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Stephen W. Garland and Greg Atkinson

Purpose:

To assess the effect of sample site (earlobe vs toe) and incremental exercise protocol (continuous vs discontinuous) on training zone prescription in rowing.

Methods:

Twenty-six rowers performed two incremental exercise tests on an ergometer: (1) a five-step discontinuous test with 4-min stages and 30-W increment, with blood samples taken from the earlobe and toe at the start of the 1-min break between steps; (2) a continuous test, with 2-min stages and 30-W increment, with blood samples taken from the right first toe at the end of each stage. Blood was analyzed for lactate concentration.

Results:

At a lactate concentration of 2 mmol·L−1, the mean (95% CI) power output was 8.1 (± 15.4) W greater for the continuous protocol, the random error between the methods (1.96 × SD of differences) was ± 58.8 W, and there was no evidence of any relationship between power output and error between methods. At a lactate concentration of 4 mmol·L−1, the mean (95% CI) power output was 24.2 (± 17.0) W greater for the continuous protocol, and the random error was ± 64.8 W. At 4 mmol·L−1, systematic bias between methods increased with high power outputs.

Conclusions:

The continuous protocol with toe sampling led to higher power outputs for a given lactate concentration compared with the discontinuous protocol with earlobe sampling. This was partly due to the choice of sample site and largely due to the choice of protocol. This bias, and also random variability, makes direct comparison of these tests inappropriate.

Open access

Robin T. Thorpe, Greg Atkinson, Barry Drust and Warren Gregson

The increase in competition demands in elite team sports over recent years has prompted much attention from researchers and practitioners to the monitoring of adaptation and fatigue in athletes. Monitoring fatigue and gaining an understanding of athlete status may also provide insights and beneficial information pertaining to player availability, injury, and illness risk. Traditional methods used to quantify recovery and fatigue in team sports, such as maximal physical-performance assessments, may not be feasible to detect variations in fatigue status throughout competitive periods. Faster, simpler, and nonexhaustive tests such as athlete self-report measures, autonomic nervous system response via heart-rate-derived indices, and to a lesser extent, jump protocols may serve as promising tools to quantify and establish fatigue status in elite team-sport athletes. The robust rationalization and precise detection of a meaningful fluctuation in these measures are of paramount importance for practitioners working alongside athletes and coaches on a daily basis. There are various methods for arriving at a minimal clinically important difference, but these have been rarely adopted by sport scientists and practitioners. The implementation of appropriate, reliable, and sensitive measures of fatigue can provide important information to key stakeholders in team-sport environments. Future research is required to investigate the sensitivity of these tools to fundamental indicators such as performance, injury, and illness.

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Robin T. Thorpe, Anthony J. Strudwick, Martin Buchheit, Greg Atkinson, Barry Drust and Warren Gregson

Purpose:

To quantify the mean daily changes in training and match load and any parallel changes in indicators of morningmeasured fatigue across in-season training weeks in elite soccer players.

Methods:

After each training session and match (TL), session ratings of perceived exertion (s-RPE) were recorded to calculate overall session load (RPE-TL) in 29 English Premier League players from the same team. Morning ratings of fatigue, sleep quality, and delayed-onset muscle soreness (DOMS), as well as submaximal exercise heart rate (HRex), postexercise heart-rate recovery (HRR%), and heart-rate variability (HRV) were recorded before match day and 1, 2, and 4 d postmatch. Data were collected for a median duration of 3 wk (range 1–13) and reduced to a typical weekly cycle including no midweek match and a weekend match day. Data were analyzed using withinsubject linear mixed models.

Results:

RPE-TL was approximately 600 arbitrary units (AU) (95% confidence interval 546–644) higher on match day than following day (P < .001). RPE-TL progressively decreased by »60 AU per day over the 3 days before a match (P < .05). Morning-measured fatigue, sleep quality, and DOMS tracked the changes in RPE-TL, being 35–40% worse on postmatch day vs prematch day (P < .001). Perceived fatigue, sleep quality, and DOMS improved by 17–26% from postmatch day to 3 d postmatch, with further smaller (7%–14%) improvements occurring between 4 d postmatch and prematch day (P < .01). There were no substantial or statistically significant changes in HRex, HRR%, or HRV over the weekly cycle (P > .05).

Conclusions:

Morning-measured ratings of fatigue, sleep quality, and DOMS are clearly more sensitive than HR-derived indices to the daily fluctuations in session load experienced by elite soccer players in a standard in-season week.

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Robin T. Thorpe, Anthony J. Strudwick, Martin Buchheit, Greg Atkinson, Barry Drust and Warren Gregson

Purpose:

To quantify the relationship between daily training load and a range of potential measures of fatigue in elite soccer players during an in-season competitive phase (17 d).

Methods:

Total high-intensity-running (THIR) distance, perceived ratings of wellness (fatigue, muscle soreness, sleep quality), countermovement-jump height (CMJ), postexercise heart-rate recovery (HRR), and heart-rate variability (Ln rMSSD) were analyzed during an in-season competitive period (17 d). General linear models were used to evaluate the influence of daily fluctuation in THIR distance on potential fatigue variables.

