Reaction Time and Postural Control Under Dual-Task Conditions in Brazilian Jiu-Jitsu Athletes

Abstract

Given the high postural control demands of sport Jiu-Jitsu, prolonged training in this discipline may result in sport-specific adaptations, particularly in positions closely related to combat scenarios. This study aimed to evaluate the differences in reaction time and postural control between elite Jiu-Jitsu athletes and untrained individuals, highlighting the potential influence of specialized training on these critical performance attributes. This study was conducted on thirty-one young participants (fifteen Brazilian Jiu-Jitsu athletes and sixteen non-athletes). Reaction time was measured using the Fit Light Trainer system in two positions. Postural control was assessed during 30 s bipedal and single-leg standing, both with and without a dual task involving tracking a randomly moving point on a screen. Results indicated that athletes demonstrated significantly faster reaction times (p = 0.0242) and greater complexity in postural control mechanisms, as evidenced by higher fractal dimension values during single-leg standing with dual tasks in the anterior–posterior direction (p = 0.0011). These findings suggest that Brazilian Jiu-Jitsu athletes possess enhanced neuromuscular and cognitive–motor integration, crucial for managing the complex demands of martial arts. This study highlights the importance of incorporating dual-task scenarios in training to optimize athletic performance and postural control in high-demand sport contexts.

1. Introduction

Daily living activities require a fundamental level of postural control [1,2]. Maintaining correct body posture and balance during rapid movements or sports is crucial for physically fit individuals, particularly those engaged in martial arts such as Judo [3], Taekwon-do [4,5,6], Karate, Krav Maga, or Brazilian Jiu-Jitsu [7]. In the last decade, there has been a significant rise in the popularity of Brazilian Jiu-Jitsu, due to the success of Brazilian athletes in mixed martial art events [8]. The primary goal in Brazilian Jiu-Jitsu is to force the opponent into submission using chokeholds, joint locks (e.g., elbow, knee, and ankle locks), and pressure techniques. When a submission is not achieved, the match is decided based on points awarded for specific techniques (such as guard passes, mounts, and back control), or by the referee’s decision in the case of a draw [8,9,10,11]. Brazilian Jiu-Jitsu athletes must be in exceptional physical condition, possessing a broad range of physical attributes [11]. Key factors for success include aerobic power for sustaining high-intensity efforts throughout the match [12]; muscle power for effective throwing techniques; muscular endurance; reaction time for anticipating opponent moves; and flexibility, which plays a critical role in both attack and defense situations [8,9]. In Andreato’s [10] systematic review which describes the physical and physiological profiles of Brazilian Jiu-Jitsu athletes, reaction time was described only in two papers. Moreover, during the literature review, a limited number of studies were found that describe the characteristics of postural control among combat sport athletes. This observation is noteworthy because maintaining a stable body posture is equally challenging when executing defensive and counterattacking techniques in conditions of significant instability [13].

Recent studies show that martial art training can improve postural control not only in individuals with neurological disorders [14] but also in healthy adults [15]. The long-term practice of combat sports, such as Judo [16], Karate [17], and Taekwon-do [18], leads to changes in postural control. Interestingly, junior athletes and untrained individuals typically exhibit poorer balance, as assessed in both static and dynamic tests, compared to senior, elite athletes [19]. Furthermore, differences in postural control are observed early in training, with adult practitioners displaying superior balance abilities compared to their same-aged, physically active peers [1]. Many studies have suggested that postural control changes are more pronounced in sport-specific positions than in basic ones like bipedal standing [20]. In static conditions (bipedal, quiet standing), elite judokas, surfers, and dancers did not achieve better postural measurements than the control groups [21,22]. However, these athletes demonstrated superior postural control during dynamic tasks or when performing dual-task exercises [23]. The dual-task paradigm, where athletes perform physical and cognitive tasks simultaneously, is a well-established method for assessing the interaction between motor control and cognitive functions. This paradigm is especially relevant in combat sports, where quick reactions and balance are paramount [24,25]. Studies involving Taekwon-do athletes have shown that dual-task conditions can negatively affect both motor and cognitive performance. However, targeted dual-task training has proven effective in improving performance in both static and dynamic tasks [26]. By incorporating dual-task training into combat sports, athletes can enhance their ability to divide attention between cognitive and motor tasks, which leads to better postural stability and more responsive dynamic reactions [27]. Moreover, dual-task performance can serve as an indicator of cognitive function and motor adaptation, suggesting its value in evaluating the training levels and postural control strategies of combat sport athletes [28,29].

