The Influence of Exercise Intensity on the Association Between Kilojoules Spent and Various Training Loads in Professional Cycling

2019 ◽  
Vol 14 (10) ◽  
pp. 1395-1400 ◽  
Author(s):  
Teun van Erp ◽  
Marco Hoozemans ◽  
Carl Foster ◽  
Jos J. de Koning
Keyword(s):  
Exercise Intensity ◽  
Power Output ◽  
Perceived Exertion ◽  
Rating Of Perceived Exertion ◽  
Regression Coefficients ◽  
Quadratic Relation ◽  
Significant Regression ◽  
Training Stress ◽  
Training Impulse ◽  
Professional Cycling

Purpose: A valid measure for training load (TL) is an important tool for cyclists, trainers, and sport scientists involved in professional cycling. The aim of this study was to explore the influence of exercise intensity on the association between kilojoules (kJ) spent and different measures of TL to arrive at valid measures of TL. Methods: Four years of field data were collected from 21 cyclists of a professional cycling team, including 11,716 training and race sessions. kJ spent was obtained from power output measurements, and others TLs were calculated based on the session rating of perceived exertion (sRPE), heart rate (Lucia training impulse [luTRIMP]), and power output (training stress score [TSS]). Exercise intensity was expressed by the intensity factor (IF). To study the effect of exercise intensity on the association between kJ spent and various other TLs (sRPE, luTRIMP, and TSS), data from low- and high-intensity sessions were subjected to regression analyses using generalized estimating equations. Results: This study shows that the IF is significantly different for training and race sessions (0.59 [0.03] vs 0.73 [0.03]). Significant regression coefficients show that kJ spent is a good predictor of sRPE, and luTRIMP, as well as TSS. However, IF does not influence the associations between kJ spent and sRPE and luTRIMP, while the association with TSS is different when sessions are done with low or high IF. Conclusion: It seems that the TSS reacts differently to exercise intensity than sRPE and luTRIMP. A possible explanation could be the quadratic relation between IF and TSS.

Training Characteristics of Male and Female Professional Road Cyclists: A 4-Year Retrospective Analysis

2020 ◽  
Vol 15 (4) ◽  
pp. 534-540 ◽  
Author(s):  
Teun van Erp ◽  
Dajo Sanders ◽  
Jos J. de Koning
Keyword(s):  
Heart Rate ◽  
Retrospective Analysis ◽  
Perceived Exertion ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Training Intensity ◽  
Male And Female ◽  
Stress Score ◽  
Training Stress ◽  
Training Impulse

Purpose: To describe the training intensity and load characteristics of professional cyclists using a 4-year retrospective analysis. Particularly, this study aimed to describe the differences in training characteristics between men and women professional cyclists. Method: For 4 consecutive years, training data were collected from 20 male and 10 female professional cyclists. From those training sessions, heart rate, rating of perceived exertion, and power output (PO) were analyzed. Training intensity distribution as time spent in different heart rate and PO zones was quantified. Training load was calculated using different metrics such as Training Stress Score, training impulse, and session rating of perceived exertion. Standardized effect size is reported as Cohen’s d. Results: Small to large higher values were observed for distance, duration, kilojoules spent, and (relative) mean PO in men’s training (d = 0.44–1.98). Furthermore, men spent more time in low-intensity zones (ie, zones 1 and 2) compared with women. Trivial differences in training load (ie, Training Stress Score and training impulse) were observed between men’s and women’s training (d = 0.07–0.12). However, load values expressed per kilometer were moderately (d = 0.67–0.76) higher in women compared with men’s training. Conclusions: Substantial differences in training characteristics exist between male and female professional cyclists. Particularly, it seems that female professional cyclists compensate their lower training volume, with a higher training intensity, in comparison with male professional cyclists.

