Heart-Rate Variability and Training-Intensity Distribution in Elite Rowers

2014 ◽  
Vol 9 (6) ◽  
pp. 1026-1032 ◽  
Author(s):  
Daniel J. Plews ◽  
Paul B. Laursen ◽  
Andrew E. Kilding ◽  
Martin Buchheit
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Intensity Distribution ◽  
Lactate Threshold ◽  
Training Intensity ◽  
Training Time ◽  
Low Intensity ◽  
Elite Rowers ◽  
And Training ◽  
Intensity Training

Purpose:Elite endurance athletes may train in a polarized fashion, such that their training-intensity distribution preserves autonomic balance. However, field data supporting this are limited.Methods:The authors examined the relationship between heart-rate variability and training-intensity distribution in 9 elite rowers during the 26-wk build-up to the 2012 Olympic Games (2 won gold and 2 won bronze medals). Weekly averaged log-transformed square root of the mean sum of the squared differences between R-R intervals (Ln rMSSD) was examined, with respect to changes in total training time (TTT) and training time below the first lactate threshold (>LT1), above the second lactate threshold (LT2), and between LT1 and LT2 (LT1–LT2).Results:After substantial increases in training time in a particular training zone or load, standardized changes in Ln rMSSD were +0.13 (unclear) for TTT, +0.20 (51% chance increase) for time >LT1, –0.02 (trivial) for time LT1–LT2, and –0.20 (53% chance decrease) for time >LT2. Correlations (±90% confidence limits) for Ln rMSSD were small vs TTT (r = .37 ± .80), moderate vs time >LT1 (r = .43 ± .10), unclear vs LT1–LT2 (r = .01 ± .17), and small vs >LT2 (r = –.22 ± .50).Conclusion:These data provide supportive rationale for the polarized model of training, showing that training phases with increased time spent at high intensity suppress parasympathetic activity, while low-intensity training preserves and increases it. As such, periodized low-intensity training may be beneficial for optimal training programming.

Training intensity distribution in young tennis players

2016 ◽  
Vol 11 (6) ◽  
pp. 880-886 ◽  
Author(s):  
Alexandre Moreira ◽  
Rodrigo V Gomes ◽  
Caroline D Capitani ◽  
Charles R Lopes ◽  
Audrei R Santos ◽  
...  
Keyword(s):  
Heart Rate ◽  
Intensity Distribution ◽  
Perceived Exertion ◽  
Rating Of Perceived Exertion ◽  
Moderate Intensity ◽  
Training Intensity ◽  
Match Play ◽  
Training Time ◽  
Tennis Players ◽  
Professional Tennis

The aim of this study was to describe the training intensity distribution of elite young tennis players, based on the session rating of perceived exertion and heart rate methods. Twelve professional tennis players participated in this study. Heart rate and session rating of perceived exertion were collected in 384 tennis training sessions, 23 simulated matches, and 17 official matches. The total training time spent in the heart rate zone-1 (52.00%) and zone-2 (37.10%) was greater than the time spent in zone-3 (10.90%) during the 5-week training period ( p < 0.05). Similarly, the total training time spent in the session rating of perceived exertion zone-1 (42.00%) and zone-2 (47.50%) was also greater than the time in zone-3 (10.50%) ( p < 0.05). The data of the present study suggest that the majority of the training sessions of these young tennis players were performed at low-to-moderate intensity zone and, therefore, under the intensity performed during actual tennis match play.

Perspectives and Determinants for Training-Intensity Distribution in Elite Endurance Athletes

2019 ◽  
Vol 14 (8) ◽  
pp. 1151-1156
Author(s):  
Jan G. Bourgois ◽  
Gil Bourgois ◽  
Jan Boone
Keyword(s):  
Intensity Distribution ◽  
High Intensity ◽  
Ventilatory Threshold ◽  
Important Determinant ◽  
Endurance Athletes ◽  
Training Intensity ◽  
High Intensity Training ◽  
Low Intensity ◽  
Intensity Training ◽  
Over Time

Training-intensity distribution (TID), or the intensity of training and its distribution over time, has been considered an important determinant of the outcome of a training program in elite endurance athletes. The polarized and pyramidal TID, both characterized by a high amount of low-intensity training (below the first lactate or ventilatory threshold), but with different contributions of threshold training (between the first and second lactate or ventilatory threshold) and high-intensity training (above the second lactate or ventilatory threshold), have been reported most frequently in elite endurance athletes. However, the choice between these 2 TIDs is not straightforward. This article describes the historical, evolutionary, and physiological perspectives of the success of the polarized and pyramidal TID and proposes determinants that should be taken into account when choosing the most appropriate TID.

scholarly journals From Heart-Rate Data to Training Quantification: A Comparison of 3 Methods of Training-Intensity Analysis