In addition to the studies mentioned, several more recent works have explored postural control using advanced measurement techniques. Force platforms, considered the gold standard for measuring center of pressure (CoP) displacement, are widely used in these studies, particularly in elite athletes. Linear metrics such as CoP path length, range, or velocity have been used to quantify postural control. However, these linear measures often fail to capture the full complexity of dynamic postural sway and do not fully explain the positive effects of sport expertise on postural control. More recent research [30] has emphasized the importance of nonlinear measures for analyzing CoP signals, focusing on temporal variations in CoP displacement in both anteroposterior (AP) and mediolateral (ML) directions. These nonlinear metrics allow for a more nuanced understanding of the regularity, adaptability, stability, and complexity of postural control. One of the most widely used nonlinear measures is Sample Entropy (SampEn), which assesses the regularity of a signal and the degree of attention applied during balance tasks [31]. High SampEn values indicate irregular CoP time series, reflecting a healthy and adaptive biological system. Conversely, low SampEn values indicate more regular time series, suggesting rigidity in postural control, which may be associated with potential pathology. Fractal dimension (FD) is a metric used to assess the complexity of the CoP signal. An FD value of 1 represents a theoretically impossible scenario for a human, as it would indicate completely still standing without any movement—an outcome unattainable for living humans due to natural postural sway [32]. The last nonlinear measure is the Lyapunov Exponent (LyE), which evaluates the resistance of the human control system to external perturbations [33]. A high LyE value indicates the ability to react faster to stimuli, and a low value indicates the rigidity of the system and problems with adapting to the environment.

Recent studies have started to incorporate nonlinear measures into postural control assessments in Brazilian Jiu-Jitsu athletes. For instance, one study employed SampEn to assess postural control in elite Jiu-Jitsu athletes and a control group of non-athletes [34]. Given the limited research on reaction time and the use of nonlinear measures to describe postural control, this study aimed to determine whether Brazilian Jiu-Jitsu athletes exhibit better reaction times in specific positions compared to a control group. In addition, this study will assess whether Brazilian Jiu-Jitsu athletes display more complex postural control than non-athletes during tasks requiring focus and attention.

2. Materials and Methods

2.1. Participants and Procedures

This study involved 31 participants, consisting of 15 Brazilian Jiu-Jitsu athletes (9 men and 6 women) with an average age of 26.67 ± 3.57 years, a body height of 171.20 ± 8.49 cm, and a body mass of 68.32 ± 10.71 kg. These athletes had an average of 5.73 ± 5.28 years of training experience. The control group comprised 16 individuals (10 men and 6 women), with an average age of 25 ± 1.80 years, a body height of 178.62 ± 7.57 cm, and a body mass of 78.29 ± 13.25 kg.

Athletes were included based on the following criteria: at least one year of non-professional Brazilian Jiu-Jitsu experience (defined as training without competition participation); no orthopedic or physiological injuries; a training frequency of 3–4 times per week; and no chronic diseases, disabilities, or pain disorders. For the control group, inclusion criteria included the absence of orthopedic injuries or neurological conditions that might interfere with postural stability testing, as well as regular participation in recreational physical activities (such as running, cycling, or walking) several times per week.

