Short-Term Effects of Rock Steady Boxing Exercise on the Balance Ability of People with Parkinson’s Disease: An Interventional Experimental Study

Abstract

The occurrence of injuries due to unintentional falls becomes particularly dangerous in people with neurological disorders such as Parkinson’s disease (PD). The present study aimed to evaluate the influence of the Rock Steady Boxing (RSB) program’s single training units on body stability changes in elderly people with PD. Data from 18 patients (PG) and a similar-age 15-person control group without PD (CG) were used to analyze the collected study material. Postural stabilography was used to assess balance ability in two 30-second tests of standing on both feet with eyes open (EO) and closed (EC). The EO_CoP path length was significantly (p = 0.007) longer in the PG (266 ± 105 mm) compared to the CG (172 ± 32 mm), and similar differences were obtained for other parameters. PG measurements were taken over four consecutive weeks of RSB, both before and after each 90-minute training session. The lack of relevant differences be-tween measurements before vs. after for the PG may indicate the appropriate adaptation of exercisers to the applied loads. The probability of the compared parameters ranged from p = 0.586 to p = 0.999. Participation in RSB-based physical activity resulted in a deterioration in balance ability in the majority of participants immediately after exer-cise, but the results were characterized by a large spread, and the changes varied indi-vidually. Therefore, sports activities for PD must be adapted accordingly, taking into account the stage of the disease or the duration of the disease.

1. Introduction

Losing balance, falling, and colliding with the ground or an obstacle can lead to serious injury and even death. This problem affects people of all ages, but the most vulnerable to its negative effects are the elderly, who, especially as a result of such events, often suffer serious health consequences [1]. With increasing life expectancy in developed countries, this phenomenon is becoming a complex interdisciplinary problem that requires collaboration between preventive health, physical rehabilitation (physiotherapy), education, social care, and economics [2,3,4,5].

The occurrence of injuries due to unintentional falls becomes particularly dangerous in people with neurological disorders such as Parkinson’s disease (PD). For this reason, particular attention is paid to monitoring balance in patients with PD, as balance disorders can lead to serious health consequences [6]. PD, a neurodegenerative disorder, affects the functioning of both the central nervous system and the motor system, leading to increasing motor difficulties and an increased risk of falls [7]. The first symptoms of PD include muscle stiffness, tremor in the limbs, difficulty moving, and deteriorating memory. As the disease progresses, patients may experience psychiatric symptoms such as depression and dementia, as well as emotional and sleep disturbances.

Findings indicate that patients with PD fall more frequently than age-matched controls [8,9,10]. Balance disorders and recurrent falls are one of the most common causes of injury in PD patients, with up to 65% reporting episodes of balance loss and 39% experiencing recurrent falls [6]. These falls are not only painful but can lead to fractures that often require hospitalization and long-term rehabilitation. It is estimated that between 10% and 35% of falls in this age group result in a fracture, with femoral neck fractures being the most common, accounting for approximately 10% of cases [11,12].

Balance control is a complex process that requires multiple structures of the nervous and musculoskeletal systems to work together. The process relies on the integration of sensory and motor information, as well as effective postural control. Although it is difficult to identify all the mechanisms underlying balance control, strengthening sensorimotor function and lower limb muscle strength, which are responsible for postural stabilization and protection against falling, are considered important [13,14].

One way to improve balance and reduce the risk of falls is to participate in exercise programs. Regular exercise is associated with improvements in motor function, balance, and gait, resulting in a better quality of life and a reduction in falls [7,15]. Despite the many benefits of physical activity, people with PD often face a variety of barriers that limit their participation in exercise programs, such as low performance expectations, lack of time, and fear of falling [8]. In response to these challenges, dedicated programs have been developed specifically for people with PD that address their needs and limitations. Trying boxing is particularly valuable because it represents goal-oriented multitasking rehabilitation. The goal-oriented dual-task approach is essential in many neurological disorders [16].

One such program is Rock Steady Boxing (RSB) a form of non-contact boxing, which uses elements of boxing and aims to improve balance and reduce the risk of falls. The RSB program is based on intensive training and balance exercises that support patients’ motor development and is gaining popularity among people with PD (RSB, 2023). Similar benefits are provided by martial arts-inspired exercise programs, such as karate or judo, which emphasize postural control and balance [17,18]. These programs mimic elements of defensive and offensive techniques, allowing for an engaging and dynamic way to improve postural control and spatial orientation in a safe manner adapted to the capabilities of older people.