An Assessment of the Validity and Reliability of Two Perceived Exertion Rating Scales among Hong Kong Children

2002 ◽  
Vol 95 (3_suppl) ◽  
pp. 1047-1062 ◽  
Author(s):  
Mee-Lee Leung ◽  
Pak-Kwong Chung ◽  
Raymond W. Leung
Keyword(s):  
Heart Rate ◽  
Hong Kong ◽  
Oxygen Consumption ◽  
Exercise Intensity ◽  
Power Output ◽  
Perceived Exertion ◽  
Rating Scales ◽  
Rating Of Perceived Exertion ◽  
Validity And Reliability ◽  
Effort Rating

This study evaluated the validity and reliability of the Chinese-translated (Cantonese) versions of the Borg 6–20 Rating of Perceived Exertion (RPE) scale and the Children's Effort Rating Table (CERT) during continuous incremental cycle ergometry with 10- to 11-yr.-old Hong Kong school children. A total of 69 children were randomly assigned, with the restriction of groups being approximately equal, to two groups using the two scales, CERT ( n = 35) and RPE ( n = 34). Both groups performed two trials of identical incremental continuous cycling exercise (Trials 1 and 2) 1 wk. apart for the reliability test. Objective measures of exercise intensity (heart rate, absolute power output, and relative oxygen consumption) and the two subjective measures of effort were obtained during the exercise. For both groups, significant Pearson correlations were found for perceived effort ratings correlated with heart rate ( rs ≥ .69), power output ( rs ≥ .75), and oxygen consumption ( rs ≥ .69). In addition, correlations for CERT were consistently higher than those for RPE. High test-retest intraclass correlations were found for both the effort ( R = .96) and perceived exertion ( R = 89) groups, indicating that the scales were reliable. In conclusion, the CERT and RPE scales, when translated into Cantonese, are valid and reliable measures of exercise intensity during controlled exercise by children. The Effort rating may be better than the Perceived Exertion scale as a measure of perceived exertion that can be more validly and reliably used with Hong Kong children.

Relationship Between Various Training-Load Measures in Elite Cyclists During Training, Road Races, and Time Trials

2019 ◽  
Vol 14 (4) ◽  
pp. 493-500 ◽  
Author(s):  
Teun van Erp ◽  
Carl Foster ◽  
Jos J. de Koning
Keyword(s):  
Perceived Exertion ◽  
Mechanical Energy ◽  
Training Load ◽  
The Other ◽  
Rating Of Perceived Exertion ◽  
Heart Rate Data ◽  
Training Stress ◽  
Training Impulse ◽  
Road Races ◽  
The Relationship

Purpose: The relationship between various training-load (TL) measures in professional cycling is not well explored. This study investigated the relationship between mechanical energy spent (in kilojoules), session rating of perceived exertion (sRPE), Lucia training impulse (LuTRIMP), and training stress score (TSS) in training, races, and time trials (TT). Methods: For 4 consecutive years, field data were collected from 21 professional cyclists and categorized as being collected in training, racing, or TTs. Kilojoules (kJ) spent, sRPE, LuTRIMP, and TSS were calculated, and the correlations between the various TLs were made. Results: 11,655 sessions were collected, from which 7596 sessions had heart-rate data and 5445 sessions had an RPE score available. The r between the various TLs during training was almost perfect. The r between the various TLs during racing was almost perfect or very large. The r between the various TLs during TTs was almost perfect or very large. For all relationships between TSS and 1 of the other measurements of TL (kJ spent, sRPE, and LuTRIMP), a significant different slope was found. Conclusion: kJ spent, sRPE, LuTRIMP, and TSS all have a large or almost perfect relationship with each other during training, racing, and TTs, but during racing, both sRPE and LuTRIMP have a weaker relationship with kJ spent and TSS. Furthermore, the significant different slope of TSS vs the other measurements of TL during training and racing has the effect that TSS collected in training and road races differs by 120%, whereas the other measurements of TL (kJ spent, sRPE, and LuTRIMP) differ by only 73%, 67%, and 68%, respectively.

scholarly journals The Influence of Different Training Load Quantification Methods on the Fitness-Fatigue Model

2020 ◽  
pp. 1-9
Author(s):  
Kobe M. Vermeire ◽  
Freek Van de Casteele ◽  
Maxim Gosseries ◽  
Jan G. Bourgois ◽  
Michael Ghijs ◽  
...  
Keyword(s):  
Perceived Exertion ◽  
Time Trial ◽  
Interval Training ◽  
Cycle Ergometer ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Fatigue Model ◽  
Stress Score ◽  
Training Stress ◽  
Training Impulse