2014 ◽  
Vol 9 (1) ◽  
pp. 100-107 ◽  
Author(s):  
Øystein Sylta ◽  
Espen Tønnessen ◽  
Stephen Seiler
Keyword(s):  
Heart Rate ◽  
Altitude Training ◽  
Training Intensity ◽  
Heart Rate Data ◽  
Conversion Factors ◽  
Training Time ◽  
High Intensity Training ◽  
Analysis Methods ◽  
Simple Conversion ◽  
Intensity Training

Purpose:The authors directly compared 3 frequently used methods of heart-rate-based training-intensity-distribution (TID) quantification in a large sample of training sessions performed by elite endurance athletes.Methods:Twenty-nine elite cross-country skiers (16 male, 13 female; 25 ± 4 y; 70 ± 11 kg; 76 ± 7 mL · min−1 · kg−1 VO2max) conducted 570 training sessions during a ~14-d altitude-training camp. Three analysis methods were used: time in zone (TIZ), session goal (SG), and a hybrid session-goal/time-in-zone (SG/TIZ) approach. The proportion of training in zone 1, zone 2, and zone 3 was quantified using total training time or frequency of sessions, and simple conversion factors across different methods were calculated.Results:Comparing the TIZ and SG/TIZ methods, 96.1% and 95.5%, respectively, of total training time was spent in zone 1 (P < .001), with 2.9%/3.6% and 1.1%/0.8% in zones 2/3 (P < .001). Using SG, this corresponded to 86.6% zone 1 and 11.1%/2.4% zone 2/3 sessions. Estimated conversion factors from TIZ or SG/TIZ to SG and vice versa were 0.9/1.1, respectively, in the low-intensity training range (zone 1) and 3.0/0.33 in the high-intensity training range (zones 2 and 3).Conclusions:This study provides a direct comparison and practical conversion factors across studies employing different methods of TID quantification associated with the most common heart-rate-based analysis methods.

scholarly journals The integration of training and off-training activities substantially alters training volume and load analysis in elite rowers

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gunnar Treff ◽  
Robert Leppich ◽  
Kay Winkert ◽  
Jürgen M. Steinacker ◽  
Benjamin Mayer ◽  
...  
Keyword(s):  
Heart Rate ◽  
Intensity Distribution ◽  
Training Intensity ◽  
Individual Level ◽  
Rowing Ergometer ◽  
Elite Rowers ◽  
Training Activities ◽  
And Performance ◽  
Training Impulse ◽  
The Relationship

AbstractTraining studies in elite athletes traditionally focus on the relationship between scheduled training (TRAIN) and performance. Here, we added activities outside of scheduled training i.e., off-training (OFF) contributing to total training (TOTAL) to evaluate the contribution of OFF on performance. Eight elite rowers recorded OFF and TRAIN during waking hours for one season (30–45 weeks) with multisensory smartwatches. Changes in performance were assessed via rowing ergometer testing and maximum oxygen uptake ($${\dot{\text{V}}}$$ V ˙ O2max). Based on 1-Hz-sampling of heart rate data during TRAIN and OFF (> 60% maximum heart rate (HRmax), the volume, session count, intensity, training impulse (TRIMP), and training intensity distribution were calculated. OFF altered volume, TRIMP, and session count by 19 ± 13%, 13 ± 9%, and 41 ± 67% (p < 0.001). On an individual level, training intensity distribution changed in 3% of the valid weeks. Athletes exercised 31% of their weekly volume below 60% HRmax. Low to moderate intensities dominated during OFF with 87% (95% CI [79, 95]); however, in some weeks high-intensity activities > 89% HRmax during OFF amounted to 21 min·week−1 (95% CI [4, 45]). No effect of OFF on changes of performance surrogates was found (0.072 > p > 0.604). The integration of OFF substantially altered volume, TRIMP, and session count. However, no effect on performance was found.

scholarly journals Recovery behavior after matches for returning to training in volleyball athletes

2021 ◽  
Vol 38 (5) ◽  
pp. 343-349
Author(s):  
Ananda S. Cardoso ◽  
Guilherme P. Berriel ◽  
Pedro Schons ◽  
Rochelle R. Costa ◽  
Luiz Fernando M. Kruel
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Negative Correlation ◽  
Perceived Exertion ◽  
Recovery Period ◽  
Ratings Of Perceived Exertion ◽  
Significance Level ◽  
Recovery Behavior ◽  
Vertical Jumps ◽  
And Training

The aim of this research was to evaluate the behavior of vertical jumps performance in professional volleyball athletes during matches and training and their relationships with fatigue and recovery through heart rate variability (HRV), ratings of perceived exertion (RPE) and perceived recovery status (PRS). Nine male professional volleyball athletes participated in the study, with mean age: 25.66 ± 5.7 years, mean body mass: 97.81 ± 8.65 Kg and mean height: 200.94 ± 5.19 cm, with experience in national and international competitions. HRV and PRS were evaluated in the morning of matches and in the presentation for the first day of training after matches. RPE was collected immediately after matches and at the end of training days. Jumps performance was monitored during the matches and during the first days of training. The data was grouped by matches and training sessions. Significance level adopted was α ≤ 0.05. There were no alterations in HRV and PRS evaluated after matches and before training sessions, as well as in RPE after training. Jumps height was greater during the matches (p< 0.013) and there were no differences in the number of jumps. There was a positive correlation between the number of jumps during matches and PRS before matches (r= 0.336, p= 0.015) and a negative correlation between the number of jumps during training and pre-training PRS (r= -0.318, p= 0.002). We conclude that the recovery period proposed by the team proved to be sufficient for the athletes to maintain the same condition for returning to training. This information can assist physical trainers to prescribe training loads for the return to training.