The RSB program is an increasingly popular form of rehabilitation for patients with PD, and there are studies in the literature confirming the effectiveness of the above training. So far, the parameters assessed have mainly been fitness tests such as the STStest [19], the TUGtest [19,20,21,22], or tasks examining general motor skills [21,22,23,24], but also quality-of-life surveys [19,23,24,25] and satisfaction surveys [19,25]. Body stability was assessed using functional tests such as the Fullerton Advanced Balance (FAB) Scale [20,21,22] or the Mini BESTest [23]. However, there are no publications that would objectively assess the changes in functional biomechanical parameters, such as postural stability, induced by RSB training in PD patients.

Modern measurement technologies, such as balance monitoring systems, provide objective data on patients’ movement patterns [26,27]. These devices allow for the accurate monitoring of subtle changes in the balance process and the loss of postural control that often escape traditional assessments [28]. A frequently analyzed measure of body stability is the length of the path traced by the center of pressure of the feet on the ground—the longer the path is, the greater the risk of falling. The use of measuring devices allows for improving of the assessment of balance abilities and the identification of predictors of falls, which can significantly support the effectiveness of preventive measures.

Based on the above, the present exploratory study aimed to evaluate the influence of the RSB program’s single training units on body stability changes in elderly people with Parkinson’s disease. We hypothesize that single RSB efforts significantly influence the stability parameters of PD patients. The impact of the RSB exercises on improving balance abilities and thus quality of life may be an important element of fall prevention and rehabilitation support for this patient group.

This paper is organized as follows. Section 2 characterizes the participants of the research, describes the RSB course, and the postural stabilography method used. Section 3 presents the obtained data in the intergroup comparison and in the comparison before and after the training session. Section 4 summarizes the experimental results and discusses them in relation to similar research. Section 5 presents the conclusions.

2. Materials and Methods

All participants were briefed on the conduct of the experiment and the control study. They were made aware of the conditions of participation in the experiment and the measurement methodology, as well as the potential risks and responsibilities. All participants have provided their informed consent to participate in the study. Each person signed a consent form, while knowing that they could terminate the experiment at any time without any consequences. The experiment was designed in accordance with the Declaration of Helsinki and was approved by the University of Physical Education in Warsaw’s Research Bioethics Commission No. SKE 01-37/2024.

2.1. Participants

Subjects with diagnosed PD, receiving medical care and drug treatment were included. To be eligible, participants could not have a neurological disease other than PD. The number of participants was based on sample size calculations using G*Power software (version 3.1.9.7, Düsseldorf, Germany). A priori sample size was calculated for a group by time interaction comparison (F test, ANOVA for repeated measures, within-between interaction) with the following specifications: alpha level = 0.05, power = 0.95, f effect size = 0.25. Based on this, the estimated number of subjects was 24. In the first phase, 25 participants were qualified: eighteen men and seven women. Only participants with a reported PD clinical severity score range of 1 to 3 on the Hoehn and Yahr scale were included in the experiment [29]. Exclusion criteria were the presence of comorbidities, clinical disease progression above 3 on the Hoehn and Yahr scale, and absenteeism from consecutive training sessions. Finally, data from 18 participants (PGs) were used to analyze the collected study material: 12 men and 6 women (

Table 1. Subjects’ characteristics (mean ± SD).

Group	n	Age [years]	Mass [kg]	Height [cm]	Length of Disease [years]	Training Experience [years]
PG	18	72 ± 6	67 ± 10	168 ± 8	7.2 ± 4.8	2.4 ± 1.8
CG	15	72 ± 5	66 ± 11	159 ± 4	n/a	n/a

). For comparison purposes, single measurements of body stability were taken in a control group (CG, n = 15), selected among subjects of similar age but without diagnosed PD. Both groups did not statistically differ in the parameters of age, body mass, and height (p > 0.05).