Purpose: Numerous methods exist to quantify training load (TL). However, the relationship with performance is not fully understood. Therefore the purpose of this study was to investigate the influence of the existing TL quantification methods on performance modeling and the outcome parameters of the fitness-fatigue model. Methods: During a period of 8 weeks, 9 subjects performed 3 interval training sessions per week. Performance was monitored weekly by means of a 3-km time trial on a cycle ergometer. After this training period, subjects stopped training for 3 weeks but still performed a weekly time trial. For all training sessions, Banister training impulse (TRIMP), Lucia TRIMP, Edwards TRIMP, training stress score, and session rating of perceived exertion were calculated. The fitness-fatigue model was fitted for all subjects and for all TL methods. Results: The error in relating TL to performance was similar for all methods (Banister TRIMP: 618 [422], Lucia TRIMP: 625 [436], Edwards TRIMP: 643 [465], training stress score: 639 [448], session rating of perceived exertion: 558 [395], and kilojoules: 596 [505]). However, the TL methods evolved differently over time, which was reflected in the differences between the methods in the calculation of the day before performance on which training has the biggest positive influence (range of 19.6 d). Conclusions: The authors concluded that TL methods cannot be used interchangeably because they evolve differently.

Factors Affecting Perception of Effort (Session Rating of Perceived Exertion) During Rugby League Training

2013 ◽  
Vol 8 (1) ◽  
pp. 62-69 ◽  
Author(s):  
Thomas W.J. Lovell ◽  
Anita C. Sirotic ◽  
Franco M. Impellizzeri ◽  
Aaron J. Coutts
Keyword(s):  
Exercise Intensity ◽  
Perceived Exertion ◽  
Rugby League ◽  
Rating Of Perceived Exertion ◽  
Stepwise Multiple Regression ◽  
Training Intensity ◽  
Intensity Measures ◽  
Positioning Systems ◽  
Body Load ◽  
Training Impulse

Purpose:The purpose of this study was to examine the validity of session rating of perceived exertion (sRPE) for monitoring training intensity in rugby league.Methods:Thirty-two professional rugby league players participated in this study. Training-load (TL) data were collected during an entire season and assessed via microtechnology (heart-rate [HR] monitors, global positioning systems [GPS], and accelerometers) and sRPE. Within-individual correlation analysis was used to determine relationships between sRPE and various other measures of training intensity and load. Stepwise multiple regressions were used to determine a predictive equation to estimate sRPE during rugby league training.Results:There were significant within-individual correlations between sRPE and various other internal and external measures of intensity and load. The stepwise multiple-regression analysis also revealed that 62.4% of the adjusted variance in sRPE-TL could be explained by TL measures of distance, impacts, body load, and training impulse (y = 37.21 + 0.93 distance − 0.39 impacts + 0.18 body load + 0.03 training impulse). Furthermore, 35.2% of the adjusted variance in sRPE could be explained by exercise-intensity measures of percentage of peak HR (%HRpeak), impacts/min, m/min, and body load/min (y = −0.01 + 0.37%HRpeak + 0.10 impacts/min + 0.17 m/min + 0.09 body load/min).Conclusion:A combination of internal and external TL factors predicts sRPE in rugby league training better than any individual measures alone. These findings provide new evidence to support the use of sRPE as a global measure of exercise intensity in rugby league training.

Heart Rate-based Lactate Minimum Test in Running and Cycling

2021 ◽  
Author(s):  
Claudio Perret ◽  
Kathrin Hartmann
Keyword(s):  
Heart Rate ◽  
Steady State ◽  
Oxygen Uptake ◽  
Exercise Intensity ◽  
Exercise Test ◽  
Power Output ◽  
Perceived Exertion ◽  
Rating Of Perceived Exertion ◽  
Maximal Lactate Steady State ◽  
Lactate Minimum

AbstractThe heart rate-based lactate minimum test is a highly reproducible exercise test. However, the relation between lactate minimum determined by this test and maximal lactate steady state in running and cycling is still unclear. Twelve endurance-trained men performed this test in running and cycling. Exercise intensity at maximal lactate steady state was determined by performing several constant heart rate endurance tests for both exercise modes. Heart rate, power output, lactate concentration, oxygen uptake and rating of perceived exertion at lactate minimum, maximal lactate steady state and maximal performance were analysed. All parameters were significantly higher at maximal lactate steady state compared to lactate minimum for running and cycling. Significant correlations (p<0.05) between maximal lactate steady state and lactate minimum data were found. Peak heart rate and peak oxygen uptake were significantly higher for running versus cycling. Nevertheless, the exercise mode had no influence on relative (in percentage of maximal values) heart rate at lactate minimum (p=0.099) in contrast to relative power output (p=0.002). In conclusion, all measured parameters at lactate minimum were significantly lower but highly correlated with values at maximal lactate steady state in running and cycling, which allows to roughly estimate exercise intensity at maximal lactate steady state with one single exercise test.

