Validation of session ratings of perceived exertion for quantifying training load in karate kata sessions

2022 ◽  
Author(s):  
Daniel Bok ◽  
Nika Jukić ◽  
Carl Foster
Keyword(s):  
Perceived Exertion ◽  
Training Load ◽  
Ratings Of Perceived Exertion

scholarly journals A comparison of sessional ratings of perceived exertion to cardiovascular indices of exercise intensity during competition in elite field hockey players

2018 ◽  
Vol 10 (1) ◽  
pp. 157-162 ◽  
Author(s):  
Andrew Scott Perrotta ◽  
Darren E. R. Warburton
Keyword(s):  
Heart Rate ◽  
Anaerobic Threshold ◽  
Exercise Intensity ◽  
Perceived Exertion ◽  
Training Load ◽  
Field Hockey ◽  
Ratings Of Perceived Exertion ◽  
National Team ◽  
Hockey Players ◽  
Competition Period

Abstract Study aim: Recent evidence has revealed a reduction in the strength of correlation between ratings of perceived exertion and a heart rate (HR) derived training load in elite field hockey players during competition. These competitive periods involve sustained levels of cardiovascular performance coupled with considerable time performing above the anaerobic threshold. As such, the purpose of this investigation was to examine the magnitude of correlation between ratings of perceived exertion and time spent above threshold and two HR derived training loads.Material and methods: Seventeen (n = 17) international caliber female field hockey players competing as a national team were monitored over four matches during a seven-day competition period within the 2016 Olympic Cycle. Cardiovascular indices of exercise intensity were derived from HR dynamics and were quantified through estimating time spent above anaerobic threshold (LT2), the Edwards training load model (TLED) and the Polar Training Load (TLPOL). Sessional ratings of perceived exertion (sRPE) were recorded after each match.Results: 64 samples were recorded for analysis. HR derived (TLED& TL POL) and sRPE training loads remained comparable between matches. A large correlation (p = 0.01) was observed between sRPE and each heart rate derived training load (TLED& TLPOL). An unremarkable relationship (p = 0.06) was revealed between time spent above LT2 and sRPE.Conclusions: Our results demonstrate HR derived training loads (TLPOL& TLED) exhibit a stronger correlation with sRPE than time spent above LT2 in elite field hockey players during competition.

scholarly journals The Role of Specific Warm-up during Bench Press and Squat Exercises: A Novel Approach

2020 ◽  
Vol 17 (18) ◽  
pp. 6882
Author(s):  
Bruno Ribeiro ◽  
Ana Pereira ◽  
Pedro P. Neves ◽  
António C. Sousa ◽  
Ricardo Ferraz ◽  
...  
Keyword(s):  
Perceived Exertion ◽  
Bench Press ◽  
Peak Velocity ◽  
Dynamic Strength ◽  
Training Load ◽  
Ratings Of Perceived Exertion ◽  
Warm Up ◽  
Novel Approach ◽  
Maximal Dynamic Strength

The current study aims to verify the effects of three specific warm-ups on squat and bench press resistance training. Forty resistance-trained males (19–30 years) performed 3 × 6 repetitions with 80% of maximal dynamic strength (designated as training load) after one of the following warm-ups (48 h between): (i) 2 × 6 repetitions with 40% and 80% of the training load (WU), (ii) 6 × 80% of training load (WU80), or (iii) 6 × 40% of the training load (WU40). Mean propulsive velocity (MPV), velocity loss (VL), peak velocity (PV), time to achieve PV, power, work, heart rates, and ratings of perceived exertion were analyzed. In squat exercises, higher MPV were found in WU80 compared with WU40 (2nd set: 0.69 ± 0.09 vs. 0.67 ± 0.06 m.s−1, p = 0.02, ES = 0.80; 3rd set: 0.68 ± 0.09 vs. 0.66 ± 0.07 m.s−1, p = 0.05, ES = 0.51). In bench press exercises, time to PV was lower in WU compared with WU40 (1st set: 574.77 ± 233.46 vs. 694.50 ± 211.71 m.s−1, p < 0.01, ES = 0.69; 2nd set: 533.19 ± 272.22 vs. 662.31 ± 257.51 m.s−1, p = 0.04, ES = 0.43) and total work was higher (4749.90 ± 1312.99 vs. 4631.80 ± 1355.01 j, p = 0.01, ES = 0.54). The results showed that force outputs were mainly optimized by WU80 in squat training and by WU in bench press training. Moreover, warming-up with few repetitions and low loads is not enough to optimize squat and bench press performances.