2.2. Rock Steady Boxing (RSB) Course

Eligible participants were informed about the RSB development project [30,31]. Participants attended 2 sessions per week. Classes were delivered on Tuesdays and Thursdays of each of the 4 weeks of the experiment (8 sessions in total). The training sessions were led by the same person, who is a certified RSB instructor and a trainer in charge of the sports club. The sessions lasted 90 min and included a 15 min warm-up, 30 min boxing exercises, 15 min strength and endurance exercises, 15 min activities focused on motor skills, and 15 min stretching and calming exercises. The warm-up included flexibility and coordination exercises in lying and standing positions. Warm-up exercises focused on multifaceted physical activity involving limb and trunk movements. Boxing exercises, including straight punches, and sickle and chin punches, were combined with cognitive and memory exercises involving the identification of movement patterns with assigned colors, numbers, or letters. Participants wore boxing gloves and hit boxing punching bags but did not confront other exercisers. Strength and endurance exercises were performed at moderate intensity and included high-intensity circuit training with 5–8 rounds lasting 10–30 s. Movement patterns in the strength and endurance section included bodyweight squats and hitting a boxing bag at high speed. This was followed by upper limb dexterity exercises such as tying shoes, lifting small objects from the ground, and threading beads. Finally, the sessions ended with the performance of calming exercises. Participants have been taking their medication consistently at a designated time each day, but not right before, during, or right after RSB exercise.

2.3. Test of Balance Ability

Postural stabilography was used to assess balance ability [32]. Posturography tests are categorized as methods for objective assessment of balance, based on the measurement of a signal representing the displacement of the point of application of the resultant ground reaction forces. The measurement of body oscillation indices is used to assess the functioning of the postural control system and to detect imbalances and risk of falls. Postural stability was measured in static, on a stationary substrate on the FreeMED BASE stabilometric mat (Italy) with the FreeSTEP 2.0 software. The device used allows the analysis of the distribution of foot pressure forces on the ground, with a sampling frequency of 250 Hz in real time, and guarantees repeatability and objectivity of measurements. Two measurements were conducted based on the standard Romberg test procedure: the first measurement involved a 30 s test of standing still and barefoot with eyes open, and the second was a 30 s test of standing still and barefoot with eyes closed. During the testing procedure, the subjects were belayed to prevent falls. Measurements were taken before the start of each training session and immediately afterwards for the following 4 weeks.

The analyzed stabilometric parameters measuring the range of center of pressure (CoP) deviation were as follows: total path length (PL) of foot pressure on the ground; confidence ellipse area (CEA) (defined as the smallest ellipse that covers 95% of the points of the CoP diagram); mean velocity (MV) (defined as the total length traveled by the CoP in 30 s); root mean square (RMS) (defined amplitude of the sway amplitude in the medial–lateral direction); (X-RMS); amplitude of the root mean square of the sway amplitude in the anteroposterior direction (Y-RMS).

2.4. Statistical Analyses

Using the Shapiro–Wilk W-test, it was found that the values obtained for the CoP displacement range did not have a normal distribution, so the data were logarithmized. Comparisons between groups of eyes open and closed were performed using the ANOVA split-plot test. An ANCOVA was conducted as an additional analysis to assess the potential impact of age, body mass, and height on the results, since preliminary diagnostics indicated moderate correlations with the outcome (up to r = 0.57) and supported the homogeneity of regression slope assumption (no significant covariate × group interactions). The ANOVA test for repeated measures was used to assess the significance of differences in the analyzed parameters between PG average data before (pre) and after the training unit (post), and between eyes open and closed. Detailed post hoc comparisons between pairs of means were made using the HSD Tukey test. Partial eta-squared (η²) was used as a measure of effect size. When analyzing PG individual values, the averaged pre- and post-data from all training units in which the subject participated in during the experiment were considered. This means that for each subject separately, one group of data was the results of all his measurements before training (pre), and the other group consisted of all his measurements after training (post). Relationships between values were assessed using Pearson’s correlation. All analyses were performed using STATISTICA (TIBCO Software Inc., San Ramon, CA, USA (2017). STATISTICA (data analysis software system), version 13. The level of p < 0.05 was used to assess the significance of effects.

3. Results

ANCOVA indicated that variables such as age, mass, and height had a marginal impact on the results of the comparative analysis between the groups. None of the analyzed variables served as significant predictors (all p ≥ 0.23) or moderators, and their interactions with the task performance variant factor (EO/EC) were also found to be irrelevant (all variant × covariate p ≥ 0.07). Therefore, ANOVA was determined to be the more appropriate method for subsequent analyses, and its results are reported as the primary analysis. The comparison of stability parameters reveals significant differences (PG vs. CG) when testing with both open and closed eyes (Group × Test) only for CEA (F = 8.070, p = 0.008, η² = 0.206); however, for the other parameters, there was no significance: CoP path length (F = 0.520, p = 0.476, η² = 0.016) (Figure S1), CoP MV (F = 0.422, p = 0.520, η² = 0.013), X-RMS (F = 2.433, p = 0.129, η² = 0.073), and Y-RMS (F = 0.758, p = 0.391, η² = 0.024). Only the post hoc analysis revealed more significant dependencies and differences, as shown in

Table 2. Mean ± SD of stabilometric variables in standing with both feet with eyes open and closed in Parkinson’s (PG) and control (CG) groups. The HSD Tukey post-hoc test was used to compare pairs of means.