Before the measurements, all participants were informed about the experimental procedures. Both athletes and control participants took part in this study during the afternoon, between 4:00 and 7:00 p.m. Additionally, they attended the testing sessions before their training, ensuring they were well rested. This approach effectively minimized the potential impact of fatigue and prior physical exertion on the study outcomes. The measurements were conducted on days prior to training and divided into two parts. The first part of this study measured reaction time using the FitLight Trainer system (FitLight Sports Corp., Kingston, ON, Canada) (Figure 1A). The FitLight Trainer system is a tool designed to measure reaction time by utilizing a series of eight interactive, wireless lights. These lights can be placed in various positions and are activated in random sequences. Participants are required to react as quickly as possible by deactivating the lights (usually by touching or pressing them) when they light up. In this study, the protocol was carried out in standing and sitting positions (Figure 1B,C), with participants positioned in front of the wall-mounted lights. In both positions, they could comfortably reach each LED light with their writing hand without leaning forward. During a 60 s task, participants responded to light signals by touching the illuminated lights, while a dedicated program recorded and calculated reaction time and the total number of switched-off lights. In this system, reaction time was measured by recording the duration between the activation of a light and the participant’s response to deactivate it.

The second part of the measurements assessed postural control using the STANIAK JB platform (100 Hz). Each participant completed four trials, each lasting 30 s, with a one-minute break between trials. (1) Bipedal standing (2eo): participants stood barefoot, arms at their sides, eyes open, and focused on a fixed point at eye level. (2) Single-leg standing (1eo): participants stood on their non-dominant leg, determined by their preferred kicking leg. (3) Bipedal standing with visual tracking (2eos): participants stood, following an irregularly moving dot on a screen located 190 cm away at eye level. (4) Single-leg standing with visual tracking (1eos): participants stood on one leg, following an unpredictable moving dot on the screen.

2.2. Parameters

Three groups of parameters were analyzed. The first group consisted of reaction time parameters: reaction time in standing (R_standing) and sitting positions (R_sitting), number of switched-off lights in standing (N_standing) and sitting positions (N_sitting). The second group included a linear measure: the center of pressure path length (CoP_path). The third group contained three nonlinear parameters: Sample Entropy (SampEn), Lyapunov Exponent (LyE), and fractal dimension (FD), each calculated separately for the anterior–posterior (AP) and mediolateral (ML) directions based on the CoP time series.

Nonlinear coefficients were calculated using MatLab R2021a (MathWorks, Natick, MA, USA). SampEn measures the likelihood that a sequence of N data points will continue to match for an additional point (m + 1), excluding self-matches, with the formula involving the natural logarithm of the ratio between sequences matching for (m + 1) and m points. SampEn was calculated using MatLab scripts from Physionet [35], with default settings of m = 2 and r = 0.2 × SD (standard deviation) of the CoP time series [36]. Fractal dimension (FD) was calculated using the Higuchi algorithm [37], which is applicable to short time series. LyE was calculated using the algorithm developed by Wolf et al. [38].

2.3. Statistical Analysis

Sample size estimated using G*Power software (version 3.1.9.2; Kiel University, Kiel, Germany) [39] returned a minimum of 15 participants for p = 0.05, effect size = 0.8, and power(1 − β) = 0.68. Statistical analysis was conducted using Statistica v. 12 (StatSoft, Tulsa, OK, USA), with a significance level set at p < 0.05. All parameters were tested for normal distribution using the Shapiro–Wilk test. A nonparametric Mann–Whitney U test was applied to compare differences between the Brazilian Jiu-Jitsu and control groups. Within-group comparisons for linear and nonlinear parameters within the directions were made using the Friedmann test with the Dunn–Bonferroni post hoc test. Spearman’s rank correlations (R) were calculated separately for both groups to examine the relationships between reaction time and postural control parameters (linear and nonlinear). The interpretation of the magnitude of the correlation coefficient was as follows: (0.90, 1.00)/(−0.90, −1.00)—very high positive/negative correlation; (0.70, 0.90)/(−0.70, −0.90)—high positive/negative correlation; (0.50, 0.70)/(−0.50, −0.70)—moderate positive/negative correlation; (0.30, 0.50)/(−0.30, −0.50)—low positive/negative correlation; (0, 0.30)/(0, −0.30)—negligible correlation [40].