A Systematic Review of Submaximal Cycle Tests to Predict, Monitor, and Optimize Cycling Performance

2016 ◽  
Vol 11 (6) ◽  
pp. 707-714 ◽  
Author(s):  
Benoit Capostagno ◽  
Michael I. Lambert ◽  
Robert P. Lamberts
Keyword(s):  
Heart Rate ◽  
Power Output ◽  
Perceived Exertion ◽  
Heart Rate Recovery ◽  
Mechanical Efficiency ◽  
Cycling Performance ◽  
Rating Of Perceived Exertion ◽  
Time To Exhaustion ◽  
Gross Mechanical Efficiency ◽  
Multiple Variables

Finding the optimal balance between high training loads and recovery is a constant challenge for cyclists and their coaches. Monitoring improvements in performance and levels of fatigue is recommended to correctly adjust training to ensure optimal adaptation. However, many performance tests require a maximal or exhaustive effort, which reduces their real-world application. The purpose of this review was to investigate the development and use of submaximal cycling tests that can be used to predict and monitor cycling performance and training status. Twelve studies met the inclusion criteria, and 3 separate submaximal cycling tests were identified from within those 12. Submaximal variables including gross mechanical efficiency, oxygen uptake (VO2), heart rate, lactate, predicted time to exhaustion (pTE), rating of perceived exertion (RPE), power output, and heart-rate recovery (HRR) were the components of the 3 tests. pTE, submaximal power output, RPE, and HRR appear to have the most value for monitoring improvements in performance and indicate a state of fatigue. This literature review shows that several submaximal cycle tests have been developed over the last decade with the aim to predict, monitor, and optimize cycling performance. To be able to conduct a submaximal test on a regular basis, the test needs to be short in duration and as noninvasive as possible. In addition, a test should capture multiple variables and use multivariate analyses to interpret the submaximal outcomes correctly and alter training prescription if needed.

scholarly journals Objective and subjective measures of exercise intensity during thermo-neutral and hot yoga

2018 ◽  
Vol 43 (4) ◽  
pp. 397-402 ◽  
Author(s):  
Corinne N. Boyd ◽  
Stephanie M. Lannan ◽  
Micah N. Zuhl ◽  
Ricardo Mora-Rodriguez ◽  
Rachael K. Nelson
Keyword(s):  
Oxygen Consumption ◽  
Light Intensity ◽  
Exercise Intensity ◽  
Perceived Exertion ◽  
Maximal Oxygen Consumption ◽  
Rating Of Perceived Exertion ◽  
Moderate Intensity ◽  
Subjective Measures ◽  
Moderate Intensity Exercise ◽  
Constant Intensity

While hot yoga has gained enormous popularity in recent years, owing in part to increased environmental challenge associated with exercise in the heat, it is not clear whether hot yoga is more vigorous than thermo-neutral yoga. Therefore, the aim of this study was to determine objective and subjective measures of exercise intensity during constant intensity yoga in a hot and thermo-neutral environment. Using a randomized, crossover design, 14 participants completed 2 identical ∼20-min yoga sessions in a hot (35.3 ± 0.8 °C; humidity: 20.5% ± 1.4%) and thermo-neutral (22.1 ± 0.2 °C; humidity: 27.8% ± 1.6%) environment. Oxygen consumption and heart rate (HR) were recorded as objective measures (percentage of maximal oxygen consumption and percentage of maximal HR (%HRmax)) and rating of perceived exertion (RPE) was recorded as a subjective measure of exercise intensity. There was no difference in exercise intensity based on percentage of maximal oxygen consumption during hot versus thermo-neutral yoga (30.9% ± 2.3% vs. 30.5% ± 1.8%, p = 0.68). However, exercise intensity was significantly higher during hot versus thermo-neutral yoga based on %HRmax (67.0% ± 2.3% vs. 60.8% ± 1.9%, p = 0.01) and RPE (12 ± 1 vs. 11 ± 1, p = 0.04). According to established exercise intensities, hot yoga was classified as light-intensity exercise based on percentage of maximal oxygen consumption but moderate-intensity exercise based on %HRmax and RPE while thermo-neutral yoga was classified as light-intensity exercise based on percentage of maximal oxygen uptake, %HRmax, and RPE. Despite the added hemodynamic stress and perception that yoga is more strenuous in a hot environment, we observed similar oxygen consumption during hot versus thermo-neutral yoga, classifying both exercise modalities as light-intensity exercise.