Specific warm-up enhances movement velocity during bench press and squat resistance training

2021 ◽  
Keyword(s):  
Resistance Training ◽  
Perceived Exertion ◽  
Bench Press ◽  
Peak Velocity ◽  
Random Order ◽  
Training Load ◽  
Training Methods ◽  
Ratings Of Perceived Exertion ◽  
Movement Velocity ◽  
Warm Up

Background and objective: The purpose of this study was to investigate the effect of specific warm-up on squat and bench press resistance training. Methods: Thirty-four resistance-trained males (23.53 ± 2.35 years) participated in the current study. Among these, 12 were evaluated in the squat and 22 in the bench press. After determining the maximal strength load (1RM), each participant performed a training set (3 × 6 repetitions) with 80%1RM (training load) after completing a specific warm-up and without warming up, in random order. The warm-up comprised 2 × 6 repetitions with 40% and 80% of the training load, respectively. Mean propulsive velocity, velocity loss, peak velocity, mechanical power, work, heart rate and ratings of perceived exertion were assessed. Results: The results showed that after the warm-up, the participants were able to perform the squat and bench press at a higher mean propulsive velocity in the first set (squat: 0.68 ± 0.05 vs. 0.64 ± 0.06 m·s−1, p = 0.009, ES = 0.91; bench press: 0.52 ± 0.06 vs. 0.47 ± 0.08 m·s−1, p = 0.02, ES = 0.56). The warm-up positively influenced the peak velocity (1.32 ± 0.12 vs. 1.20 ± 0.11 m·s−1, p = 0.001, ES = 1.23) and the time to reach peak velocity (593.75 ± 117.01 vs. 653.58 ± 156.53 ms, p = 0.009, ES = 0.91) during the squat set. Conclusion: The specific warm-up seems to enhance neuromuscular actions that enable a higher movement velocity during the first training repetitions and to allow greater peak velocities in less time.

Sport-Specific Outdoor Rehabilitation in a Group Setting: Do the Intentions Match Actual Training Load?

2018 ◽  
Vol 27 (2) ◽  
pp. 151-156 ◽  
Author(s):  
Jeroen de Bruijn ◽  
Henk van der Worp ◽  
Mark Korte ◽  
Astrid de Vries ◽  
Rick Nijland ◽  
...  
Keyword(s):  
Heart Rate ◽  
Perceived Exertion ◽  
Training Load ◽  
Soccer Players ◽  
Group Setting ◽  
Ratings Of Perceived Exertion ◽  
Lower Limb Injury ◽  
Distance Data ◽  
Group Rehabilitation ◽  
The Relationship

Context: Previous research has shown a weak relationship between intended and actual training load in various sports. Due to variety in group and content, this relationship is expected to be even weaker during group rehabilitation. Objective: The goal of this study was to examine the relationship between intended and actual training load during sport-specific rehabilitation in a group setting. Design: Observational study. Setting: Three outdoor rehabilitation sessions. Participants: Nine amateur soccer players recovering from lower limb injury participated in the study (age 22 ± 3 y, height 179 ± 9 cm, body mass 75 ± 13 kg). Main Outcome Measures: We collected physiotherapists’ ratings of intended exertion (RIE) and players’ ratings of perceived exertion (RPE). Furthermore, Zephyr Bioharness 3 equipped with GPS-trackers provided heart rate and distance data. We computed heart rate–based training loads using Edwards’ method and a modified TRIMP. Results: Overall, we found weak correlations (N = 42) between RIE and RPE (r = 0.35), Edwards’ (r = 0.34), TRIMPMOD (r = 0.07), and distance (r = 0.26). Conclusions: In general, physiotherapists tended to underestimate training loads. To check whether intended training loads are met, it is thus recommended to monitor training loads during rehabilitation.

scholarly journals The tracking of internal and external training loads with next-day player-reported fatigue at different times of the season in elite soccer players