To compute the effect size for a Mann–Whitney U test, the following formula was used: $r={\displaystyle \frac{Z}{\sqrt{N}}}$, where Z is the Z-score from the test, and N is the total number of observations. In this case, N = 31. The effect size interpretation was as follows: r < 0.3—small effect; 0.3 ≤ r ≤ 0.5—medium effect; and r > 0.5—large effect [41].

3. Results

3.1. Comparison of Reaction Time and Postural Control Parameters Between Groups

The Mann–Whitney U test revealed that Brazilian Jiu-Jitsu athletes demonstrated significantly faster reaction times in both standing and sitting positions (Figure 2,

Table 1. Median (lower; upper quartile) for reaction time, linear, and nonlinear parameter values for Brazilian Jiu-Jitsu and control groups, where * denotes significant differences, p < 0.05.

Group	Brazilian Jiu-Jitsu	Control	U-Value	p-Value	Effect Size
Reaction time parameters
R_standing [s]	0.42 (0.40; 0.45)	0.47 (0.42; 0.49)	62.5	p = 0.0242 *	0.4
R_sitting [s]	0.41 (0.37; 0.43)	0.44 (0.41; 0.47)	57	p = 0.0134 *	0.4
N_standing [-]	76 (73; 78)	73 (69.5; 77)	71	p = 0.0538	0.4
N_sitting [-]	77 (76; 80)	75.50 (72; 77)	53	p = 0.0077 *	0.5
Linear parameters
CoP_path_2eo [mm]	217 (186; 250.50)	236 (193; 264.25)	97.5	p = 0.3844	0.16
CoP_path_1eo [mm]	1083 (956.25; 1251)	1131 (1006; 1218.50)	114	p = 0.8278	0.04
CoP_path_2eos [mm]	225 (196.25; 290.50)	235 (191; 271)	111	p = 0.7368	0.06
CoP_path_1eos [mm]	1437 (1286.5; 1619)	1571 (1453.75; 1846.25)	84	p = 0.1605	0.25
Nonlinear parameters
SampEn_ML_2eo [-]	0.34 (0.30; 0.39)	0.36 (0.32; 0.39)	111	p = 0.0134 *	0.06
SampEn_AP_2eo [-]	0.26 (0.22; 0.33)	0.25 (0.22; 0.32)	110	p = 0.7368	0.07
FD_ML_2eo [-]	1.95 (1.92; 1.96)	1.95 (1.93; 1.96)	110	p = 0.7072	0.07
FD_AP_2eo [-]	1.89 (1.87; 1.93)	1.90 (1.88; 1.94)	105	p = 0.7072	0.1
LyE_ML_2eo [-]	0.08 (0.08; 0.1)	0.09 (0.08; 0.10)	103	p = 0.5665	0.12
LyE_AP_2eo [-]	0.07 (0.06; 0.08)	0.07 (0.07; 0.08)	113	p = 0.5142	0.05
SampEn_ML_1eo [-]	0.59 (0.58; 0.60)	0.59 (0.57; 0.60)	117	p = 0.7972	0.02
SampEn_AP_1eo [-]	0.59 (0.58; 0.60)	0.59 (0.58; 0.59)	86	p = 0.9212	0.24
FD_ML_1eo [-]	2.01 (2; 2.01)	2 (1.99; 2.01)	112	p = 0.1854	0.05
FD_AP_1eo [-]	2.01 (2; 2.01)	2.01 (2; 2.01)	91	p = 0.7668	0.2
LyE_ML_1eo [-]	0.15 (0.13; 0.16)	0.13 (0.12; 0.14)	56	p = 0.0120 *	0.45
LyE_AP_1eo [-]	0.09 (0.08; 0.10)	0.09 (0.08; 0.10)	109	p = 0.6781	0.07
SampEn_ML_2eos [-]	0.36 (0.3; 0.40)	0.33 (0.29; 0.41)	112	p = 0.7668	0.05
SampEn_AP_2eos [-]	0.25 (0.2; 0.33)	0.24 (0.22; 0.26)	117	p = 0.9212	0.02
FD_ML_2eos [-]	1.94 (1.93; 1.96)	1.94 (1.92; 1.97)	116	p = 0.8899	0.02
FD_AP_2eos [-]	1.90 (1.86; 1.94)	1.89 (1.88; 1.92)	114	p = 0.8278	0.04
LyE_ML_2eos [-]	0.09 (0.08; 0.10)	0.09 (0.08; 0.10)	118	p = 0.9527	0.01
LyE_AP_2eos [-]	0.07 (0.06; 0.07)	0.06 (0.05; 0.07)	108	p = 0.6494	0.08
SampEn_ML_1eos [-]	0.60 (0.59; 0.60)	0.60 (0.59; 0.60)	120	p = 0.9842	0.01
SampEn_AP_1eos [-]	0.60 (0.59; 0.61)	0.60 (0.60; 0.61)	88	p = 0.2130	0.22
FD_ML_1eos [-]	2.007 (2.003; 2.0101)	2.009 (2.005; 2.011)	100	p = 0.44082	0.14
FD_AP_1eos [-]	2.0102 (2.008; 2.0109)	2.012 (2.011; 2.013)	37	p = 0.0011 *	0.59
LyE_ML_1eos [-]	0.15 (0.13; 0.16)	0.15 (0.14; 0.16)	82	p = 0.1382	0.27
LyE_AP_1eos [-]	0.096 (0.089; 0.10)	0.092 (0.087; 0.10)	97	p = 0.3737	0.16