Stabilometric Variables	PG (n = 18)	CG (n = 15)	PG vs. CG (Post-Hoc)
PL (mm)
EO	266 ± 105	172 ± 32	p = 0.007
EC	328 ± 199	211 ± 40	p = 0.023
EO vs EC (post-hoc)	p = 0.062	p = 0.003
CEA (mm2)
EO	314 ± 380	64 ± 104	p < 0.001
EC	305 ± 391	121 ± 128	p = 0.041
EO vs EC (post-hoc)	p = 0.806	p = 0.017
MV (mm/s)
EO	9.1 ± 3.5	5.8 ± 1.1	p = 0.004
EC	10.8 ± 6.5	6.9 ± 1.4	p = 0.012
EO vs EC (post-hoc)	p = 0.088	p = 0.019
X-RMS (mm)
EO	0.35 ± 0.15	0.23 ± 0.05	p = 0.009
EC	0.57 ± 0.30	0.30 ± 0.07	p < 0.001
EO vs EC (post-hoc)	p < 0.001	p = 0.019
Y-RMS (mm)
EO	0.27 ± 0.12	0.17 ± 0.05	p = 0.024
EC	0.47 ± 0.25	0.36 ± 0.22	p = 0.047
EO vs EC (post-hoc)	p < 0.001	p = 0.001

EO = eyes open; EC = eyes closed; PL = CoP path length; CEA = 95% confidence ellipse area; MV = mean velocity; X-RMS = medial–lateral mean square root; Y-RMS = anterior–posterior mean square root.

. In PG, there were no statistically significant differences in CoP PL, CEA, or MV between measurements with eyes open and closed (p > 0.05). Only in terms of X-RMS (p < 0.001) and Y-RMS (p < 0.001) excursions were the range for closed eyes significantly greater than with open eyes. In the CG, all parameters with closed eyes were significantly larger than with open eyes (p < 0.05). On the other hand, in the intergroup comparison, the CEA outlined by the center of gravity movement was more than twice as large in the PG as in the CG. The other body stability parameters analyzed were more than 50% greater (statistically significant differences, p < 0.05) in PG in both the open-eyed and closed-eyed tests than in CG. It is also worth noting that there is a much greater variation in results in the test group than in the control group, as evidenced by the standard deviation of results in both open-eyed and closed-eyed standing being several times greater.

ANOVA results for the Parkinson’s group indicated significant differences in the combination of eyes open–closed and pre–post measurements regarding the CoP path length (F = 6.1546, p = 0.001, η² = 0.278), CoP MV (F = 4.505, p = 0.007, η² = 0.209), X-RMS (F = 19.981, p < 0.001, η² = 0.540), and Y-RMS (F = 23.768, p < 0.001, η² = 0.583), and no significant differences in CEA (F = 1.118, p = 0.351, η² = 0.062). A thorough post hoc analysis of specific variables is presented in

Table 3. Mean ± SD of stabilometric variables in standing with both feet with eyes open and closed pre- and post-training in the Parkinson’s group. The HSD Tukey post-hoc test was used to compare pairs of means.

Stabilometric Variables	Pre (n = 18)	Post (n = 18)	Pre vs. Post (Post-Hoc)
PL (mm)
EO	266 ± 105	290 ± 142	p = 0.586
EC	328 ± 199	337 ± 172	p = 0.722
EO vs EC (post-hoc)	p = 0.065	p = 0.085
CEA (mm2)
EO	314 ± 380	399 ± 584	p = 0.952
EC	305 ± 391	402 ± 747	p = 0.934
EO vs EC (post-hoc)	p = 0.629	p = 0.670
MV (mm/s)
EO	9.1 ± 3.5	9.9 ± 4.7	p = 0.553
EC	10.8 ± 6.5	11.2 ± 5.6	p = 0.653
EO vs EC (post-hoc)	p = 0. 097	p = 0.136
X-RMS (mm)
EO	0.35 ± 0.15	0.39 ± 0.19	p = 0.560
EC	0.57 ± 0.30	0.59 ± 0.27	p = 0.940
EO vs EC (post-hoc)	p < 0.001	p < 0.001
Y-RMS (mm)
EO	0.27 ± 0.12	0.29 ± 0.17	p = 0.993
EC	0.47 ± 0.25	0.48 ± 0.26	p = 0.999
EO vs EC (post-hoc)	p = 0.001	p = 0.001

EO = eyes open; EC = eyes closed; PL = CoP path length; CEA = 95% confidence ellipse area; MV = mean velocity; X-RMS = medial–lateral mean square root; Y-RMS = anterior–posterior mean square root.

