Are There Sex Differences in Lower-Limb Biomechanics and Muscle Activation During Rope Jumping in Muay Thai Athletes?

x-related differences in lower-limb biomechanics and neuromuscular strategies during rope jumping remain underexplored, particularly in combat-sport athletes. This study investigated leg stiffness and muscle activation in ten female (22.8 0.8 years) and ten male (22.9 1.4 years) Muay Thai athletes. Participants performed rope skipping under three conditions: dominant leg, non-dominant leg, and double leg at 2.2 Hz. Ground reaction forces were recorded at 1000 Hz, center of mass displacement at 200 Hz, and electromyographic activity of the vastus lateralis, biceps femoris, tibialis anterior, and medial gastrocnemius at 3000 Hz. Vertical stiffness (Kvert) was calculated as the ratio of peak vertical force to displacement. Results showed no signi cant sex differences in peak ground reaction force (e.g., dominant leg: females 2.83 0.42 vs. males 3.22 0.57 kN; double leg: females 4.04 0.83 vs. males 4.35 0.73 kN;p> 0.05), vertical stiffness (females 17.02 3.66 vs. males 16.21 4.09 kN/m;p> 0.05), contact time (females 0.280 0.03 vs. males 0.275 0.05 s;p> 0.05), or ight time (females 0.205 0.03 vs. males0.245 0.05 s ; p> 0.05). In contrast, females exhibited signi cantly higher co-activation ratios during

males 3.22 0.57 kN; double leg: females 4.04 0.83 vs. males 4.35 0.73 kN;p> 0.05), vertical stiffness (females 17.02 3.66 vs. males 16.21 4.09 kN/m;p> 0.05), contact time (females 0.280 0.03 vs. males 0.275 0.05 s;p> 0.05), or ight time (females 0.205 0.03 vs. males0.245 0.05 s ; p> 0.05). In contrast, females exhibited signi cantly higher co-activation ratios during unilateral skipping, including BF/VL (0.76 0.18 vs. 0.63 0.10;p< 0.05) and TA/MG (0.38 0.11 vs. 0.29 0.07;p< 0.05), suggesting a neuromuscular strategy to enhance joint stability. These ndings highlight rope jumping as a practical drill that can promote neuromuscular control and stability in Muay Thai training. Keywords:Muay Thai; muscle activation; vertical leg stiffness; rope jumping 1. Introduction Leg stiffness (K leg) is an important factor in human movement research because it relates to both performance and injury risk [1,2]. Extremely low stiffness increases the chance of muscle damage, while excessively high stiffness raises the risk of bone injury [2,3]. K legis de ned as the ratio of maximal ground reaction force (MaxGRF) to the vertical displacement of the center of mass during stance. In simple terms, stiffness re ects the relationship between the force applied and the body's deformation. During running, hopping, and jumping, the lower limbs act like a spring system, where body mass is supported by leg stiffness [4]. Athletes with higher K legcan generally run faster and jump higher because they transfer energy more ef ciently. Sports2025,13, 410 https://doi.org/10.3390/sports13110410

Sports2025,13, 410 2 of 12 Previous studies have examined gender differences in stiffness and muscle activation. For example, Padua et al. (2005) reported higher quadriceps-to-hamstring co-activation ratios in females but no signi cant gender differences in stiffness at 3.0 Hz hopping [5]. Similarly, Hobara et al. (2012) found a positive relationship between passive ankle stiff- ness and leg stiffness in females, though not signi cantly different between sexes [6]. Brauner (2014)observed no difference in stiffness between dominant and non-dominant legs in unilateral hopping [7]. Furthermore, leg stiffness has been positively correlated with sprint velocity [6,8,9]. While these ndings provide important insights from general athletic populations, they do not capture the sport-speci c neuromuscular demands of Muay Thai. Rope jumping in Muay Thai athletes involves both repetitive unilateral kicking and bilateral footwork, creating a unique context to investigate whether established gender- related activation patterns extend to combat sports. This study therefore addresses a gap by examining rope skipping in a combat-sport population, providing new perspectives on neuromuscular control beyond what has been reported in general athletes. Ground contact time is another important factor: higher hopping frequency typically increases stiffness while reducing contact time [10,11]. Studies of drop jumps at different heights showed shorter contact times and higher stiffness with increasing jump height [12]. Hobara et al. (2015) compared younger and older participants and found similar spring- mass behavior across hopping frequencies, though fatigue protocols decreased stiffness due to reduced joint moment and muscle activation [13]. Other research has shown no clear effect of leg dominance, running speed, or sidedness on stiffness [14,15]. In particular, hopping frequencies around 2.2 Hz have been frequently adopted in previous studies to provide a stable and representative condition for assessing leg stiffness, as shown by Hobara et al. (2013), who examined stiffness at 1.5, 2.2, and 3.0 Hz and identi ed 2.2 Hz as a suitable reference point for evaluating bilateral differences [16]. In addition, muscle activation patterns differ with contact phases. Short contact time phases are associated with higher stiffness and greater activation of the gastrocnemius and soleus [17]. Training studies show that endurance runners

