Heart rate responses during a 4-d cycle stage race

Palmer, G. S.; Hawley, John A.; Dennis, Steven C.; Noakes, Timothy D.

doi:10.1249/00005768-199410000-00016

Cited by 80 publications

(64 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These results are similar to prior research that found MHR was higher in two different field tests than on a laboratory treadmill test among a group of male youth soccer players, (Aziz, Tan, & Teh, 2005), as well as two prior studies that found lower MHR during laboratory testing than competitive environments among athletes from multiple sports (St Clair Gibson et al, 2000) and veteran cyclists. (Palmer et al, 1994) On the other hand, our findings differ from those of Metaxas (Metaxas, Koutlianos, Kouidi, & Deligiannis, 2005) who found no differences in MHR obtained between laboratory and field test in youth soccer players. Similarly, Boudet (Boudet et al, 2002) found that median MHR did not differ between laboratory and field testing conditions among competitive adult triathletes, although considerable intraindividual variability was noted between methods.…”

Section: Discussioncontrasting

confidence: 96%

Maximal heart rate differs between laboratory and field conditions among female athletes

Coutinho¹,

Watson²,

Brickson³

et al. 2017

jhse

View full text Add to dashboard Cite

The purpose of this study was to determine if maximal heart rate (MHR) varies between laboratory testing, field testing, training, competitive matches and an age predicted MHR equation among female collegiate soccer players. 21 female NCAA Division 1 soccer players had MHR determined during a maximal treadmill test (MHRGXT), a 20-meter shuttle run test (MHRFIELD), 4 weeks of early season training (MHRTRAIN), 5 competitive matches (MHRMATCH), and an age prediction equation (MHRPRED). Participants were excluded if they were injured during the data collection period or failed to obtain at least 2 out of 3 criteria during treadmill testing: 1) RER ≥ 1.1, 2) plateau in VO2, and 3) attainment of ≥90% of MHRPRED. MHR was compared across different methods by ANOVA and Spearman correlation coefficients were determined between the different methods. 15 athletes satisfied the inclusion criteria. MHRGXT (190 ± 3.1 bpm) was significantly lower than MHRFIELD (197.9 ± 7.0 bpm, p<0.001), MHRTRAIN (198.9 ± 5.3bpm, p<0.001), and MHRMATCH (196.8 ± 4.4bpm, p=0.004), but not MHRPRED (193.8 ± 0.7bpm, p=0.12). Significant correlations were found between MHRGXT and MHRFIELD (r=0.89, p<0.001), MHRTRAIN (r=0.822, p<0.001), and MHRMATCH (r=0.584, p=0.02). No differences were identified between MHRFIELD, MHRTRAIN, or MHRMATCH, but all three measures were significantly correlated (r=0.63 to 0.81). MHRPRED was not significantly correlated with any of the other methods (r=-0.216 to 0.137). MHR from laboratory testing was significantly lower than field testing, training, and Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation competition, although all 4 methods were highly

show abstract

Section: Discussioncontrasting

confidence: 96%

Maximal heart rate differs between laboratory and field conditions among female athletes

Coutinho¹,

Watson²,

Brickson³

et al. 2017

jhse

View full text Add to dashboard Cite

show abstract

“…Before any intervention, each cyclist performed three~150-minute simulated 100km time trials (TT 100 ) on his own bicycle attached to a Kingcycle 1 air-braked ergometer, as described by Palmer et al [134] Pre-trial TT 100 rides were separated by 4 to 7 days and were designed to introduce the cyclists to the test and ensure that their athletic performance was consistent. To simulate the variable power demands of road cycle racing, [134] TT 100 rides included 1km sprints after 10, 32, 52, 72 and 99km and 4km sprints after 20, 40, 60 and 80km. Schabort et al [135] showed that individual cyclists' (n = 8) coefficients of variation in three TT 100 performances were 1.7%, with a 95% confidence interval of 1.1 to 2.5%.…”