R_standing—reaction time in standing position; R_sitting—reaction time in sitting position; N_standing—the number of lights off in the standing position; N_sitting—the number of lights off in the sitting position; CoP—center of pressure; CoP_path—center of pressure path length; AP—anterior–posterior direction; ML—mediolateral direction; SampEn—Sample Entropy; FD—fractal dimension; LyE—Lyapunov Exponent; 2eo—bipedal standing; 1eo—single-leg standing; 2eos—bipedal standing with visual tracking; 1eos—single-leg standing with visual tracking.

).

Additionally, the number of light-off events in this group was higher than in the control group, with a significant difference observed only in the sitting position (Table 1).

For linear parameters—the center of pressure path length (CoP_path)—no significant differences were observed between the groups. The highest CoP path length was recorded in the control group during single-leg, dual-task standing (CoP_path_1eos), while the lowest was observed in Brazilian Jiu-Jitsu athletes during quiet standing (CoP_path_2eo). The Mann–Whitney U test revealed three significant differences for nonlinear measures: SampEn_ML_2eo (higher values in the control group than in Brazilian Jiu-Jitsu athletes), LyE_ML_1eo (higher values in Brazilian Jiu-Jitsu athletes compared to in the control group), and FD_AP_1eos (higher in the control group compared to in Brazilian Jiu-Jitsu athletes).

3.2. Comparison and Correlations Within Control Group

In the control group, the Friedmann test identified statistically significant differences across all linear (CoP: F(N = 16, df = 3) = 41.52, p = 0.0001) and nonlinear parameters within directions (SampEn_ML: F(N = 16, df = 3) = 38.70, p = 0.0001; SampEn_AP: F(N = 16, df = 3) = 41.17, p = 0.0001; FD_ML: F(N = 16, df = 3) = 40.27, p = 0.0001); FD_AP: F(N = 16, df = 3) = 42.07, p = 0.0001; LyE_ML: F(N = 16, df = 3) = 41.17, p = 0.0001; LyE_AP: F(N = 16, df = 3) = 37.12, p = 0.0001). The Dunn–Bonferroni post hoc test identified significant differences between the following trial pairs: 2eo vs. 1eo, 2eo vs. 1eos, 1eo vs. 2eos, and 2eos vs. 1eos, with all differences highly significant (p = 0.0001). Notably, linear and nonlinear parameter values were consistently higher during the two lower-limb standing trials.