et al. (2013), who examined stiffness at 1.5, 2.2, and 3.0 Hz and identi ed 2.2 Hz as a suitable reference point for evaluating bilateral differences [16]. In addition, muscle activation patterns differ with contact phases. Short contact time phases are associated with higher stiffness and greater activation of the gastrocnemius and soleus [17]. Training studies show that endurance runners typically present lower stiffness than power-trained athletes, re ecting adaptations in neuromuscular control [18]. Jumping rope, or skipping, is a simple yet effective training method to improve tness, coordination, balance, and cardiovascular endurance. It is widely used in sports such as track and eld, boxing, basketball, and martial arts [19]. Rope jumping involves repetitive stretch-shortening cycle (SSC) actions of the lower limbs, similar to plyometric training [20]. Studies have compared energy expenditure, lactate responses, and cardiovascular adap- tations, showing rope skipping to be ef cient and bene cial [21–23]. Variations such as double-unders further enhance SSC demands and sprint performance [20]. Moreover, rope skipping improves neuromuscular coordination, with trained individuals displaying shorter EMG activation times compared to untrained groups [14]. Despite these ndings, research on leg stiffness during rope jumping is still limited, especially regarding gender differences. Most evidence comes from running, hopping, and drop jumps, leaving rope skipping underexplored. Therefore, the purpose of this study is to examine sex differences in leg stiffness and muscle activation during unilateral and bilateral rope jumping among Muay Thai athletes. This rationale is based on evidence that muscle mass and force production capacity may partly explain sex-related differences in stiffness and neuromuscular strategies, yet prior studies have not examined these mechanisms in the context of rope skipping. We hypothe- size that male athletes will demonstrate greater leg stiffness than female athletes, re ecting differences in muscle mass and force production. Furthermore, we expect dominant legs to show higher stiffness than non-dominant legs due to repeated kicking and loading patterns in training and competition. In terms of muscle activation, female athletes are anticipated

differences in muscle mass and force production. Furthermore, we expect dominant legs to show higher stiffness than non-dominant legs due to repeated kicking and loading patterns in training and competition. In terms of muscle activation, female athletes are anticipated

Sports2025,13, 410 3 of 12 to present higher quadriceps-to-hamstring co-activation ratios, whereas male athletes will exhibit greater gastrocnemius and soleus activation. The objective is therefore stated as a single, clearly de ned aim to address this gap, avoiding redundancy with other sections. 2. Materials and Methods 2.1. Participants A total of twenty Muay Thai athletes were recruited using purposeful sampling from the National Sports University (females,n= 10; age 22.80 0.78 yr, body weight 60.70 7.49 kg , height 161.60 7.93 cm; males,n= 10; age 22.90 1.37 yr, body weight 63.90 9.98 kg, height 172.30 3.46 cm). All participants had at least three years of Muay Thai training experience and practiced a minimum of four days per week. Inclusion criteria were: (1) a minimum of three years of Muay Thai training; (2)training at least four days per week; (3) no musculoskeletal injuries within the past three months; and (4) no history of serious lower-limb injuries or surgeries(e.g., ACL injury, fracture, patellar dislocation). Exclusion criteria were: (1) current injury or pain affecting performance; (2) history of neurological disorders;and (3) use of ergogenic aids or dietary supplements that could in uence rope skipping performance. Participants con rmed that they did not use any ergogenic aids or supplements during the study. Participant eligibility was con rmed using a purpose-designed questionnaire assessing training background and physical activity level. The study protocol was approved by the Human Ethics Committee, and written informed consent was obtained from all participants before the experiment. An a priori power analysis was conducted in G*Power 3.1 [24] for a mixed design with one between-subjects factor (sex: male vs. female) and one within-subjects factor (task: unilateral vs. bilateral rope jumping; 2 levels). The analysis assumed a medium effect size for the sex task interaction (f = 0.25), with = 0.05, power (1 ) = 0.80, correlation among repeated measures r = 0.50, and nonsphericity correction"= 1.0. Based on these parameters, the required total sample size was N = 18. Allowing for ~10% attrition, we targeted N = 20 (10 per sex), which was achieved. In the subsequent statistical analysis, both main effects