Results:

Fluctuations in fatigue (r = −.51, large, P < .001), Ln rMSSD (r = −.24, small, P = .04), and CMJ (r = .23, small, P = .04) were significantly correlated with fluctuations in THIR distance. Correlations between variability in muscle soreness, sleep quality, and HRR and THIR distance were negligible and not statistically significant.

Conclusions:

Perceived ratings of fatigue and Ln rMSSD were sensitive to daily fluctuations in THIR distance in a sample of elite soccer players. Therefore, these particular markers show promise as simple, noninvasive assessments of fatigue status in elite soccer players during a short in-season competitive phase.

Open access

Robin T. Thorpe, Anthony J. Strudwick, Martin Buchheit, Greg Atkinson, Barry Drust and Warren Gregson

Purpose:

To determine the sensitivity of a range of potential fatigue measures to daily training load accumulated over the previous 2, 3, and 4 d during a short in-season competitive period in elite senior soccer players (N = 10).

Methods:

Total highspeed-running distance, perceived ratings of wellness (fatigue, muscle soreness, sleep quality), countermovement-jump height (CMJ), submaximal heart rate (HRex), postexercise heart-rate recovery (HRR), and heart-rate variability (HRV: Ln rMSSD) were analyzed during an in-season competitive period (17 d). General linear models were used to evaluate the influence of 2-, 3-, and 4-d total high-speed-running-distance accumulation on fatigue measures.

Results:

Fluctuations in perceived ratings of fatigue were correlated with fluctuations in total high-speed-running-distance accumulation covered on the previous 2 d (r = –.31; small), 3 d (r = –.42; moderate), and 4 d (r = –.28; small) (P < .05). Changes in HRex (r = .28; small; P = .02) were correlated with changes in 4-d total high-speed-running-distance accumulation only. Correlations between variability in muscle soreness, sleep quality, CMJ, HRR%, and HRV and total high-speed-running distance were negligible and not statistically significant for all accumulation training loads.

Conclusions:

Perceived ratings of fatigue and HRex were sensitive to fluctuations in acute total high-speed-running-distance accumulation, although sensitivity was not systematically influenced by the number of previous days over which the training load was accumulated. The present findings indicate that the sensitivity of morning-measured fatigue variables to changes in training load is generally not improved when compared with training loads beyond the previous day’s training.

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Lee E.F. Graves, Nicola D. Ridgers, Karen Williams, Gareth Stratton, Greg Atkinson and Nigel T. Cable

Background:

Active video games (exergames) increase energy expenditure (EE) and physical activity (PA) compared with sedentary video gaming. The physiological cost and enjoyment of exergaming in adolescents, and young and older adults has not been documented, nor compared with aerobic exercise. This study compared the physiological cost and enjoyment of exergaming on Wii Fit with aerobic exercise in 3 populations.

Methods:

Cardiorespiratory and enjoyment measurements were compared in 14 adolescents, 15 young adults, and 13 older adults during handheld inactive video gaming, Wii Fit activities (yoga, muscle conditioning, balance, aerobics), and brisk treadmill walking and jogging.

Results:

For all groups EE and heart rate (HR) of Wii Fit activities were greater than handheld gaming (P < .001) but lower than treadmill exercise (P ≤ .001). Wii aerobics elicited moderate intensity activity in adolescents, young adults, and older adults with respective mean (SD) metabolic equivalents of 3.2 (0.7), 3.6 (0.8), and 3.2 (0.8). HR during Wii aerobics fell below the recommended intensity for maintaining cardiorespiratory fitness. Group enjoyment rating was greater for Wii balance and aerobics compared with treadmill walking and jogging (P ≤ .05).

Conclusions:

Wii Fit appears an enjoyable exergame for adolescents and adults, stimulating light-to-moderate intensity activity through the modification of typically sedentary leisure behavior.

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Lee E.F. Graves, Nicola D. Ridgers, Greg Atkinson and Gareth Stratton

Active video game interventions typically provide children a single game that may become unappealing. A peripheral device (jOG) encourages step-powered gaming on multiple games. This trial evaluated the effect of jOG on children’s objectively measured PA, body fat and self-reported behaviors. 42 of 58 eligible children (8–10 y) randomly assigned to an intervention (jOG) or control (CON) completed the trial. Intervention children received two jOG devices for home use. Analyses of covariance compared the intervention effect at 6 and 12 weeks from baseline. No differences were found between groups for counts per minute (CPM; primary outcome) at 6 and 12 weeks (p > .05). Active video gaming increased (adjusted change 0.95 (95% CI 0.25, 1.65) h·d−1, p<.01) and sedentary video gaming decreased (-0.34 (-1.24, 0.56) h·d−1, p > .05) at 6 weeks relative to CON. No body fat changes were observed between groups. Targeted changes in video game use did not positively affect PA. Larger trials are needed to verify the impact of active video games on children’s PA and health.