Controlled 5-mo aerobic training improves heart rate but not heart rate variability or baroreflex sensitivity

2000 ◽  
Vol 89 (5) ◽  
pp. 1825-1829 ◽  
Author(s):  
Antti Loimaala ◽  
Heikki Huikuri ◽  
Pekka Oja ◽  
Matti Pasanen ◽  
Ilkka Vuori
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Exercise Training ◽  
High Intensity ◽  
Baroreflex Sensitivity ◽  
Aerobic Training ◽  
Control Group ◽  
Resting Heart Rate ◽  
Endurance Time ◽  
Low Intensity

Endurance-trained athletes have increased heart rate variability (HRV), but it is not known whether exercise training improves the HRV and baroreflex sensitivity (BRS) in sedentary persons. We compared the effects of low- and high-intensity endurance training on resting heart rate, HRV, and BRS. The maximal oxygen uptake and endurance time increased significantly in the high-intensity group compared with the control group. Heart rate did not change significantly in the low-intensity group but decreased significantly in the high-intensity group (−6 beats/min, 95% confidence interval; −10 to −1 beats/min, exercise vs. control). No significant changes occurred in either the time or frequency domain measures of HRV or BRS in either of the exercise groups. Exercise training was not able to modify the cardiac vagal outflow in sedentary, middle-aged persons.

scholarly journals Heart Rate Variability Responses to a Training Cycle in Female Youth Rowers

2020 ◽  
Vol 17 (22) ◽  
pp. 8391
Author(s):  
Rohan Edmonds ◽  
Julian Egan-Shuttler ◽  
Stephen J. Ives
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Perceived Exertion ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Cardiac Autonomic Function ◽  
Female Youth ◽  
Training Cycle ◽  
And Training

Heart rate variability (HRV) is a reputable estimate of cardiac autonomic function used across multiple athletic populations to document the cardiac autonomic responses to sport demands. However, there is a knowledge gap of HRV responses in female youth rowers. Thus, the purpose of this study was to measure HRV weekly, over a 15-week training period, covering pre-season and up to competition in youth female rowers, in order to understand the physiological response to long-term training and discern how fluctuations in HRV may relate to performance in this population. Measures of heart rate and heart rate variability were recorded before training each Friday over the monitoring period in seven athletes. Analysis of heart rate variability focused on time domain indices, the standard deviation of all normal to normal R–R wave intervals, and the root mean square of successive differences as markers of cardiac parasympathetic modulation. Training load was quantified by multiplying the rating of perceived exertion of the weeks training and training duration. A decrease was identified in cardiac parasympathetic modulation as the season progressed (Effect Size (Cohen’s d) = −0.34 to −0.8, weeks 6 and 11–15), despite no significant relationship between training load and heart rate variability. Factors outside of training may further compound the reduction in heart rate variability, with further monitoring of external stressors (e.g., school) in adolescent athletes.

scholarly journals The Current and Future Role of Heart Rate Variability for Assessing and Training Compassion

2017 ◽  
Vol 5 ◽  
Author(s):  
James N. Kirby ◽  
James R. Doty ◽  
Nicola Petrocchi ◽  
Paul Gilbert
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Future Role ◽  
And Training

BCIA Launches a Heart Rate Variability Biofeedback Certificate of Completion

Biofeedback ◽  
2013 ◽  
Vol 41 (1) ◽  
pp. 4-6 ◽  
Author(s):  
Fred Shaffer ◽  
Judy Crawford ◽  
Donald Moss
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Education And Training ◽  
Academic Rigor ◽  
Heart Rate Variability Biofeedback ◽  
International Alliance ◽  
Training Standards ◽  
And Training

The Biofeedback Certification International Alliance (BCIA) has developed a certificate of completion program to establish education and training standards for the exciting modality of heart rate variability (HRV) biofeedback. HRV represents the beat-to-beat changes in the intervals between consecutive heartbeats. A growing list of HRV biofeedback applications has earned ratings from possibly efficacious to probably efficacious. BCIA's expert-designed Blueprint of Knowledge and exam promise to increase the academic rigor of didactic HRV biofeedback courses and enhance the knowledge of providers who incorporate this modality into their practice.

Sign in / Sign up

Export Citation Format

Share Document