The authors examined whether changes in heart-rate (HR) variability (HRV) could consistently track adaptation to training and race performance during a 32-wk competitive season. An elite male long-course triathlete recorded resting HR (RHR) each morning, and vagal-related indices of HRV (natural logarithm of the square root of mean squared differences of successive R−R intervals [ln rMSSD] and the ratio of ln rMSSD to R−R interval length [ln rMSSD:RR]) were assessed. Daily training load was quantified using a power meter and wrist-top GPS device. Trends in HRV indices and training load were examined by calculating standardized differences (ES). The following trends in week-to-week changes were consistently observed: (1) When the triathlete was coping with a training block, RHR decreased (ES −0.38 [90% confidence limits −0.05;−0.72]) and ln rMSSD increased (+0.36 [0.71;0.00]). (2) When the triathlete was not coping, RHR increased (+0.65 [1.29;0.00]) and ln rMSSD decreased (−0.60 [0.00;−1.20]). (3) Optimal competition performance was associated with moderate decreases in ln rMSSD (−0.86 [−0.76;−0.95]) and ln rMSSD:RR (−0.90 [−0.60;−1.20]) in the week before competition. (4) Suboptimal competition performance was associated with small decreases in ln rMSSD (−0.25 [−0.76;−0.95]) and trivial changes in ln rMSSD:RR (−0.04 [0.50;−0.57]) in the week before competition. To conclude, in this triathlete, a decrease in RHR concurrent with increased ln rMSSD compared with the previous week consistently appears indicative of positive training adaptation during a training block. A simultaneous reduction in ln rMSSD and ln rMSSD:RR during the final week preceding competition appears consistently indicative of optimal performance.
Search Results
You are looking at 1 - 7 of 7 items for
- Author: Jamie Stanley x
- Refine by Access: All Content x
Cardiac Parasympathetic Activity and Race Performance: An Elite Triathlete Case Study
Jamie Stanley, Shaun D’Auria, and Martin Buchheit
The Multidisciplinary Physical Preparation of a Multiple Paralympic Medal-Winning Cyclist
Dajo Sanders, David J. Spindler, and Jamie Stanley
Purpose: This case study aims to describe the multidisciplinary preparation of a multiple medal-winning Paralympic cyclist active in the C5 class. Specifically, it describes the 12-month preparation period toward the Tokyo 2020 Paralympic Games. Method: The participant (height 173 cm; weight approximately 63 kg) is active in the C5 para-cycling class (right arm impairment) and was preparing for the individual pursuit, road time trial, and mass-start race in the Tokyo Paralympic Games. The participant was supported by a multidisciplinary practitioner team focusing on multiple facets of athletic preparation. Morning resting heart rate (HR) and HR variability, as well as daily training data, were collected during the 12 months prior to Tokyo. Weekly and monthly trends in training, performance, and morning measures were analyzed. Training intensity zones were divided into zone 1 (<lactate threshold), zone 2(>lactate threshold, <critical power), and zone 3 (>critical power). Results: The participant won a silver (individual pursuit) and a bronze (time trial) medal at the Paralympic Games. Annual sums of volume and total work (in kilojoules) were, respectively, 1039 hours and 620,715 kJ. Analyzing all road sessions, 85% was spent in zone 1, 9% in zone 2, and 6% in zone 3. Physiological (eg, high training loads, hypoxic stimuli) and psychological stressors (ie, significant life events) were clearly reflected in morning HR and HR-variability responses. Conclusions: This case study demonstrates how a multidisciplinary team of specialist practitioners successfully prepared an elite Paralympic cyclist utilizing a holistic approach to training and health using data to manage allostatic load.
