Effects of concomitant high-intensity interval training and sprint interval training on exercise capacity and response to exercise- induced muscle damage in mountain bike cyclists with different training backgrounds

2021

IJERPH

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This study was undertaken to investigate the effect of two different concepts in a training program on muscle thickness and anaerobic power in trained cyclists. Twenty-six mountain bike cyclists participated in the study and were divided into an experimental group (E), which performed polarized training, comprising sprint interval training (SIT), high-intensity interval training (HIIT), and endurance training (ET), and a control group (C), which performed HIIT and ET. The experiment was conducted over the course of 9 weeks. Laboratory tests were performed immediately before and after the conducted experiment, including an ultrasound measurement of the quadriceps femoris muscle thickness and a sprint interval testing protocol (SITP). During the SITP, the cyclists performed 4 maximal repetitions, 30 s each, with a 90-s rest period between the repetitions. SITP was performed to measure maximal and mean anaerobic power. As a result of the applied training program, the muscle thickness decreased and the mean anaerobic power increased in the experimental group. By contrast, no significant changes were observed in the control group. In conclusion, a decrease in muscle thickness with a concomitant increase in mean anaerobic power resulting from the polarized training program is beneficial in mountain bike cycling.

Section: Discussionsupporting

confidence: 92%

The Effect of Polarized Training (SIT, HIIT, and ET) on Muscle Thickness and Anaerobic Power in Trained Cyclists

2021

IJERPH

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“…Our findings (Table 5) imply that baseline HRV (HF, LF, RMSSD, and SDNN) can be a factor that determines the strength and direction of the relationship between HIT av and HRV variables (HF av , RMSSD av , and SDNN av ). This information supplements our previous research in which we proved that the effects of periods of training intensification through the use of HIT and sprint interval training could be predicted by an analysis of the training volume in a previous training process [28,29], as well as peak pulmonary minute ventilation in incremental tests and the restitution RMSSD value after a moderate-intensity warm-up [28].…”

Section: Discussionsupporting

confidence: 86%

“…The test started with a 50 W load; every 3 min, the load was increased by 35 and 50 W (for women and men, respectively) until refusal due to exhaustion. If the participant was unable to exercise for the entire 3 min at the last test load, 0.19 and 0.28 W (for women and men, respectively) was subtracted from the obtained final maximal power for each missed second [ 4 , 28 , 29 ]. In this way, Pmax was calculated.…”

Section: Methodsmentioning

confidence: 99%

An Attempt to Predict Changes in Heart Rate Variability in the Training Intensification Process among Cyclists

Jastrzębska

2021

IJERPH

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Individual changes in resting heart rate variability (HRV) parameters were assessed in seven Polish cyclists during a training process consisting of: a six-week period (P1) of predominantly low- and moderate-intensity training (L-MIT) and a six-week period (P2) where the proportion of high-intensity interval training (HIT) increased. Daily recorded HRV parameters included high-frequency spectral power (HF), square root of the mean squared difference between successive normal-to-normal RR intervals (RMSSD), and standard deviation of normal-to-normal RR intervals (SDNN). In each training microcycle, the average values of HFav, RMSSDav, and SDNNav were calculated individually for each participant. In three cyclists, HF was higher in P2 compared to P1, whereas in one cyclist, HF was higher in P1 than in P2. Each of these four cyclists presented an individual correlation between the average daily duration HIT effort in training microcycles (HITav) and HFav. Cyclists with low baseline values of HRV parameters showed increased activity of the parasympathetic nervous system, while in the cyclist with high baseline values of HRV parameters, an opposite change was observed. In conclusion, changes in resting HRV parameters between period P1 and P2 can be individualised. In the investigated group, it was possible to predict how HRV would change as a result of training intensification on the basis of HRV baseline values.

“…Existing literature has noted that the difficult terrain conditions of MTB can elicit significant eccentric muscle contractions for shock attenuation and handling particularly during downhill sections [2-4] and may compound energy expenditure even when little to no pedaling is required [4]. This type of varied and prolonged muscle action including maximal bouts during uphill climbs can severely stress skeletal muscle [8], and cause structural damage within the muscle fiber [9], which had previously been confirmed in MTB cyclists [10]. The varied static, eccentric and concentric phases of MTB [4] can be compared with the principally concentric muscle action that characterizes road cycling [11].…”

Section: Introductionmentioning

confidence: 97%

“…Research has found creatine kinase (CK) activity and myoglobin (MB) concentration to serve as useful markers of acute muscle damage and be correlated with training status [8]. These biomarkers of muscle status are particularly attractive as previous studies have suggested that they can also be used to predict cycling performance [10].…”

Section: Introductionmentioning

confidence: 99%

Relationships between acute race-induced changes in creatine kinase activity and blood plasma myoglobin concentration and race performance in mountain bike and road cyclists

Borkowski

2021

Preprint

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The aim of this study was to determine if the changes in plasma creatine kinase (CK) activity and myoglobin (MB) concentrations as markers of muscle damage differ between competitive road (n = 14) and mountain bike (n = 11) cyclists and if these biochemical markers show a relationship with real-world race performance. CK and MB were measured from blood samples collected 2 hours before race start and 1 hour after race completion and the change in pre- and post-race difference was calculated (ΔCK and ΔMB). An incremental exercise test was used to determine maximal oxygen uptake, maximal aerobic power, and power output at the second ventilatory threshold. Post-race CK and MB increased in the whole group of cyclists. Although the magnitude of change in CK was similar in both road and mountain bike cyclists, only the increase in road cyclists was significant. MB significantly increased only in mountain bike cyclists. Multiple regression analysis revealed a significant association between both road and mountain bike race performance and ΔCK and ΔMB. The other significant predictors for mountain bike race performance were maximal aerobic power (W?kg-1) and power output at the second ventilatory threshold (W?kg-1) and for road race performance both maximal oxygen uptake (l?min-1) and power output at the second ventilatory threshold (W). In conclusion, mountain bike racing was associated with an increase in MB whereas road racing with an increase in CK, with the post-race changes in CK and MB related to race performance as high ΔCK and low ΔMB were obtained by better-performing cyclists.