In this group, only two significant correlations were identified. The first was a positive correlation (R = 0.61, p < 0.05) between the number of lights turned off in the sitting position and the SampEn_AP_1eos value. The second was a negative correlation (R = −0.53, p < 0.05) between reaction time in the standing position and the SampEn_AP_1eos value.

3.3. Comparison and Correlations Within Brazilian Jiu-Jitsu Athletes

In the Brazilian Jiu-Jitsu group, as in the control group, the Friedmann test identified statistically significant differences across all linear (CoP: F(N = 16, df = 3) = 41.09, p = 0.0001) and nonlinear parameters within directions (SampEn_ML: F(N = 16, df = 3) = 36.36, p = 0.0001; SampEn_AP: F(N = 16, df = 3) = 37.80, p = 0.0001; FD_ML: F(N = 16, df = 3) = 36.36, p = 0.0001); FD_AP: F(N = 16, df = 3) = 36.04, p = 0.0001; LyE_ML: F(N = 16, df = 3) = 36.20, p = 0.0001; LyE_AP: F(N = 16, df = 3) = 35.08, p = 0.0001). The Dunn–Bonferroni post hoc test identified significant differences between the following trial pairs: 2eo vs. 1eo, 2eo vs. 1eos, 1eo vs. 2eos, and 2eos vs. 1eos, with all differences highly significant (p = 0.0001). Notably, linear and nonlinear parameter values were consistently higher during the two lower-limb standing trials.

In this group, nine significant correlations were identified (Figure 3). Negative correlations were observed between the number of lamps switched off in the standing position and both LyE_AP_1eo (R = −0.62, p < 0.05) and LyECoP_ML_1eos (R = −0.61, p < 0.05). Similarly, negative correlations were found between the number of lamps switched off in the sitting position and both LyE_AP_1eo (R = −0.80, p < 0.05) and LyECoP_ML_1eos (R = −0.58, p < 0.05). Additionally, a significant positive correlation was found between the number of lamps switched off in the standing position and LyECoP_ML_2eos (R = 0.54, p < 0.05) (Figure 3A).

Positive correlations were observed between the reaction time (in both standing and sitting positions) and LyE_AP_1eo (R = 0.57, p < 0.05), as well as between LyECoP_ML_1eos and the reaction time (R = 0.64, p < 0.05 for standing and R = 0.81, p < 0.05 for sitting) (Figure 3B).

4. Discussion

This study aimed to assess whether Brazilian Jiu-Jitsu athletes exhibit faster reaction times in specific positions compared to untrained control subjects across various postural trials. Additionally, this study sought to evaluate whether Brazilian Jiu-Jitsu athletes demonstrate more complex postural control than control subjects during tasks that require focus and attention.

Reaction time, as noted by Cano et al. [42], is a critical parameter in sports, reflecting an individual’s ability to respond quickly to external stimuli. In combat sports like Brazilian Jiu-Jitsu, reaction time is particularly vital, as athletes must respond instantly to dynamic and unpredictable situations, such as countering an opponent’s movements or transitioning between techniques. Effective reaction times can determine success in both offensive and defensive scenarios, making it an essential skill for high-level performance. In this study, Brazilian Jiu-Jitsu athletes demonstrated significantly faster reaction times in both sitting and standing positions when compared to the control group. Notably, the athletes also achieved significantly higher numbers of light-off events in the sitting position, indicating enhanced focus and response efficiency in this posture. Here, the sitting position appears to be particularly effective in differentiating athletes from non-athletes, likely due to the specific training exercises in Brazilian Jiu-Jitsu that involve engaging core stability; spatial awareness; and rapid decision-making while seated, such as defending guard positions or transitioning into attacks [43,44].