. The CoP path length values by measurement time were not statistically significantly different, regardless of the measurement protocol with eyes open (p = 0.586) or closed (p = 0.722). Similarly, no significant differences were noted between pre- and post-training averaged values for the CEA (p = 0.952, p = 0.934), as well as for the CoP MV (p = 0.553, p = 0.653) or the X-RMS (p = 0.560, p = 0.940) and Y-RMS (p = 0.993, p = 0.999). It is noteworthy, however, that sway amplitudes in both the frontal (p < 0.001) and sagittal (p < 0.001) planes were significantly larger in measurements with eyes closed.

As the mean values showed no significant differences between the pre- and post-training body stability parameters, and given the large standard deviation of the data, we decided to look at the values and individual changes in CoP path length for open and closed eyes. It turned out that, averaged over the training units analyzed, the values between pre- and post-training measurements varied individually with open eyes from −37% to 97% (Figure S2) and with closed eyes from −27% to 50% (Figure S3). In the majority (12 subjects), path length increased after training. However, in six subjects, the training unit had a positive effect on postural stability (path length was shorter after training than before).

Using the Pearson’s correlation coefficient, the significance of the relationship of CoP path length with the subjects’ body composition indices and other time parameters was determined (

Table 4. Correlation coefficients (r) and 95% confidence interval (CI) between CoP path length and body mass and height, as well as age, training experience, and length of illness of subjects.

	Pre EO	Pre EC	Post EO	Post EC
Body height	r = −0.220 CI (−0.620, 0.290)	r = −0.266 CI (−0.650, 0.230)	r = −0.171 CI (−0.588, 0.325)	r = −0.248 CI (−0.637, 0.253)
Body mass	r = −0.238 CI (−0.631, 0.263)	r = −0.239 CI (−0.634, 0.259)	r = −0.420 CI (−0.738, 0.067)	r = −0.363 CI (−0.707, 0.130)
Age	r = 0.471 CI (−0.036, 0.782)	r = 0.399 CI (−0.101, 0.738)	r = 0.195 CI (−0.316, 0.617)	r = 0.353 CI (−0.153, 0.713)
Training period	r = −0.161 CI (−0.601, 0.329)	r = −0.180 CI (−0.608, 0.329)	r = 0.174 CI (−0.335, 0.604)	r = −0.023 CI (−0.499, 0.462)
Length of disease	r = 0.309 CI (−0.201, 0.688)	r = 0.329 CI (−0.180, 0.699)	r = 0.637 a CI (0.225, 0.856)	r = 0.492 b CI (0.014, 0.786)

Pre/post EO = Eyes Open before/after activity; pre/post EC = Eyes Closed before/after activity. ^a correlations significant at p = 0.006; ^b correlations significant at p = 0.045

). Statistically significant (p < 0.05) directly proportional correlations were only recorded between CoP path length obtained after a training unit in both open-eye and closed-eye measurements and duration of illness. Height and mass, as well as age and training duration, did not correlate significantly with body stability parameters.

4. Discussion

With the rapid development and growing popularity of the RSB program among people with PD, obtaining detailed data on its impact on this patient group becomes crucial [33]. RSB is designed to improve patients’ motor function, balance, and overall quality of life. Research to date has mainly focused on small samples, which limits the ability to generalize results. Nevertheless, indications are suggesting that participation in regular, 90 min sessions of RSB once a week has physiological and psychological benefits and is associated with improvements in gait speed, overall mobility, motor outcomes, quality of life, decreased fatigue and fear of falling, and confidence in their ability to complete daily tasks [34,35,36,37].