2021 ◽  
pp. 174795412198896
Author(s):  
Garrison Draper ◽  
Matthew Wright ◽  
Paul Chesterton ◽  
Greg Atkinson
Keyword(s):  
Global Positioning System ◽  
Perceived Exertion ◽  
Longitudinal Research ◽  
Principal Component ◽  
Training Load ◽  
Ratings Of Perceived Exertion ◽  
Global Positioning ◽  
Within Subjects ◽  
External Training ◽  
Psychological Mood

The aim was to assess factor structure of player-reported fatigue and quantify within-subjects association between changes in training load measures and next day player-reported fatigue at different time points of an elite football season. Using longitudinal research design, twenty-four professional footballers, mean (SD) age of 25.7 (3.4) years, were monitored during their competitive season, including pre-season. Player-reported fatigue data and session ratings of perceived exertion (session-RPE) were collected via a mobile application. Player’s Heart rate (HR) and global positioning system (GPS) data were collected daily for each player in field sessions. Principal component analysis (PCA) indicated three components with Eigenvalues above 1.0; “soreness”, “mood, and “hydration”. Within-player correlations between training load values and next day player-reported fatigue values were trivial to moderate (r ≈ −0.42 to −0.04). In-season we observed large correlations between Total Distance (TD) and PlayerLoad with Soreness (r = −0.55, 95% CI: −0.62 to −0.46; r = −.054, 95% CI: −0.62 to −0.46), but during pre-season, correlations were small (r = −0.15, 95% CI: −0.28 to −0.01; r = −0.13, 95% CI: −0.26 to 0.01). The HR TRIMP, TD and session-RPE measures each showed trivial to moderate correlations (r ≈ −0.41 to −0.08) with next day “mood”. Our in-house player-reported fatigue questionnaire was sensitive to the multi-dimensional nature of fatigue, identifying physiological (soreness), psychological (mood and stress) and nutritional (hydration and nutrition) components. We found the in-season correlations with training load to be greater than previously reported in the literature, specifically with next day player-reported “soreness”. Nevertheless, the correlations between the items of our scale and pre-season training load were small.

Monitoring Rating of Perceived Exertion Time in Zone: A Novel Method to Quantify Training Load in Elite Open-Water Swimmers?

2020 ◽  
pp. 1-5
Author(s):  
Cristian Ieno ◽  
Roberto Baldassarre ◽  
Maddalena Pennacchi ◽  
Antonio La Torre ◽  
Marco Bonifazi ◽  
...  
Keyword(s):  
Heart Rate ◽  
Perceived Exertion ◽  
Hybrid Approach ◽  
Open Water ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Zone Model ◽  
Ratings Of Perceived Exertion ◽  
Accurate Analysis ◽  
Novel Method

Purpose: To analyze training-intensity distribution (TID) using different independent monitoring systems for internal training load in a group of elite open-water swimmers. Methods: One hundred sixty training sessions were monitored in 4 elite open-water swimmers (2 females and 2 males: 23.75 [4.86] y, 62.25 [6.18] kg, 167 [6.68] cm) during 5 weeks of regular training. Heart-rate-based methods, such as time in zone (TIZ), session goal (SG), and hybrid (SG/TIZ), were used to analyze TID. Similarly to SG/TIZ, a new hybrid approach, the rating of perceived exertion (RPE)/TIZ for a more accurate analysis of TID was used. Moreover, based on the 3-zone model, the session ratings of perceived exertion of the swimmers and the coach were compared. Results: Heart-rate- and RPE-based TID methods were significantly different in quantifying Z1 (P = .012; effect size [ES] = 0.490) and Z2 (P = .006; ES = 0.778), while no difference was observed in the quantification of Z3 (P = .428; ES = 0.223). The heart-rate-based data for Z1, Z2, and Z3 were 83.2%, 7.4%, and 8.1% for TIZ; 80.8%, 8.3%, and 10.8% for SG/TIZ; and 55%, 15.6%, and 29.4% for SG. The RPE-based data were 70.9%, 19.9%, and 9.2% for RPE/TIZ% and 41.2%, 48.9%, and 9.7% for the session rating of perceived exertion. No differences were observed between the coach’s and the swimmers’ session ratings of perceived exertion in the 3 zones (Z1: P = .663, ES = −0.187; Z2: P = .110, ES = 0.578; Z3: P = .149, ES = 0.420). Conclusion: Using RPE-based TID methods, Z2 was significantly larger compared with Z1. These results show that RPE-based TID methods in elite open-water swimmers are affected by both intensity and volume.