According to Lima et al. [43], Brazilian Jiu-Jitsu is a martial art that not only requires strength and flexibility but also places a significant emphasis on balance. The ability to maintain and adjust one’s balance is crucial for executing effective offensive and defensive techniques [45]. Research consistently supports the idea that long-term training, particularly exercises that challenge and disrupt balance, has a positive impact on improving postural control [46,47]. Such training helps individuals develop a heightened sense of balance, enabling them to respond more effectively to dynamic situations. This study utilized both linear and nonlinear parameters to assess postural control, focusing on the complexity of postural control and the regularity of the CoP signal during four tasks: standing on both feet and one leg with eyes open, as well as standing on both feet and one leg while tracking a chaotically moving point on a screen. The linear parameter (CoP path length) did not significantly differentiate the groups. The control group consistently showed longer CoP paths in each task, reflecting greater balance fluctuations and reduced stability compared to Brazilian Jiu-Jitsu athletes. Similar findings were reported by Akbas’s study [34], who observed no differences in quiet standing between elite Jiu-Jitsu athletes and control subjects.

In contrast, nonlinear measures provided more detailed and informative insights. Specifically, SampEn_ML_2eo was higher in the control group compared to in Brazilian Jiu-Jitsu athletes, suggesting that the control group exhibited a more irregular mediolateral CoP signal when standing on both feet and with eyes open. This irregularity may indicate less consistent postural strategies or a lack of refined balance control, which is often seen in untrained individuals. In contrast, the lower SampEn values in Brazilian Jiu-Jitsu athletes suggest more regular and efficient postural control in this task, likely reflecting the effects of their training on balance stability. For LyE_ML_1eo, Brazilian Jiu-Jitsu athletes displayed higher values compared to the control group, indicating greater divergence in the mediolateral CoP trajectory during one-legged standing with eyes open. Higher Lyapunov Exponent values are associated with greater adaptability and complexity in the postural control system, which is advantageous in dynamic environments. This finding aligns with the demands of Brazilian Jiu-Jitsu, where athletes must continuously adapt their balance to counter unpredictable movements and maintain stability during grappling scenarios. In contrast, the control group exhibited higher FD_AP_1eos values compared to Brazilian Jiu-Jitsu athletes during one-legged standing while tracking a chaotically moving dot. A higher fractal dimension indicates a more complex CoP trajectory, which could reflect the control group’s greater difficulty in maintaining stability during this cognitively demanding task. The lower FD values in Brazilian Jiu-Jitsu athletes suggest that their training allows them to simplify their postural control strategy under challenging conditions, maintaining effective stability without unnecessary complexity.

These findings demonstrate that Brazilian Jiu-Jitsu training fosters a balance system that is both adaptive and efficient. While athletes displayed greater adaptability in tasks requiring single-leg standing (LyE_ML_1eo), they also showed more efficient and stable postural control strategies in simpler tasks (SampEn_ML_2eo) and cognitively demanding conditions (FD_AP_1eos). These differences highlight the sport-specific benefits of Brazilian Jiu-Jitsu, which involves frequent dynamic shifts in posture, maintaining balance under pressure, and responding to complex environmental stimuli.

The last part of this paper looked at patterns of observed correlations in the control group and Brazilian jiu-jitsu athletes, highlighting differences in their postural control and response strategies.

In the control group, only two significant correlations were observed. A moderate positive correlation (R = 0.61, p < 0.05) was found between the number of lights turned off in the sitting position and SampEn_AP_1eos, suggesting that participants with more irregular CoP signals in the anteroposterior (AP) direction performed better in light-switching tasks. Conversely, a moderate negative correlation (R = −0.53, p < 0.05) between reaction time in the standing position and SampEn_AP_1eos indicated that participants with faster reaction times exhibited more regular CoP signals, possibly reflecting a more rigid postural control strategy.

