How Much Energy Do E'Athletes Use during Gameplay? Quantifying Energy Expenditure and Heart Rate Variability Within E'Athletes.

BACKGROUND: Research into esports suggests that e'athletes experience physiological stressors and demands during competition and training. The physiological demands of esports are poorly understood and need to be investigated further to inform future training guidelines, optimise performance outcomes, and manage e'athlete wellbeing. This research aimed to quantify the metabolic rate of esports gameplay and compare this outcome with heart rate variability within expert e'athletes. RESULTS: Thirteen healthy male participants ranked within the top 10% of their respective esports title participated in the study (age = 20.7 ± 2.69 years; BMI = 24.6 ± 5.89 kg·m- 2). Expired gas analysis indirect calorimetry measured gas exchange during rest and gaming. Compared to resting conditions, competitive esports gameplay significantly increased median energy expenditure (1.28 (IQR 1.16-1.49) kcal·min- 1 vs. 1.45 (IQR 1.20-1.77) kcal·min- 1, p = .02), oxygen consumption (0.27 (IQR 0.24-0.30) L·min- 1 vs. 0.29 (IQR 0.24-0.35) L·min- 1, p = .02) and carbon dioxide production (0.20 (IQR 0.19-0.27) L·min- 1vs. 0.27 (IQR 0.24-0.33) L·min- 1, p = .01). Competitive gameplay also resulted in a significant increase in heart rate (84.5 (IQR 74.1-96.1) bpm vs. 87.1 (IQR 80.3-104) bpm, p = .01) and decrease in R-R interval's (710 (IQR 624-810) ms vs. 689 (IQR 579-747) ms, p = .02) when compared to rest. However, there were no significant differences in time or frequency measures of heart rate variability. CONCLUSIONS: The data reveal increased physiological responses to metabolic rate, energy expenditure and cardiovascular function to esports game play within expert e'athletes. Further physiological research into the physical demands on e'athletes, the influence of different training programs to esport performance, and the added multivariate determinants to elite level esport performance are warranted.

Physical Activity and Self-Determination towards Exercise among Esports Athletes.

BACKGROUND: Esports is competitive video gaming, performed within teams or individually, across multiple genres. Players are required to be sedentary for extended periods and require a high-level of cognitive skills for successful competitive performance. There are conflicting findings within the physical activity research in the esports industry. The aim of this research is to explore self-reported physical activity through accelerometer-assessed physical activity, to gain a better insight into the physical activity behaviours of international e'athletes. METHOD: Participants (n = 796) across multiple popular esports games, holding any in-game rank, competing at any level, were recruited. The survey consisted of demographic details, esports experience, the International Physical Activity Questionnaire-Long Form (IPAQ-LF), and Behavioural Regulations towards Exercise Questionnaire (BREQ-3). Within a convenience sample, local intervarsity e'athletes (n = 18) were recruited to wear a wrist-worn accelerometer to measure physical activity for 7-days and then complete the survey. Results from the accelerometers were compared to the survey results to explore physical activity reporting within this population. RESULTS: When comparing IPAQ-LF to accelerometer data, players significantly over-report moderate-to-vigorous physical activity and weekly MET-min- 1 (p = .018, r = .63 and p ≤ .001, r = .92). The BREQ-3 showed that e'athletes categorised as high physical activity displayed significantly higher levels of intrinsic motivation, when compared to players categorised as low and moderate physical activity. CONCLUSIONS: E'athletes significantly over report physical activity time when measured through the IPAQ-LF, suggesting previous surveys may overestimate physical activity and further research is needed. Given the exponential growth of the industry and the level of physical inactivity, esports may contribute to global physical inactivity levels.

Effects of Nutritional Interventions on Accuracy and Reaction Time with Relevance to Mental Fatigue in Sporting, Military, and Aerospace Populations: A Systematic Review and Meta-Analysis.

Background: Research in sport, military, and aerospace populations has shown that mental fatigue may impair cognitive performance. The effect of nutritional interventions that may mitigate such negative effects has been investigated. This systematic review and meta-analysis aimed to quantify the effects of nutritional interventions on cognitive domains often measured in mental fatigue research. Methods: A systematic search for articles was conducted using key terms relevant to mental fatigue in sport, military, and aerospace populations. Two reviewers screened 11,495 abstracts and 125 full texts. A meta-analysis was conducted whereby effect sizes were calculated using subgroups for nutritional intervention and cognitive domains. Results: Fourteen studies were included in the meta-analysis. The consumption of energy drinks was found to have a small positive effect on reaction time, whilst the use of beta-alanine, carbohydrate, and caffeine had no effect. Carbohydrate and caffeine use had no effect on accuracy. Conclusions: The results of this meta-analysis suggest that consuming energy drinks may improve reaction time. The lack of effect observed for other nutritional interventions is likely due to differences in the type, timing, dosage, and form of administration. More rigorous randomized controlled trials related to the effect of nutrition interventions before, during, and after induced mental fatigue are required.

Passive muscle stretching reduces estimates of persistent inward current strength in soleus motor units.

Prolonged (≥60 s) passive muscle stretching acutely reduces maximal force production at least partly through a suppression of efferent neural drive. The origin of this neural suppression has not been determined; however, some evidence suggests that reductions in the amplitude of persistent inward currents (PICs) in the motoneurons may be important. The aim of the present study was to determine whether acute passive (static) muscle stretching affects PIC strength in gastrocnemius medialis (GM) and soleus (SOL) motor units. We calculated the difference in instantaneous discharge rates at recruitment and de-recruitment (ΔF) for pairs of motor units in GM and SOL during triangular isometric plantar flexor contractions (20% maximum) both before and immediately after a 5 min control period and immediately after five 1 min passive plantar flexor stretches. After stretching, there was a significant reduction in SOL ΔF (-25.6%; 95% confidence interval, CI=-45.1% to -9.1%, P=0.002) but not GM ΔF These data suggest passive muscle stretching can reduce the intrinsic excitability, via PICs, of SOL motor units. These findings (1) suggest that PIC strength might be reduced after passive stretching, (2) are consistent with previously established post-stretch decreases in SOL but not GM EMG amplitude during contraction, and (3) indicate that reductions in PIC strength could underpin the stretch-induced force loss.

New Methods for Processing and Quantifying VO2 Kinetics to Steady State: VO2 Onset Kinetics.

Current methods of oxygen uptake (VO2) kinetics data handling may be too simplistic for the complex physiology involved in the underlying physiological processes. Therefore, the aim of this study was to quantify the VO2 kinetics to steady state across the full range of sub-ventilatory threshold work rates, with a particular focus on the VO2 onset kinetics. Ten healthy, moderately trained males participated in five bouts of cycling. Each bout involved 10 min at a percentage of the subject's ventilation threshold (30, 45, 60, 75, 90%) from unloaded cycling. The VO2 kinetics was quantified using the conventional mono-exponential time constant (tau, τ), as well as the new methods for VO2 onset kinetics. Compared to linear modeling, non-linear modeling caused a deterioration of goodness of fit (main effect, p < 0.001) across all exercise intensities. Remainder kinetics were also improved using a modified application of the mono-exponential model (main effect, p < 0.001). Interestingly, the slope from the linear regression of the onset kinetics data is similar across all subjects and absolute exercise intensities, and thereby independent of subject fitness and τ. This could indicate that there are no functional limitations between subjects during this onset phase, with limitations occurring for the latter transition to steady state. Finally, the continuing use of mono-exponential modeling could mask important underlying physiology of more instantaneous VO2 responses to steady state. Consequently, further research should be conducted on this new approach to VO2 onset kinetics.