task interaction (f = 0.25), with = 0.05, power (1 ) = 0.80, correlation among repeated measures r = 0.50, and nonsphericity correction"= 1.0. Based on these parameters, the required total sample size was N = 18. Allowing for ~10% attrition, we targeted N = 20 (10 per sex), which was achieved. In the subsequent statistical analysis, both main effects and the sex task interaction were tested and reported accordingly. 2.2. Procedure Participants performed barefoot rope jumping on a force platform under three condi- tions: non-dominant leg (NDL), dominant leg (DL), and double-leg (DOL). The dominant leg was de ned as the preferred leg used to kick a ball, whereas the non-dominant leg was identi ed as the supporting leg. Each condition was performed at a controlled frequency of 2.2 Hz (132 jumps per minute), guided by a digital metronome to ensure consistent cadence. Each trial lasted 30 s, and the order of conditions was randomized across participants. A standardized 2 min passive rest interval was provided between conditions to minimize fatigue. This rest duration was adopted based on previous plyometric and jump perfor- mance studies, which demonstrated that a 2 min recovery period is suf cient to restore performance capacity and minimize carry-over fatigue between trials [25–27]. The frequency of 2.2 Hz was selected because previous studies have demonstrated that this cadence elicits stable spring–mass behavior and is widely used to evaluate leg stiffness during hopping tasks [13,16]. This frequency allows for reliable comparisons across conditions while minimizing variability in ground contact time and ight time. 2.3. Kinetic Data Collection and Analysis Kinetic data during rope jumping were collected using a force platform (AMTI, Inc., Newton, MA, USA) at a sampling frequency of 1000 Hz. Each trial lasted 30 s, and

Sports2025,13, 410 4 of 12 ve consecutive jumps (6th to 10th) were selected for analysis. The rst 1–4 s of each trial were excluded to avoid variability during the acceleration phase, and jumps after the 10th cycle were not analyzed to minimize potential fatigue effects. Therefore, the 6th–10th cycles were chosen to represent steady-state performance while controlling for both initial adaptation and later fatigue. Ground reaction force (GRF) recordings were used to determine ground contact time (tc), ight time (tf), and to compute leg stiffness (K leg) based on the spring–mass model. Leg stiffness was calculated using the spring–mass model [4]. Stiffness was de ned as the ratio of peak vertical ground reaction force to the vertical displacement of the center of mass (COM) between its lowest position at mid-stance and its highest position during ight [28]. Leg stiffness (K leg) was de ned in this study as the ratio of peak vertical ground reaction force to the vertical displacement of the center of mass (COM). For clarity, the term vertical stiffness (Kvert) is sometimes used in the literature with a similar de nition; however, in the present study we consistently use Kleg to denote leg stiffness derived from the spring–mass model. K leg= Fmax/Dy where Fmaxis the peak vertical ground reaction force, andDy is the vertical displacement of the center of mass. COM displacement was obtained from body markers recorded with ten high-speed cameras (200 Hz; Motion Analysis System, Santa Rosa, CA, USA). A total of 29 re ective markers were placed according to the Helen Hayes marker set to de ne the segmental model. Markers were attached to anatomical landmarks including the head (top, front, rear), bilateral shoulders and offset, elbows, wrists, anterior superior iliac spines (ASIS), sacrum, thighs, medial and lateral knees, shanks, medial and lateral ankles, heels, and toes. Marker trajectories were processed using Orthotrak software (version 6.2.4; Single Trial Processing Module (version 3.2); Motion Analysis System, Vicon Nexus (version 2.14); Clinical Gait Analysis Software (version 4.0)) to compute COM displacement. Raw marker data were low-pass ltered at 6 Hz using a fourth-order Butterworth lter, which

