Active recovery effects by previously inactive muscles on 40-s exhaustive cycling

Optimizing active recovery strategies for finger flexor fatigue

Introduction

Active recovery (AR) is used during exercise training; however, it is unclear whether the AR should involve the whole body, only the upper extremities, or only the lower extremities when aiming to maintain localized upper body performance. Therefore, this study aimed to evaluate the impact of different AR strategies on repeated intermittent finger flexor performance leading to exhaustion.

Methods

A crossover trial involving a familiarization session and three laboratory visits, each including three exhaustive intermittent isometric tests at 60% of finger flexor maximal voluntary contraction separated by 22 min of randomly assigned AR: walking, intermittent hanging, and climbing.

Results

The impulse (Nꞏs) significantly decreased from the first to third trials after walking (-18.4%, P = 0.002, d = 0.78), climbing (-29.5%, P < 0.001, d = 1.48), and hanging (-27.2%, P < 0.001, d = 1.22). In the third trial, the impulse from the intermittent test was significantly higher after walking (21,253 ± 5,650 Nꞏs) than after hanging (18,618 ± 5,174 Nꞏs, P = 0.013, d = 0.49) and after climbing (18,508 ± 4,435 Nꞏs, P = 0.009, d = 0.54).

Conclusions

The results show that easy climbing or intermittent isolated forearm contractions should not be used as AR strategies to maintain subsequent performance in comparison to walking, indicating that using the same muscle group for AR should be avoided between exhaustive isometric contractions.

Moderate intensity active recovery improves performance in a second wingate test in cyclists

Background

The aim of the present study was to compare the effects of active (AR) vs. passive recovery (PR) between two Wingate Anaerobic Tests (WAnT) on power output, blood lactate (BLa) and oxygen consumption (VO₂) in a second WAnT.

Methods

Twelve well-trained cyclists underwent three experimental sessions. In the first session, they completed an incremental test for maximum oxygen consumption (V O₂max) and lactate threshold determination. In the second and third sessions, cyclists completed, in random order, two WAnT tests separated by 30-min recovery intervals, during which they performed an AR at 70% of the V O₂ at lactate threshold (V O₂LT) or a PR. The cardiorespiratory, metabolic, and mechanical responses in the two recovery conditions were compared.

Results

No differences were found in the VO₂-on kinetics between WAnT tests (p > 0.05). As expected, blood lactate kinetics showed a greater clearance (from the 7th to the 31st min, p < 0.001) during AR; however, no differences were found in peak BLa between conditions (p > 0.05). Mean and peak power, and total work were significantly higher in the second WAnT after AR (p < 0.001), while the power decline was also lower in this condition (p < 0.05).

Conclusion

The submaximal active recovery strategy used in the present study can induce an improvement in mechanical power and total work during a second WAnT. This suggests that AR of submaximal intensity can induce a post-activation performance enhancement when used during the recovery phase between maximal anaerobic efforts.

Is active recovery during cold water immersion better than active or passive recovery in thermoneutral water for postrecovery high-intensity sprint interval performance?

High-intensity exercise is impaired by increased esophageal temperature (T_es) above 38 °C and/or decreased muscle temperature. We compared the effects of three 30-min recovery strategies following a first set of three 30-s Wingate tests (set 1), on a similar postrecovery set of Wingate tests (set 2). Recovery conditions were passive recovery in thermoneutral (34 °C) water (Passive-TN) and active recovery (underwater cycling; ∼33% maximum power) in thermoneutral (Active-TN) or cold (15 °C) water (Active-C). T_es rose for all conditions by the end of set 1 (∼1.0 °C). After recovery, T_es returned to baseline in both Active-C and Passive-TN but remained elevated in Active-TN (p < 0.05). At the end of set 2, T_es was lower in Active-C (37.2 °C) than both Passive-TN (38.1 °C) and Active-TN (38.8 °C) (p < 0.05). From set 1 to 2 mean power did not change with Passive-TN (+0.2%), increased with Active-TN (+2.4%; p < 0.05), and decreased with Active-C (-3.2%; p < 0.05). Heart rate was similar between conditions throughout, except at end-recovery; it was lower in Passive-TN (92 beats·min^-1) than both exercise conditions (Active-TN, 126 beats·min^-1; Active-C, 116 beats·min^-1) (p < 0.05). Although Active-C significantly reduced T_es, the best postrecovery performance occurred with Active-TN. Novelty An initial set of 3 Wingates increased T_es to ∼38 °C. Thirty minutes of Active-C was well tolerated, and decreased T_es and blood lactate to baseline values, but decreased subsequent Wingate performance.

The Acute Effect of Concurrent Training on Running Performance Over 6 Days

PURPOSE

This study examined the effects of strength training on alternating days and endurance training on consecutive days on running performance for 6 days.

METHODS

Sixteen male and 8 female moderately trained individuals were evenly assigned into concurrent-training (CCT) and strength-training (ST) groups. The CCT group undertook strength training on alternating days combined with endurance training on consecutive days for 6 days. One week later, the CCT group conducted 3 consecutive days of endurance training only to determine whether fatigue would be induced with endurance training alone (CCT-Con). Endurance training was undertaken to induce endurance-training stimulus and to measure the cost of running (CR), rating of perceived exertion (RPE), and time to exhaustion (TTE). The ST group undertook 3 strength-training sessions on alternating days. Maximal voluntary contraction (MVC), rating of muscle soreness (RMS), and rating of muscle fatigue (RMF) were collected prior to each strength and endurance session.