scholarly journals Relationships Between Internal Training Load in a Taper With Elite Weightlifting Performance Calculated Using Different Moving Average Methods

2020 ◽  
pp. 1-11
Author(s):  
Joseph O.C. Coyne ◽  
Robert U. Newton ◽  
G. Gregory Haff
Keyword(s):  
Perceived Exertion ◽  
Moving Average ◽  
Training Load ◽  
Ratings Of Perceived Exertion ◽  
World Record ◽  
Training Stress ◽  
Training Impulse ◽  
And Training ◽  
Weighted Moving Average ◽  
Exponentially Weighted

Purpose: A simple and 2 different exponentially weighted moving average methods were used to investigate the relationships between internal training load and elite weightlifting performance. Methods: Training impulse data (sessional ratings of perceived exertion × training duration) were collected from 21 elite weightlifters (age = 26.0 [3.2] y, height = 162.2 [11.3] cm, body mass = 72.2 [23.8] kg, previous 12-mo personal best total 96.3% [2.7%] of world record total) during the 8 weeks prior to the 2016 Olympic Games qualifying competition. The amount of training modified or cancelled due to injury/illness was also collected. The training stress balance (TSB) and acute to chronic workload ratio (ACWR) were calculated with the 3 moving average methods. Along with the amount of modified training, TSB and ACWR across the moving average methods were then examined for their relationship to competitive performance. Results: There were no consistent associations between performance and training load on the day of competition. The volatility (SD) of the ACWR in the last 21 days preceding the competition was moderately correlated with performance across moving average methods (r = −.41 to .48, P = .03–.07). TSB and ACWR volatility in the last 21 days were also significantly lower for successful performers but only as a simple moving average (P = .03 and .03, g = 1.15 and 1.07, respectively). Conclusions: Practitioners should consider restricting change and volatility in an athlete’s TSB or ACWR in the last 21 days prior to a major competition. In addition, a simple moving average seemed to better explain elite weightlifting performance than the exponentially weighted moving averages in this investigation.

scholarly journals Self-Selected Training Load and RPE During Resistance and Aerobic Training Among Recreational Exercisers

2018 ◽  
Vol 125 (4) ◽  
pp. 769-787 ◽  
Author(s):  
Marcelo R. C. Dias ◽  
Roberto Simão ◽  
Francisco J. F. Saavedra ◽  
Cosme F. Buzzachera ◽  
Steven Fleck
Keyword(s):  
Perceived Exertion ◽  
Aerobic Training ◽  
Maximal Exercise ◽  
Treadmill Exercise ◽  
Cardiovascular Fitness ◽  
Training Load ◽  
Ratings Of Perceived Exertion ◽  
Maximal Exercise Test ◽  
Specific Instruction ◽  
Trained Subjects

This study compared training load and ratings of perceived exertion (RPE) during resistance training (RT) and aerobic training (AT) sessions at self-selected intensity. Participants were 54 recreationally trained subjects assigned to either RT or AT groups. During RT, participants performed three sets of 10 repetitions of each exercise at a self-selected intensity (load). After RT completion, participants performed one repetition maximum (1RM) and 10RM tests. During AT, participants performed a treadmill exercise at a self-selected intensity and duration (velocity and time). After AT completion, participants performed a treadmill maximal exercise test using a ramp protocol. During RT, subjects chose an intensity (43.6%–60.2% 1RM) below typical training recommendations, and RPE increased in successive exercise sets. During AT, participants chose an intensity (83.9% Heart Ratepeak) in line with typical training recommendations, and RPE increased from the first to second quartile of the session (from a mean of 3.9, standard deviation [ SD] = 1.7 to a mean of 5.4, SD = 1.7; p < .05) and remained stable thereafter. These recreationally trained participants self-selected lower RT intensities than are typically recommended for strength and hypertrophy increases (>67% 1RM) and AT intensities in line with typically recommended intensity (64%–95% HRmax) for cardiovascular fitness increases. Thus, for recreational trained individuals to perform RT at recommended intensities, specific instruction will be required.

