Nineteen young fencers, 14 males and 5 females, [mean ± SD: age: 15.8 ± 1.1 (14–17) years, height: 165.7 ± 8.1 cm, body mass: 57.3 ± 7.5 kg] participated in this study. The mean duration of fencing experience was 4.9 ± 3.7 years. The fencers in the present study consisted of ten foil fencers (five males and five females), four epee fencers (four males), and five sabre fencers (five males). FL and BL were determined as the leg on the weapon-held side and contralateral side, respectively. In 14 out of the 19 participants, the right leg was FL. A priori analysis of sample size for the present study was conducted using G*Power software (version 3.1, Heinrich Hein University, Dusseldorf, Germany). Referring to a previous study (Nystrom et al. 1990), power analysis using an effect size of 0.8 (large effect size), with an α error of 0.05, and a power of 0.80, revealed that the required sample size was 12 subjects for a comparison between limbs. Written informed consent was obtained from all participants with their guardians after providing them with a detailed explanation of the purposes, potential benefits, and risks associated with participation. This study was approved by the Research Ethics Committee of Chukyo University (2021-13).
Participants performed isometric contraction of unilateral knee extension for both right and left legs on a dynamometer (Takei Scientific Instruments Co., Ltd., Niigata, Japan). Based on the force measured by a force transducer (LU-100KSE; Kyowa Electronic Instruments, Tokyo, Japan) fixed at the distal part of the shank segment and the distance between the transducer and estimated knee joint center as the moment arm, knee joint extension torque was calculated. Maximal voluntary contraction (MVC) and submaximal contractions with the knee/hip angle at 90° were measured following a warm-up session. Two MVCs were performed with a 2-min rest interval between them for right and left legs, respectively. An MVC trial included a gradual increase in the knee extension force to maximum effort in 2–3 s, and the plateau phase at maximum effort was maintained for 2–3 s with a verbal count given at 1-s intervals. Force signal is detected by force amplifier (TSA-110, Takei Scientific Instruments Co., Ltd., Niigata, Japan) with 190 Hz of sampling rate. Peak force measured in this amplifier system during MVC trial was determined as MVC force.
Three different ramp contractions were applied as submaximal contraction. Individual ramp contractions consisted of a 15, 17, and 14-s increasing ramp phase from the baseline to 30, 50, and 70% of MVC force levels with an approximately 2, 3, and 5% of MVC/s rate of force increase and 15, 10, and 5-s sustained holding phase at 30, 50, and 70% of MVC force levels, respectively. Participants were provided with visual feedback of target and performed force via a monitor. One successful trial was used for further analyses for each force level. Thus, participants performed at least one trial for 30, 50, and 70% of MVC force levels. If the exerted force was not correctly traced the target force line, additional trial was given for each contraction level. During ramp contractions, high-density surface electromyography (HDsEMG) signals were recorded from the vastus lateralis (VL) muscle using a semi-disposable adhesive grid of 64 electrodes (13 rows and 5 columns with one missing electrode) with a 1-mm diameter and 8-mm inter-electrode distance (GR08MM1305, OT Bioelectronica, Torino, Italy). The electrode grids were placed at the midpoint of the line between the head of the greater trochanter and upper lateral edge of the patella, and the long side of grids was aligned along the reference line (Fig. 1). A wet electrode strap (WS2, OT Bioelectronica, Torino, Italy) was placed at the knee. Monopolar surface EMG signals were recorded with a band-pass filter (10–500 Hz), amplified by a factor of 256, sampled at 2000 Hz, and converted to digital form by a 16-bit analog-to-digital converter (Sessantaquattro, OT Bioelectronica, Torino, Italy). The signal from the force transducer of the dynamometer was also recorded and synchronized with this analog-to-digital converter.
During the preparation for attaching HDsEMG electrodes, muscle thickness (MT) of the VL muscle was measured using an ultrasound device b-mode (iViz air, FUJIFILM Medical Co., Ltd.). We instructed participants to sit on a chair with the knee/hip angle at 90° during the measurement with their legs relaxed. The ultrasound probe (10–5 MHz) was placed on the skin at the center of the HDsEMG electrode grid. We took two ultrasound images from a side of legs in each participant. From a longitudinal image of ultrasonography, the distance between the superficial and deep aponeurosis of VL was measured as the muscle thickness by imaging software (ImageJ; National Institute of Health) (Watanabe et al. 2018a, b) (Fig. 1). The averaged values of muscle thickness of VL from two images measured in a leg from a participants were used for further analyses.