In contrast, Brazilian Jiu-Jitsu athletes demonstrated a more complex interplay between postural control and task performance, with nine significant correlations identified. Negative correlations were observed between the number of lamps switched off and LyE_AP_1eo (R = −0.62, p < 0.05) and LyECoP_ML_1eos (R = −0.61, p < 0.05) during standing tasks, as well as LyE_AP_1eo (R = −0.80, p < 0.05) and LyECoP_ML_1eos (R = −0.58, p < 0.05) during sitting tasks. These moderate to high negative correlations suggest that athletes who performed better in light-switching tasks exhibited less variability in their postural dynamics, likely reflecting greater postural control efficiency.

Positive correlations were also observed in the athlete group. Moderate correlations were noted between reaction time (in both positions) and LyE_AP_1eo (R = 0.57, p < 0.05) and LyECoP_ML_1eos (R = 0.64, p < 0.05 for standing, R = 0.81, p < 0.05 for sitting). This indicates that longer reaction times were associated with more dynamic and adaptable postural control, as reflected by higher LyE values. Furthermore, a moderate positive correlation (R = 0.54, p < 0.05) between the number of lamps switched off in the standing position and LyECoP_ML_2eos suggests that greater postural adaptability in the mediolateral (ML) direction supported better task performance. A review of the literature reveals that no previous studies have combined reaction time analysis with nonlinear postural control parameters. However, research has investigated dual-task performance in athletes, including Taekwon-do practitioners [26,48]. These studies suggest that expert athletes automatically adjust their postural control during motor tasks, requiring less cognitive effort due to their well-developed proprioceptive and balance systems. In contrast, novice athletes show significant declines in performance under dual-task conditions, underscoring the importance of dual-task training to enhance working memory and attentional control. Future research should examine dual-task paradigms across various combat sports and compare postural control strategies between disciplines.

5. Limitations and Future Research

The small sample size may limit the ability to generalize the results to a larger population. Future research could explore the impact of specific Brazilian Jiu-Jitsu training protocols on these adaptations and investigate whether the benefits extend to other dynamic activities outside the sport. It would also be valuable to study experienced Brazilian Jiu-Jitsu athletes to assess how training seniority influences posture and reaction time, offering a deeper understanding of the effects of elite-level training.

Additionally, investigating athlete preferences and fighting styles (e.g., stand-up vs. ground fighting) could provide insights into how these factors influence the variables examined and their potential impact on performance in competition. Future studies should also incorporate dynamic tasks, such as balancing on unstable surfaces or analyzing movement during real combat techniques, to better reflect the conditions encountered in Brazilian Jiu-Jitsu.

Moreover, the inclusion of advanced biomechanical indicators—such as ground reaction force (GRF) analysis, eye tracking, and electromyographic (EMG) recordings—could provide a more comprehensive understanding of postural control. Alternative approaches to measuring reaction time, such as integrating tactile and auditory stimuli or assessing performance under varying levels of fatigue, would allow for a more precise evaluation of perceptual–motor abilities.

6. Conclusions

This study highlights the significant impact of Brazilian Jiu-Jitsu training on both reaction time and postural control. Brazilian Jiu-Jitsu athletes demonstrated faster reaction times and superior cognitive–motor coordination, enabling them to efficiently perform complex tasks in both sport-specific and general postural challenges. These findings underscore the potential benefits of the sport in enhancing dynamic responsiveness and decision-making under pressure. Additionally, the correlation analysis revealed distinct differences between the control group and the Brazilian Jiu-Jitsu athletes. While the control group exhibited a more rigid approach to postural strategies, the athletes showed a stronger and more nuanced relationship between postural adaptability and task performance. This suggests that Brazilian Jiu-Jitsu training improves the ability to dynamically adjust posture in response to complex and attention-demanding tasks, highlighting the sport’s influence on nonlinear postural control adaptations. These findings emphasize the value of long-term Brazilian Jiu-Jitsu training in enhancing balance, adaptability, and task-specific performance.