Section: Effect Of Reduced Training (Taper) In Endurance-trained Indimentioning

confidence: 99%

Training Techniques to Improve Endurance Exercise Performances

2002

Self Cite

View full text Add to dashboard Cite

In previously untrained individuals, endurance training improves peak oxygen uptake (V. O2peak), increases capillary density of working muscle, raises blood volume and decreases heart rate during exercise at the same absolute intensity. In contrast, sprint training has a greater effect on muscle glyco(geno)lytic capacity than on muscle mitochondrial content. Sprint training invariably raises the activity of one or more of the muscle glyco(geno)lytic or related enzymes and enhances sarcolemmal lactate transport capacity. Some groups have also reported that sprint training transforms muscle fibre types, but these data are conflicting and not supported by any consistent alteration in sarcoplasmic reticulum Ca 2+ ATPase activity or muscle physicochemical H + buffering capacity. While the adaptations to training have been studied extensively in previously sedentary individuals, far less is known about the responses to high-intensity interval training (HIT) in already highly trained athletes. Only one group has systematically studied the reported benefits of HIT before competition. They found that ≥6 HIT sessions, was sufficient to maximally increase peak work rate (Wpeak) values and simulated 40km time-trial (TT40) speeds of competitive cyclists by 4 to 5% and 3.0 to 3.5%, respectively. Maximum 3.0 to 3.5% improvements in TT40 cycle rides at 75 to 80% of Wpeak after HIT consisting of 4-to 5-minute rides at 80 to 85% of Wpeak supported the idea that athletes should train for competition at exercise intensities specific to their event. The optimum reduction or 'taper' in intense training to recover from exhaustive exercise before a competition is poorly understood. Most studies have shown that 20 to 80% single-step reductions in training volume over 1 to 4 weeks have little effect on exercise performance, and that it is more important to maintain training intensity than training volume. Progressive 30 to 75% reductions in pool training volume over 2 to 4 weeks have been shown to improve swimming performances by 2 to 3%. Equally rapid exponential tapers improved 5km running times by up to 6%. We found that a 50% single-step reduction in HIT at 70% of Wpeak produced peak ~6% improvements in simulated 100km time-trial performances after 2 weeks. It is possible that the optimum taper depends on the intensity of the athletes'preceding training and their need to recover from exhaustive exercise to compete. How the optimum LEADING ARTICLE

show abstract

“…5,8,9 Laboratory-and field-based research has observed a stochastic variation in power output and heart rate during exercise. Palmer et al 11 observed nonmonotonic variation in heart rate that was not related to changes in terrain during a 4-day cycling race, while Tucker et al 10 observed nonmonotonic oscillations of power output with multiple frequency peaks during a self-paced 20-km time trial. During marathon running, high variability in both heart rate and speed with reduced variability in the second half of the race due to fatigue has also been observed.…”

mentioning

confidence: 99%

Even Between-Lap Pacing Despite High Within-Lap Variation During Mountain Biking

Martin

Lambeth-Mansell

Azevedo

et al. 2012

International Journal of Sports Physiology and Performance

View full text Add to dashboard Cite

Purpose:Given the paucity of research on pacing strategies during competitive events, this study examined changes in dynamic high-resolution performance parameters to analyze pacing profiles during a multiple-lap mountain-bike race over variable terrain.Methods:A global-positioning-system (GPS) unit (Garmin, Edge 305, USA) recorded velocity (m/s), distance (m), elevation (m), and heart rate at 1 Hz from 6 mountain-bike riders (mean ± SD age = 27.2 ± 5.0 y, stature = 176.8 ± 8.1 cm, mass = 76.3 ± 11.7 kg, VO2max = 55.1 ± 6.0 mL · kg−1 . min−1) competing in a multilap race. Lap-by-lap (interlap) pacing was analyzed using a 1-way ANOVA for mean time and mean velocity. Velocity data were averaged every 100 m and plotted against race distance and elevation to observe the presence of intralap variation.Results:There was no significant difference in lap times (P = .99) or lap velocity (P = .65) across the 5 laps. Within each lap, a high degree of oscillation in velocity was observed, which broadly reflected changes in terrain, but high-resolution data demonstrated additional nonmonotonic variation not related to terrain.Conclusion:Participants adopted an even pace strategy across the 5 laps despite rapid adjustments in velocity during each lap. While topographical and technical variations of the course accounted for some of the variability in velocity, the additional rapid adjustments in velocity may be associated with dynamic regulation of self-paced exercise.

show abstract

Heart rate responses during a 4-d cycle stage race

Cited by 80 publications

References 0 publications

Maximal heart rate differs between laboratory and field conditions among female athletes

Maximal heart rate differs between laboratory and field conditions among female athletes

Training Techniques to Improve Endurance Exercise Performances

Even Between-Lap Pacing Despite High Within-Lap Variation During Mountain Biking

Contact Info

Product

Resources

About