After the knee extension tasks, the participants performed unilateral vertical jump (UVJ) on two force platforms (Takei Scientific Instruments Co., Ltd., Niigata, Japan) to measure vertical forces of right and left legs separately. Vertical force was sampled at 1000 Hz by an A-D converter (Power Lab 16/35, AD Instruments, Melbourne, Australia). UVJ performance is useful for assessing dynamic leg strength like isokinetic force (Bishop et al. 2021; Menzel et al. 2013). Participants were instructed to push the ground vertically to jump as high as possible by one leg, and the depth of counter movement was freely chosen by each participant to adopt a comfortable posture following the trial for familiarization. Their right or left feet were placed on different platforms to measure vertical forces separately, and their hands were held at their waists to restrict arm movements during UVJ. Following familiarization and warm-up, two UVJs were performed for right or left legs, respectively. The impulse of the vertical force during the propulsive phase was calculated and used for further analysis.
The highest MVC of two trials was determined as MVC of right and left legs, respectively, and used for target forces of submaximal contractions.
During submaximal contractions, individual motor units were identified from the recorded monopolar surface EMG signals by the Convolution Kernel Compensation (CKC) technique using DEMUSE software (Holobar et al. 2009; Holobar and Zazula 2004, 2008; Merletti et al. 2008). The procedures for decomposition into individual motor units used in the present study were previously and extensively validated based on HDsEMG signals from various skeletal muscles, including the VL muscle (Farina et al. 2010; Gallego et al. 2015a, b; Holobar et al. 2009; Watanabe and Holobar 2021; Watanabe et al. 2016; Yavuz et al. 2015). Based on Holobar et al. (2014), the pulse-to-noise ratio (PNR) was used as an indicator of the motor unit identification accuracy, and only motor units with PNR > 30 dB (corresponding to an accuracy of motor unit firing identification > 90%) were employed for further analysis; all other motor units were discarded (Holobar et al. 2014). We used motor unit firing properties during the ramp contraction to 70% of MVC for further analyses. To detect the motor units recruited at lower force levels during the ramp contraction to 70% of MVC, motor units were detected using the MU filter estimated from surface EMG during ramp contractions to 30 and 50% of MVC with lower ramp rates to the EMG signals recorded during the ramp contraction to 70% of MVC, as described previously (Del Vecchio et al. 2019a, b; Frančič and Holobar 2021). The previously introduced criterion of PNR > 30 dB was also applied to motor unit tracking, ensuring an accuracy of motor unit firing identification > 90% during ramp contraction to 70% of MVC. Median values of instantaneous firing rates when participants exerted forces between 50 and 60% of MVC during the ramp contraction to 70% of MVC were used for individual motor units and applied for further analysis. Motor unit firing behavior shows inter-individual characteristics at higher force levels in our previous study such as effects of aging and training intervention (Watanabe et al. 2016, 2021). On the other hand, motor unit firing rate rapidly declined during sustained phase at higher force level (Bigland-Ritchie et al. 1983; Garland and Gossen 2002). Also, some participants performed force production with large force fluctuation at over 60% of MVC during the ramp contraction to 70% of MVC. Therefore, we used this force level (50–60% of MVC) for analysis of motor unit firing properties. For the right or left leg of individual fencers, scatter plots of firing rates of individual motor units and recruitment thresholds were analyzed and linear regression was calculated between them (y = ax + b) (Fig. 1). Since the motor unit firing rate is strongly influenced by the recruitment threshold, and their association is negatively and linearly correlated (Parra et al. 2021), this effect should be accounted for. Therefore, the present study used the intercept of this equation (b) as an indicator of neural characteristics in individual fencers, i.e., the modified motor unit firing rate (mMUFR). The slope of this equation (a) was also used as indicator of motor unit firing properties (sMUFR).
To examine the effect of fencing experience, participants were divided into two groups: less [< 3 years (F3−)] or more [> 3 years (F3+)] than 3 years of fencing experience. As stated in Table 1, eight and ten participants were enrolled in the two groups, respectively.
All data are presented as the mean ± SD. We used non-parametric statistical tests in the present study based on the results of the Shapiro–Wilk test. MVC, MT, mMUFR, sMUFR, and UVJ were compared between FL and BL using the Wilcoxon signed rank test for all participants, F3−, and F3+. Using Spearman’s rank correlation coefficient, correlation analysis between FL and BL in MVC, MT, mMUFR, sMUFR, and UVJ was also performed in all participants, F3−, and F3+ groups, to assess their laterality. Age, height, body mass, and MVC, MT, mMUFR, sMUFR, and UVJ for FL and BL were compared between F3− and F3+ using the Wilcoxon signed rank test. Additionally, the effects of sex (male/female) and weapon types (foil/epee/sabre) were also analyzed following the above mentioned process for all participants, F3−, and F3+ groups. Effect size (ES) was calculated as correlation coefficient for each comparison (Tomczak and Tomczak 2014). Statistical analysis was performed using SPSS (version 21.0, SPSS, Tokyo, Japan), and the level of significance was set at 0.05.