Analysis of a training mesocycle and positional quantification in elite European soccer players

2017 ◽  
Vol 12 (5) ◽  
pp. 665-676 ◽  
Author(s):  
Adam L Owen ◽  
Carlos Lago-Peñas ◽  
Miguel-Ángel Gómez ◽  
Bruno Mendes ◽  
Alexandre Dellal
Keyword(s):  
Perceived Exertion ◽  
Training Load ◽  
Soccer Players ◽  
Ratings Of Perceived Exertion ◽  
Positioning Systems ◽  
Professional Soccer ◽  
Training Post ◽  
Elite Level ◽  
Daily Training ◽  
Player Performance

Ensuring adequate levels of training and recovery at the elite level of professional soccer to maximise player performance has continued to drive the necessity to monitor the training load and physical training output of soccer players. The aim of this investigation was to analyse a training mesocycle whilst quantifying positional demands imposed on elite European soccer players. Sixteen players were assessed using global positioning systems and ratings of perceived exertion over a competitive training six-week mesocycle period. The positional demands and training loads were analysed in addition to match conditions (match location, match score) and player’s age. Results from the investigation revealed that typical daily training loads (i.e. total distance, high-intensity distance, sprint distance, average speed, ratings of perceived exertion) did not differ throughout each week of the mesocycle in-season period. Further analysis revealed training loads were significantly lower on match day-1 when compared to training loads on match day-2, match day-3 and match day-4 preceding a match ( p < 0.05). Significant differences in physical outputs were also found between match day-2, match day-3 and match day-4 highlighting a structured periodised tapered approach ( p < 0.05). Lower average speeds were reported in training post-successful matches compared to defeats ( p < 0.05), and more specifically when a match was played away compared to home fixtures ( p < 0.05). To conclude, practitioners can maintain a uniformed and structured training load mesocycle whilst inducing variation of the physical outputs during the microcycle phase. Additionally, the investigation also provides a tapering approach that may induce significant variation of the positional demands.

Training Mode’s Influence on the Relationships between Training-Load Models During Basketball Conditioning

2014 ◽  
Vol 9 (5) ◽  
pp. 851-856 ◽  
Author(s):  
Aaron T. Scanlan ◽  
Neal Wen ◽  
Patrick S. Tucker ◽  
Nattai R. Borges ◽  
Vincent J. Dalbo
Keyword(s):  
Perceived Exertion ◽  
Training Load ◽  
Ratings Of Perceived Exertion ◽  
Game Play ◽  
Basketball Players ◽  
Physiological Models ◽  
Load Models ◽  
Training Plan ◽  
Training Impulse ◽  
Pearson Correlations

Purpose:To compare perceptual and physiological training-load responses during various basketball training modes.Methods:Eight semiprofessional male basketball players (age 26.3 ± 6.7 y, height 188.1 ± 6.2 cm, body mass 92.0 ± 13.8 kg) were monitored across a 10-wk period in the preparatory phase of their training plan. Player session ratings of perceived exertion (sRPE) and heart-rate (HR) responses were gathered across base, specific, and tactical/game-play training modes. Pearson correlations were used to determine the relationships between the sRPE model and 2 HR-based models: the training impulse (TRIMP) and summated HR zones (SHRZ). One-way ANOVAs were used to compare training loads between training modes for each model.Results:Stronger relationships between perceptual and physiological models were evident during base (sRPE-TRIMP r = .53, P < .05; sRPE-SHRZ r = .75, P < .05) and tactical/game-play conditioning (sRPE-TRIMP r = .60, P < .05; sRPE-SHRZ r = .63; P < .05) than during specific conditioning (sRPE-TRIMP r = .38, P < .05; sRPE-SHRZ r = .52; P < .05). Furthermore, the sRPE model detected greater increases (126–429 AU) in training load than the TRIMP (15–65 AU) and SHRZ models (27–170 AU) transitioning between training modes.Conclusions:While the training-load models were significantly correlated during each training mode, weaker relationships were observed during specific conditioning. Comparisons suggest that the HR-based models were less effective in detecting periodized increases in training load, particularly during court-based, intermittent, multidirectional drills. The practical benefits and sensitivity of the sRPE model support its use across different basketball training modes.

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