thighs, medial and lateral knees, shanks, medial and lateral ankles, heels, and toes. Marker trajectories were processed using Orthotrak software (version 6.2.4; Single Trial Processing Module (version 3.2); Motion Analysis System, Vicon Nexus (version 2.14); Clinical Gait Analysis Software (version 4.0)) to compute COM displacement. Raw marker data were low-pass ltered at 6 Hz using a fourth-order Butterworth lter, which is commonly applied in gait and jump analyses to reduce high-frequency noise while preserving movement signals [29,30]. The global coordinate system was de ned with the x-axis oriented anterior–posterior, y-axis medial–lateral, and z-axis vertical, ensuring reproducibility of COM calculations across participants. 2.4. EMG Collection and Analysis Maximal voluntary contraction (MVC) testing was performed using a Biodex System 4 Pro Dynamometer (Biodex Medical Systems, Shirley, NY, USA) to normalize EMG signals. Participants performed maximal isometric exion and extension of the knee joint and dorsi exion and plantar exion of the ankle joint for 5 s each, with both joints positioned at 90 . Electromyographic activity (EMG) was recorded using a wireless telemetry system (TeleMyo 2400T, Noraxon, Scottsdale, AZ, USA) from the vastus lateralis (VL), biceps femoris (BF), tibialis anterior (TA), and medial gastrocnemius (MG) of both legs. Prior to electrode placement, the skin was shaved, abraded, and cleaned with alcohol wipes to reduce impedance. Disposable surface electrodes (Noraxon USA Inc., Scottsdale, AZ, USA) were positioned over the muscle belly according to the SENIAM guidelines [31]. EMG signals were pre-ampli ed, band-pass ltered at 15–1000 Hz, and sampled at 3000 Hz following established recommendations for surface EMG acquisition [32,33]. Normalized EMG activity (%MVC) was calculated as the mean and standard deviation across conditions and rope-jumping phases.

Sports2025,13, 410 5 of 12 Muscle activity was analyzed in different temporal phases relative to ground con- tact: (1) pre-activation (PRE), de ned as the mean EMG within 100 ms before landing; (2) background activity (BGA), de ned as the rst 30 ms after foot contact; (3) short-latency re ex (M1), de ned as EMG activity 30–60 ms post-contact; and (4) long-latency re ex (M2), de ned as EMG activity 60–90 ms post-contact [17,18]. M1 and M2 windows were speci cally selected because they correspond to well-established neuromuscular re ex responses following stretch-shortening cycle actions, allowing for standardized comparison across studies, whereas task-speci c phases such as stance or ight may vary depending on cadence and individual technique. Co-activation ratios were also calculated to assess joint stability. At the knee, the ratio of BF to VL represented hamstring–quadriceps co-activation, while at the ankle, the ratio of TA to MG represented dorsi exor–plantar exor co-activation. 2.5. Statistical Analysis All statistical analyses were performed using SPSS software (version 20.0; IBM Corp., Armonk, NY, USA). Data normality was veri ed using the Kolmogorov–Smirnov test. Independent t-tests were applied to compare kinetic variables between male and female Muay Thai athletes. Paired t-tests were conducted to examine differences between mea- surement methods for vertical leg stiffness and center of mass displacement. Differences across jumping conditions (NDL, DL, and DOL) were analyzed using one-way repeated- measures ANOVA. In addition, a two-way mixed-design ANOVA was employed with sex(male vs. female)as the between-subjects factor and condition (NDL, DL, DOL) as the within-subjects factor, followed by Bonferroni-adjusted pairwise comparisons to control for multiple testing and reduce the risk of Type I error. Mauchly's test of sphericity was applied to assess the assumption of sphericity, and when violated, Greenhouse–Geisser corrections were used. Effect sizes were also calculated, with partial eta squared ( 2) reported for ANOVA results and Cohen's d for pairwise comparisons, to enhance interpretation given the small sample size. Statistical signi cance was set atp< 0.05. 3. Results 3.1. Peak Ground Reaction Force, Contact Time, and Flight Time Peak ground reaction force (GRF Peak) values were lower in