Time Spent Near V˙O2max During Different Cycling Self-Paced Interval Training Protocols

2020 ◽  
pp. 1-7
Author(s):  
Cristiano Dall’ Agnol ◽  
Tiago Turnes ◽  
Ricardo Dantas De Lucas
Keyword(s):  
Power Output ◽  
Perceived Exertion ◽  
Recovery Period ◽  
Interval Training ◽  
Exercise Duration ◽  
Rating Of Perceived Exertion ◽  
Recovery Ratio ◽  
Active Recovery ◽  
Mean Power ◽  
Work Recovery

Purpose: Cyclists may increase exercise intensity by prolonging exercise duration and/or shortening the recovery period during self-paced interval training, which could impact the time spent near . Thus, the main objective of this study was to compare the time spent near during 4 different self-paced interval training sessions. Methods: After an incremental test, 11 cyclists (mean [SD]: age = 34.4 [6.2] y; ) performed in a randomized order 4 self-paced interval training sessions characterized by a work–recovery ratio of 4:1 or 2:1. Sessions comprised 4 repetitions of 4 minutes of cycling with 1 minute (4/1) or 2 minutes (4/2) of active recovery or 8 minutes of cycling with 2 minutes (8/2) or 4 minutes (8/4) of active recovery. Time spent at 90% to 94% (), ≥95% (), and 90% to 100% () was analyzed in absolute terms and relative to the total work duration. Power output, heart rate, blood lactate, and rating of perceived exertion were compared. Results: The 8/4 session provided higher absolute and than 8/2 (P = .015 and .029) and 4/1 (P = .002 and .047). The 4/2 protocol elicited higher relative (47.7% [26.9%]) and (23.5% [22.7%]) than 4/1 (P = .015 and .028) and 8/2 (P < .01). Session 4/2 (275 [23] W) elicited greater mean power output (P < .01) than 4/1 (261 [27] W), 8/4 (250 [25] W), and 8/2 (234 [23] W). Conclusions: Self-paced interval training composed of 4-minute and 8-minute work periods efficiently elicit , but protocols with a work–recovery ratio of 2:1 (ie, 4/2 and 8/4) could be prioritized to maximize .

Technical and Tactical Training Load in Professional Volleyball Players

2019 ◽  
Vol 14 (10) ◽  
pp. 1338-1343
Author(s):  
Thiago S. Duarte ◽  
Danilo L. Alves ◽  
Danilo R. Coimbra ◽  
Bernardo Miloski ◽  
João C. Bouzas Marins ◽  
...  
Keyword(s):  
Perceived Exertion ◽  
Training Load ◽  
Technical Training ◽  
Rating Of Perceived Exertion ◽  
Different Types ◽  
Volleyball Players ◽  
Tactical Training ◽  
Training Impulse ◽  
The Relationship ◽  
And Training

Purpose: To analyze the technical and tactical training load in professional volleyball players, using subjective internal training load (session rating of perceived exertion  [SRPE]) and objective internal training load (training impulse of the heart rate [HR]) and the relationship between them. Methods: The sample was composed of 15 male professional volleyball players. They were monitored during 37 training sessions that included both technical (n = 23) and tactical (n = 14) training. Technical and training load was calculated using SRPE and training impulse of the HR. Results: Significant correlations were found between the methods in tactical (r = .616) and technical training (r = −.414). Furthermore, it was noted that technical training occurs up to 80% of HRmax (zone 3) and tactical training between 70% and 90% of HRmax (zones 3–4). Conclusions: The training impulse of the HR method has proved to be effective for training-load control during tactical training. However, it was limited compared with technical training. Thus, the use of SRPE is presented as a more reliable method in the different types of technical training in volleyball.

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