RESULTS

For the CCT group, small differences were primarily found in CR and RPE (ES = 0.17-0.41). However, moderate-to-large reductions were found for TTE and MVC (ES = 0.65-2.00), whereas large increases in RMS and RMF (ES = 1.23-2.49) were found prior to each strength- and endurance-training session. Small differences were found in MVC for the ST group (ES = 0.11) and during CCT-Con for the CCT group (ES = 0.15-0.31).

CONCLUSION

Combining strength training on alternating days with endurance training on consecutive days impairs MVC and running performance at maximal effort and increases RMS and RMF over 6 days.

The effect of passive versus active recovery on power output over six repeated wingate sprints

PURPOSE

The aim of this study was to examine the effect of active versus passive recovery on 6 repeated Wingate tests (30-s all-out cycling sprints on a Velotron ergometer).

METHOD

Fifteen healthy participants aged 29 (SD = 8) years old (body mass index = 23 [3] kg/m(2)) participated in 3 sprint interval training sessions separated by 3 to 7 days between each session during a period of 1 month. The 1st visit was familiarization to 6 cycling sprints; the 2nd and 3rd visits involved a warm-up followed by 6 30-s cycling sprints. Each sprint was followed by 4 min of passive (resting still on the ergometer) or active recovery (pedaling at 1.1 W/kg). The same recovery was used within each visit, and recovery type was randomized between visits.

RESULTS

Active recovery resulted in a 0.6 W/kg lower peak power output in the second sprint (95% confidence interval [CI] [ - 0.2, - 0.8 W/kg], effect size = 0.50, p < .01) and a 0.4 W/kg greater average power output in the 5th and 6th sprints (95% CI [+0.2,+0.6 W/kg], effect size = 0.50, p < .01) compared with passive recovery. There was little difference between fatigue index, total work, or accumulated work between the 2 recovery conditions.

CONCLUSIONS

Passive recovery is beneficial when only 2 sprints are completed, whereas active recovery better maintains average power output compared with passive recovery when several sprints are performed sequentially (partial eta squared between conditions for multiple sprints = .38).

Guidelines to Classify Subject Groups in Sport-Science Research

Purpose:

The aim of this systematic literature review was to outline the various preexperimental maximal cycle-test protocols, terminology, and performance indicators currently used to classify subject groups in sportscience research and to construct a classification system for cycling-related research.

Methods:

A database of 130 subject-group descriptions contains information on preexperimental maximal cycle-protocol designs, terminology of the subject groups, biometrical and physiological data, cycling experience, and parameters. Kolmogorov-Smirnov test, 1-way ANOVA, post hoc Bonferroni (P < .05), and trend lines were calculated on height, body mass, relative and absolute maximal oxygen consumption (VO2max), and peak power output (PPO).

Results:

During preexperimental testing, an initial workload of 100 W and a workload increase of 25 W are most frequently used. Three-minute stages provide the most reliable and valid measures of endurance performance. After obtaining data on a subject group, researchers apply various terms to define the group. To solve this complexity, the authors introduced the neutral term performance levels 1 to 5, representing untrained, recreationally trained, trained, well-trained, and professional subject groups, respectively. The most cited parameter in literature to define subject groups is relative VO2max, and therefore no overlap between different performance levels may occur for this principal parameter. Another significant cycling parameter is the absolute PPO. The description of additional physiological information and current and past cycling data is advised.

Conclusion:

This review clearly shows the need to standardize the procedure for classifying subject groups. Recommendations are formulated concerning preexperimental testing, terminology, and performance indicators.

Effect of five different recovery methods on repeated cycle performance

PURPOSE

The aim of this study was to determine the influence of five different recovery strategies on repeated simulated time trial (TT) performance on a stationary cycle ergometer.

METHODS

Study 1 (n=8, male, club-level trained; V˙O2max: 56.9 ± 3.8 mL·min·kg) investigated the influence of passive rest with or without upper leg cooling (cooling device set at 0 °C or 10 °C) and compression after a first time trial (TT1) on a second time trial (TT2). Study 2 (n=9, male, club-level trained; V˙O2max: 53.3 ± 5.2 mL·min·kg) examined the influence of active recovery (AR) with or without upper leg cooling (cooling device set at 0 °C) applied after TT1 on TT2. Exhaustive exercise consisted of a cycle exercise at 55% Wmax lasting 30 min, immediately followed by a TT in which subjects had to complete a preset amount of work, equal to 30 min at 75% Wmax, as fast as possible. Immediately after TT1, a different recovery intervention was used for 20 min, and then subjects passively rested for 100 min before starting TT2. TT performance and physiological parameters were registered during the experiments.

RESULTS

In both studies, we observed that TT performance did not significantly change for either of the recovery interventions. During the cooling interventions, skin temperatures significantly decreased (P<0.05). AR + cooling + compression versus AR (study 2) clearly showed a significantly (P<0.05) faster decrease of the blood lactate concentration ([BLa]) during the recovery period after TT1 and a lower [BLa] during TT2.

CONCLUSIONS

Twenty minutes after cooling (device set at 0 °C or 10 °C), AR or the combined recovery method had comparable effects as passive recovery on the maintenance of TT2 performance 120 min after the first TT (TT1). After AR, however, subjects seemed to perform slightly better during TT2.