were used. Effect sizes were also calculated, with partial eta squared ( 2) reported for ANOVA results and Cohen's d for pairwise comparisons, to enhance interpretation given the small sample size. Statistical signi cance was set atp< 0.05. 3. Results 3.1. Peak Ground Reaction Force, Contact Time, and Flight Time Peak ground reaction force (GRF Peak) values were lower in Muay Thai females com- pared with males across all jumping conditions, although these differences were not sta- tistically signi cant (p> 0.05). Within each sex, GRF Peakwas signi cantly lower during unilateral (dominant and non-dominant leg) rope jumping than during bilateral rope jump- ing (p< 0.05). The corresponding effect sizes indicated large magnitudes of difference between jumping modes (females: 2= 0.46, d = 1.84; males: 2= 0.43, d = 1.73), re ecting substantial increases in ground reaction forces under double-leg conditions. No signi cant main effect of sex was observed for contact time (p> 0.05). However, contact time during double-leg rope jumping was signi cantly shorter than during unilat- eral rope jumping in both sexes (p< 0.05). The observed effect sizes demonstrated large effects (females: 2= 0.50, d = 2.00; males: 2= 0.29, d = 1.26), con rming meaningful reductions in ground contact duration during the double-leg condition. Flight time also showed no signi cant differences between sexes (p> 0.05). Neverthe- less, ight time was signi cantly longer during double-leg compared with unilateral rope jumping within both groups (p< 0.05). The corresponding effect sizes were large (females: 2= 0.27, d = 1.21; males: 2= 0.19, d = 0.97), indicating that the bilateral condition induced greater airtime and rebound performance (Table).

Sports2025,13, 410 6 of 12 Table 1. Kinetic characteristics of rope jumping, including peak ground reaction force (GRFpeak), leg stiffness (Kleg), contact time (tc), and ight time (tf), across dominant-leg, non-dominant-leg, and double-leg jumping conditions. Effect sizes ( 2and Cohen's d) are presented to indicate the magnitude of differences between conditions. Parameter Sex Dominant Leg Non-Dominant Leg Double Leg Effect Size ( 2 /Cohen's d) GRF Peak (kN) Females 2.83 0.42 2.96 0.60 4.04 0.83 a,b 2 = 0.46 (d = 1.84) Males 3.22 0.57 3.33 0.45 4.35 0.73 a,b 2 = 0.43 (d = 1.73) K leg (kN/m) Females 17.02 3.66 16.47 3.61 19.88 5.46 2 = 0.09 (d = 0.62) Males 16.21 4.09 16.58 3.38 19.08 3.44 2 = 0.13 (d = 0.76) tc (s) Females 0.280 0.03 0.257 0.04 0.220 0.03 a,b 2 = 0.50 (d = 2.00) Males 0.275 0.05 0.279 0.04 0.223 0.03 a,b 2 = 0.29 (d = 1.26) tf (s) Females 0.205 0.03 0.206 0.04 0.255 0.05 a,b 2 = 0.27 (d = 1.21) Males 0.245 0.05 0.224 0.03 0.285 0.03 a,b 2 = 0.19 (d = 0.97) GRF peak= peak vertical ground reaction force; K leg= leg stiffness; tc = contact time; tf = ight time. a Signi cant difference between dominant and double-leg conditions (p< 0.05). b Signi cant difference between non-dominant and double-leg conditions (p< 0.05). Effect sizes are reported as partial eta squared ( 2) for the ANOVA and Cohen's d for pairwise comparisons. 3.2. Leg Stiffness (K leg) and Center of Mass Displacement (COM) Leg stiffness (K leg) de ned as the ratio of peak ground reaction force to the vertical displacement of the center of mass, did not differ signi cantly between Muay Thai males and females across all jumping conditions (p> 0.05). However, within both sex groups, K legvalues were signi cantly higher during double-leg rope jumping compared with unilateral conditions (p< 0.05). The corresponding effect sizes indicated small-to-moderate magnitudes (females: 2= 0.09, d = 0.62; males: 2= 0.13, d = 0.76), suggesting that although statistically signi cant, the practical differences in stiffness were modest. Center

This study investigates leg stiffness and muscle activation in Muay Thai athletes during rope jumping.