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Ten youth male and highly trained futsal athletes aged 15.9 ± 1.2 years (body mass: 62.9 ± 8.8 kg, and body height: 169.8 ± 9.5 cm) volunteered to participate in this study and signed a written informed consent after information on benefits and risks of study participation were provided. Informed consent was obtained from all participants and their parent and/or legal guardian. The local ethical research committee approved this study (R.SSRI.REC.1400.1184).
A minimal sample size was calculated using an a priori statistical power tool (G∗Power, Version 3.1, University of Dusseldorf, Germany). The a priori power analysis was computed for our primary outcome (i.e., mean power [W]) with the following input parameters: assumed power of 0.80, alpha level of 0.05, medium effect size Cohen’s f = 0.52 [16]. The results of the power analysis indicate that 10 participants would be required to achieve significant group-by-time interactions.
To be eligible to participate in this study, individuals had to be (i) normal weighted as indicated by the body mass index (18–23 kg/m2), (ii) free of lower extremity injuries, and (iii) free of neuromuscular, cardiovascular, or mental illnesses [9, 10, 17]. Participants were diagnosed as post-pubertal by a physician using the Tanner and Whitehouse method and the stages of pubic hair development [18]. Habitual CAF consumption was determined by a questionnaire [19]. None of the participants consumed caffeine habitually. Daily caffeine consumption was less than 70 mg. Participants were excluded from the analysis if they did not have natural patterns of sleep (8-h/day on average), felt tired on the test day, and did not follow the dietary instructions 24 h before the test [17]. The standardized diet protocol did participants not allow to consume caffeinated beverages and foods such as coffee, cocoa, and dark chocolate [8]. In a randomized, double-blind, placebo-controlled study design, participants were scheduled to come in for two testing sessions, separated by 72 h [9]. Participants were instructed to ingest either caffeine (CAF, 6 mg/kg body mass) or placebo (PL, dextrose) supplements, which were concealed in opaque, unmarked containers. A trained laboratory expert provided the supplements to the athletes one hour before undergoing the Wingate test [8, 9].
The Wingate test was performed on a bicycle ergometer (Ergomedic 894E, Monark, Sweden). Participants were familiarized with the Wingate test procedures in a separate session prior to the actual test session. Before performing the Wingate test, participants warmed up for four minutes on a cycling ergometer at low intensity and 70–80 revolutions per minute (RPM), followed by dynamic stretching. After a three-minute rest period, the participant’s resistance on the ergometer was set at 7.5% of the body mass of the respective participant [9, 10]. Athletes were allowed to pedal for a few seconds until their pedaling speed reached 120 RPM, then the resistance was applied. Participants were verbally encouraged to pedal at maximum speed for 30 s. Peak power and mean power were the recorded anaerobic performance variables. The anaerobic performance variables and the fatigue index were calculated using Wingate software (Monark anaerobic test software, Sweden, 3.7.16) recorded during the 30 s Wingate test.
The Noraxon DTS wireless electromyography system (Noraxon DTS. USA) was used to detect myoelectric activity from the selected muscles during the Wingate test. To detect signals, a pair of Ag/AgCl electrodes (Model SKINTACT, Austria) with a diameter of 12 mm in dipole array was placed in the muscular belly of the selected muscles, including m. vastus medialis (VM), vastus lateralis (VL), rectus femoris (RF), gastrocnemius lateral head (GS) and biceps femoris (BF) of the dominant leg according to the European concerted action surface EMG for Non-Invasive Assessment of Muscles (SENIAM) [20]. The dominant leg was defined using the ball-kick test [21] the day before the first Wingate trial was performed. In the ball-kick test, players were kindly asked to kick a ball with moderate intensity and maximal accuracy through a set of cones placed 1 m apart and 10 m from the subject. The leg used to kick the ball was identified as the dominant leg [21]. Before surface electrode placement, the skin was shaved and cleaned with a pad soaked in 70% alcohol (Ethanol-C2H5OH) to reduce skin impedance. The signals were recorded at a sampling frequency of 1500 Hz, a gain of 500, CMR > 100 db, and a 10–500 Hz bandwidth filter to reduce electrical interference from external sources [22]. The EMG signal was processed with Noraxon software (version MR3 3.14.16). The EMG data detected during the 30-second Wingate test were divided into six 5-second epochs. The six epochs included data collected on the Wingate test at 0–5, 6–10, 11–15, 16–20, 21–25 and 26–30 s [9, 10, 23]. Normalized root mean square (RMS) was used to report the values of the EMG signal amplitude. The RMS data were normalized by the RMS values obtained during each muscle’s maximum voluntary isometric contraction (MVIC) [20]. Subjects performed two maximum voluntary isometric contractions for each muscle according to SENIAM recommendations (www.seniam.org) for five seconds with a one-minute break. An average of three seconds in the middle of the MVICs was used for normalization purposes [24].
The mean power frequency (MPF), the median power frequency (MDPF) and the WT were selected for frequency analysis. MPF and MDPF were calculated from the Eqs. 1 and 2.
$$ \rm{MPF}=\frac{{\int }_{{f}_{0}}^{{f}_{1}}f.PS\left(f\right)}{{\int }_{{f}_{0}}^{{f}_{1}}PS\left(f\right)}$$
(1)
where PS (f) is the EMG power spectrum and f0 and f1 stand for the surface electromyography bandwidth (f0 = lowest frequency and f1 = highest frequency of the bandwidth).
$$ \rm{MDPF}={\int }_{{f}_{0}}^{{f}_{median}}PS\left(f\right) df={\int }_{{f}_{median}}^{{f}_{1}}PS\left(f\right) df$$
(2)
where PS(f) is the EMG power spectrum and f0 and f1 stand for the surface electromyography bandwidth (f0 = lowest frequency and f1 = highest frequency of the bandwidth).
To calculate WT, we calculated one-dimensional wavelet decomposition with the type of Db4 mother wavelet of each window 5 s preprocessed signal with a sampling frequency = 1500 \( \frac{samples}{s}\)) and all the wavelet coefficients (approximate and detail coefficients) were extracted [15, 25, 26]. Thereafter, we reported the detailed coefficient of wavelet decomposition. The spectrum of the raw signal in each 5-second epoch of the 30-seconds Wingate test was normalized using related parameters, such as MPF, MDPF, and WT in the first epoch [9]. The calculations were performed using MATLAB software (2018a, The Mathworks Inc., Natick, MA, USA).
As noted, this study was conducted in a double-blinded, placebo-controlled, crossover design. Normal distribution of data was examined and confirmed using the Shapiro-Wilk test. The paired t-test was used to investigate the effects of caffeine ingestion on peak power, mean power, and the fatigue index. Furthermore, Cohen’s d effect sizes were used to highlight important pairwise differences, with values of 0.2, 0.5, and 0.8 corresponding to small, medium, and large effects, respectively [27]. The effect of caffeine on the parameters of the EMG signal was examined using a two-way (treatment [caffeine and placebo] × time [6-time epochs]) analysis of variance (ANOVA) with repeated measures. In case of significant treatment-by-time interaction effects, Bonferroni corrected post-hoc tests were computed. Statistical significance was accepted at p < 0.05. Statistical analysis was performed using SPSS software (version 25, IBM Corporation, Armonk, NY, USA).
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