edwards' training impulse demonstrated that the first half was more demanding than the second half (p = 0.020). Significant changes between time points and groups were observed for leukocytes (pre-match: 6920 ± 1949; post-match: 13,890 ± 3292; p ≤ 0.05) and cortisol (pre-match: 10.78 ± 3.63; post-match: 19.15 ± 7.40; p ≤ 0.05). CK (pre-match: 516.50 ± 248.38; post-match: 713.70 ± 308.20; p ≤ 0.05) and LDH (pre-match: 348.80 ± 36.49; post-match: 414.80 ± 26.55; p ≤ 0.05) increased significantly across the time points for the EG, with no difference between the groups, however. Raised lactate (pre-match: 1.05 ± 0.32; post-match: 3.24 ± 1.60; p ≤ 0.05) and glucose (pre-match: 72.54 ± 9.76; post-match: 101.42 ± 19.87; p ≤ 0.05) differences between the groups at half-time were also observed. These current findings provide helpful information to better understand football match demands regarding physiological effects.