Differing Physiological Adaptations Induced by Dry and Humid Short-Term Heat Acclimation
Samuel T. Tebeck, Jonathan D. Buckley, Clint R. Bellenger, and Jamie Stanley
Purpose: To investigate the effect of a 5-day short-term heat acclimation (STHA) protocol in dry (43°C and 20% relative humidity) or humid (32°C and 80% relative humidity) environmental conditions on endurance cycling performance in temperate conditions (21°C). Methods: In a randomized, cross-over design, 11 cyclists completed each of the two 5-day blocks of STHA matched for heat index (44°C) and total exposure time (480 min), separated by 30 days. Pre- and post-STHA temperate endurance performance (4-min mean maximal power, lactate threshold 1 and 2) was assessed; in addition, a heat stress test was used to assess individual levels of heat adaptation. Results: Differences in endurance performance were unclear. Following dry STHA, gross mechanical efficiency was likely reduced (between-condition effect size dry vs humid −0.59; 90% confidence interval, −1.05 to −0.15), oxygen uptake was likely increased for a given workload (0.64 [0.14 to 1.07]), and energy expenditure likely increased (0.59 [0.17 to 1.03]). Plasma volume expansion at day 5 of acclimation was similar (within-condition outcome 4.6% [6.3%] and 5.3% [5.1%] dry and humid, respectively) but was retained for 3 to 4 days longer after the final humid STHA exposure (−0.2% [8.1%] and 4.5% [4.2%] dry and humid, respectively). Sweat rate was very likely increased during dry STHA (0.57 [0.25 to 0.89]) and possibly increased (0.18 [−0.15 to 0.50]) during humid STHA. Conclusion: STHA induced divergent adaptations between dry and humid conditions, but did not result in differences in temperate endurance performance.
Training for Elite Team-Pursuit Track Cyclists—Part I: A Profile of General Training Characteristics
Antony M.J. Stadnyk, Jamie Stanley, Tim Decker, and Katie M. Slattery
Purpose: To profile the training characteristics of an elite team pursuit cycling squad and assess variations in training intensity and load accumulation across the 36-week period prior to a world-record performance at the 2018 Commonwealth Games. Methods: Training data of 5 male track endurance cyclists (mean [SD]; age 21.9 [3.52] y; 4.4 [0.16] W·kg−1 at anaerobic threshold; 6.2 [0.28] W·kg−1 maximal oxygen uptake 68.7 [2.99] mL kg·min−1) were analyzed with weekly total training volume and heart rate, power output, and torque intensity distributions calculated with reference to their 3:49.804 min:s.ms performance requirements for a 4-km team pursuit. Results: Athletes completed 543 (37) h−1 of training across 436 (16) sessions. On-bike activities accounted for 69.9% of all training sessions, with participants cycling 11,246 (1139) km−1 in the training period of interest, whereas 12.7% of sessions involved gym/strength training. A pyramidal intensity distribution was evident with over 65% and 70% of training, respectively, performed at low-intensity zone heart rate and power output, whereas 5.3% and 7.7% of training was performed above anaerobic threshold. The athletes accumulated 4.4% of total training volume at, or above, their world-record team pursuit lead position torque (55 N·m). Conclusions: These data provide updated and novel insight to the power and torque demands and load accumulation contributing to world-record team pursuit performance. Although the observed pyramidal intensity distribution is common in endurance sports, the lack of shift toward a polarized intensity distribution during taper and competition peaking differs from previous research.
Training for Elite Team-Pursuit Track Cyclists—Part II: A Comparison of Preparation Phases in Consecutive World-Record-Breaking Seasons
Antony M.J. Stadnyk, Jamie Stanley, Tim Decker, and Katie M. Slattery
Purpose: To compare the training characteristics of an elite team pursuit cycling squad in the 3-month preparation phases prior to 2 successive world-record (WR) performances. Methods: Training data of 5 male track endurance cyclists (mean [SD]; age 23.4 [3.46] y; body mass 80.2 [2.74] kg; 4.5 [0.17] W·kg−1 at LT2; maximal aerobic power 6.2 [0.27] W·kg−1; maximal oxygen uptake 65.9 [2.89] mL·kg−1·min−1) were analyzed with weekly total training volume by training type and heart rate, power output, and torque intensity distributions calculated with reference to the respective WRs’ performance requirements. Results: Athletes completed 805 (82.81) and 725 (68.40) min·wk–1 of training, respectively, in each season. In the second season, there was a 32% increase in total track volume, although track sessions were shorter (ie, greater frequency) in the second season. A pyramidal intensity distribution was consistent across both seasons, with 81% of training, on average, performed below LT1 power output each week, whereas 6% of training was performed above LT2. Athletes accumulated greater volume above WR team pursuit lead power (2.4% vs 0.9%) and torque (6.2% vs 3.2%) in 2019. In one athlete, mean single-leg-press peak rate of force development was 71% and 46% higher at mid- and late-phases, respectively, during the preparation period. Conclusions: These findings provide novel insights into the common and contrasting methods contributing to successive WR team pursuit performances. Greater accumulation of volume above race-specific power and torque (eg, team pursuit lead), as well as improved neuromuscular force-generating capacities, may be worthy of investigation for implementation in training programs.