PD causes a significant reduction in the ability to maintain a stable standing position, which was confirmed in comparative measurements with the control group. It is noteworthy that among PD subjects, baseline stability parameters did not differ significantly between open- and closed-eye trials, whereas in CG subjects, closing the eyes caused a significant deterioration in parameters. Similar results were obtained by Paolucci et al. [38], indicating that the length of CoP fluctuation was shorter in CG under open-eye conditions compared to closed-eye conditions, but in patients with PD, the effect of vision was not significant. In the present study, the only parameters that were weaker in the PG when the eyes were closed appeared to be the anteroposterior and medial–lateral fluctuations. A second phenomenon specific to the patient group was that the scatter of results was more than three times greater than in those without diagnosed disease. This demonstrates the strongly individualized stability parameters in individual subjects.

Nevertheless, keeping PD patients physically active is a major challenge. The gradual decline in their motor skills leads to a reduction in the effectiveness of intervention exercises in the long term. In this context, it may be crucial to focus on strategies that support a steady increase in physical activity and its regular maintenance, as evidenced in the literature [39,40,41].

The averaged data for all subjects show a tendency for the analyzed body stability parameters to deteriorate after training. However, given the lack of statistical significance between pre- and post-results and the large standard deviations, an analysis of individual results was applied. It turned out that for one-third of the subjects, the training load had a positive effect on the maintenance of body stability (CoP path length decreased after training), and for two-thirds a negative effect (CoP path length increased after training). In this approach, it can be seen that individual post-training performance ranged in PG from 37% better to 97% worse than before training. It seems, therefore, that the analysis and diagnosis of body stability in Parkinson’s patients should be individualized, and the different responses to exercise should contribute to further research in this area.

It is presumed that this is influenced by physiological mechanisms that may explain the deterioration of stability performance immediately after training. Intense exercise, such as RSB, may lead to short-term muscle fatigue, which affects the ability to maintain balance. On the other hand, exercise can stimulate long-term neuroplasticity, which warrants analysis in future research. As selected studies show, exercise promotes the release of neurotrophic factors, which promote the regeneration of dopaminergic neurons and may contribute to improved motor function in the long term [42,43,44,45].

The obtained data are consistent with the study by Combs et al. [30,31], which found that motor performance after RSB classes was variable, with only two of six participants showing symptom improvement. Similarly, in the work of Regan et al. [21], only seven out of ten participants improved their results in the Timed Up and Go test after the RSB training. On the other hand, Papa et al. [46] recorded a statistically significant improvement in balance and functional mobility in the following tests: BBS, TUG, 5×STS. Posturographic analysis by Sebastia–Amat et al. [47] showed that all variables worsened as the disease progressed. Significant differences were found for all variables, except for mean Y. The authors showed that posturographic variables correlated with clinical balance tests. It was observed that postural stability deteriorated with disease progression, and the tests conducted between disease stages were only found to be significant between stages 1 and 3 on the H&Y scale. They indicated that this method could be very useful as a complementary tool for monitoring disease progression. In the present study, significant deterioration in posturographic variables was also mostly observed, although the participants’ response to RSB physical activity varied widely individually. The results are consistent with the hypothesis of Mitchell et al. [48], who indicate that medial–lateral sway is a consequence of the response that seeks to reduce anterior–posterior sway, which is a risk for people with PD. According to a study by Chastan et al. [49], medial–lateral sway was more sensitive in detecting PD progression and more predictive of future PD decline.

A limitation of the study is the relatively small sample size, which may have failed to detect statistical significance for moderate effects. Before the start of the study, no minimum sample size of participants was set to have a high chance of detecting large effects. The research was carried out on the maximum available research sample, as it was important to determine not only the high-power test relationships, but also the trends in the relationships. They may also have application significance in the studied group. Another limitation is the lack of inclusion of the control group in the RSB program in its comparison of results with PD patients. In the experiment conducted, only the effects of single efforts within the RSB program were analyzed, whereas in subsequent studies, the measurement period should be extended in order to assess the effect of the training cycle on changes in postural stability parameters.

5. Conclusions

In conclusion, participation in a single unit of RSB-based physical activity did not demonstrate a consistent pattern of improvement or decline in participants’ balance ability immediately post-exercise. It is important to note that the data obtained from individuals with PD should not be generalized; rather, for safety reasons, results must be analyzed on an individual basis. It has been proven that patients with PD rely on increased CoP swing length and ellipse area to maintain their balance, and they do not benefit from a sense of sight for static postural control as healthy individuals do. The findings of this study indicate that a longer duration of diagnosed PD is associated with a greater impact of RSB exercises on the deterioration of postural stability after a single workout. This suggests that it is essential to tailor activities to the specific stage and duration of the disease.