The Effect of Training at 2100-m Altitude on Running Speed and Session Rating of Perceived Exertion at Different Intensities in Elite Middle-Distance Runners
Avish P. Sharma, Philo U. Saunders, Laura A. Garvican-Lewis, Brad Clark, Jamie Stanley, Eileen Y. Robertson, and Kevin G. Thompson
Purpose:
To determine the effect of training at 2100-m natural altitude on running speed (RS) during training sessions over a range of intensities relevant to middle-distance running performance.
Methods:
In an observational study, 19 elite middle-distance runners (mean ± SD age 25 ± 5 y, VO2max, 71 ± 5 mL · kg–1 · min–1) completed either 4–6 wk of sea-level training (CON, n = 7) or a 4- to 5-wk natural altitude-training camp living at 2100 m and training at 1400–2700 m (ALT, n = 12) after a period of sea-level training. Each training session was recorded on a GPS watch, and athletes also provided a score for session rating of perceived exertion (sRPE). Training sessions were grouped according to duration and intensity. RS (km/h) and sRPE from matched training sessions completed at sea level and 2100 m were compared within ALT, with sessions completed at sea level in CON describing normal variation.
Results:
In ALT, RS was reduced at altitude compared with sea level, with the greatest decrements observed during threshold- and VO2max-intensity sessions (5.8% and 3.6%, respectively). Velocity of low-intensity and race-pace sessions completed at a lower altitude (1400 m) and/or with additional recovery was maintained in ALT, though at a significantly greater sRPE (P = .04 and .05, respectively). There was no change in velocity or sRPE at any intensity in CON.
Conclusion:
RS in elite middle-distance athletes is adversely affected at 2100-m natural altitude, with levels of impairment dependent on the intensity of training. Maintenance of RS at certain intensities while training at altitude can result in a higher perceived exertion.
The Effects of Daily Cold-Water Recovery and Postexercise Hot-Water Immersion on Training-Load Tolerance During 5 Days of Heat-Based Training
David N. Borg, Ian B. Stewart, John O. Osborne, Christopher Drovandi, Joseph T. Costello, Jamie Stanley, and Geoffrey M. Minett
Purpose: To examine the effects of daily cold- and hot-water recovery on training load (TL) during 5 days of heat-based training. Methods: Eight men completed 5 days of cycle training for 60 minutes (50% peak power output) in 4 different conditions in a block counter-balanced-order design. Three conditions were completed in the heat (35°C) and 1 in a thermoneutral environment (24°C; CON). Each day after cycling, participants completed 20 minutes of seated rest (CON and heat training [HT]) or cold- (14°C; HTCWI) or hot-water (39°C; HTHWI) immersion. Heart rate, rectal temperature, and rating of perceived exertion (RPE) were collected during cycling. Session-RPE was collected 10 minutes after recovery for the determination of session-RPE TL. Data were analyzed using hierarchical regression in a Bayesian framework; Cohen d was calculated, and for session-RPE TL, the probability that d > 0.5 was also computed. Results: There was evidence that session-RPE TL was increased in HTCWI (d = 2.90) and HTHWI (d = 2.38) compared with HT. The probabilities that d > 0.5 were .99 and .96, respectively. The higher session-RPE TL observed in HTCWI coincided with a greater cardiovascular (d = 2.29) and thermoregulatory (d = 2.68) response during cycling than in HT. This result was not observed for HTHWI. Conclusion: These findings suggest that cold-water recovery may negatively affect TL during 5 days of heat-based training, hot-water recovery could increase session-RPE TL, and the session-RPE method can detect environmental temperature-mediated increases in TL in the context of this study.
