, Na-eun Byeona, Wan-hee Leea* 
This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.Stroke is a disease in which blood flow to the brain is blocked or blood circulation in the brain is impaired due to rupture of blood vessels in the brain, resulting in loss of neurological function [1], Various symptoms vary depending on the site and degree of damage, and the most common symptoms include muscle weakness in the upper and lower limbs due to incomplete or complete hemiplegia in the opposite body of the brain lesion site, sensory and perceptual abnormalities, and cognitive loss [2]. Most stroke patients experience hemiplegia, in which one side of the body is paralyzed, which shifts the center line of the body toward the non-paralytic side and causes constant weight load on the non-paralytic lower extremities, resulting in an imbalance in posture and disrupting normal weight movement, which is affected by functional activities in daily life such as standing up in a sitting position, sitting up in a standing position, walking, and climbing stairs [3, 4]. Stroke patients' balance defects are caused by decreased sensory information, weakness of paralysis side muscle strength, and disturbance in muscle activation period [5], As a result, problems such as not being able to maintain the center of the body or not being able to perform activities such as exercise occur [6, 7]. This increases the risk of falling [8], Makes independent walking difficult [9], It has a direct impact on individual autonomy and quality of life [10]. In recent years, the use of virtual reality has been recommended for functional recovery after stroke [11].
Virtual reality rehabilitation therapy provides external stimulation to stroke patients to stimulate their motor senses and is provided as an effective tool for the rehabilitation of stroke patients [12]. Virtual reality training creates scenarios in a virtual environment interface that simulate events or objects appearing on a computer, allowing users to feel as if they are actually experiencing them. It includes all senses and stimulates the brain in a multisensory way, enhancing motivation and enjoyment in environments like games [13]. The types of Virtual Reality (VR) can be broadly categorized into Non-immersive VR, Fully Immersive VR, Augmented Reality (AR), Mixed Reality (MR), and Extended Reality (XR) [14]. Among these, clinically, Virtual Reality can be categorized into "Non-immersive" and "Fully Immersive" based on the degree to which the virtual environment and its interacting users are separated from the physical environment [15]. Non-immersive virtual reality refers to a virtual environment displayed on a monitor screen and manipulated through a mouse or controller. While lacking the sensation of being present in actual virtual reality, it offers the advantage of experiencing both the real and virtual worlds simultaneously [14]. Fully immersive virtual reality removes information from the real world and replaces it with computer-generated data, providing a sensation of actually being present in the virtual world [16, 17]. However, research consistently reports the effectiveness of using virtual reality in rehabilitation to recover functional impairments caused by strokes [18, 19], Interventions involving virtual reality primarily focus on upper limb rehabilitation after stroke [20, 21]. Specifically, there is a lack of research focusing on fully immersive virtual reality for balance and gait rehabilitation, resulting in very limited evidence supporting its efficacy [22]. Also, During the first two years following a stroke, rehabilitation treatment time is guaranteed, but it decreases after that period (Leigh, Kim, Sohn, Chang, & Paik, 2022). The physical function of stroke patients peaks approximately six months after the stroke and then gradually starts to decline (Dhamoon et al., 2009). Therefore, including patients who are more than two years post-stroke allows us to compare and analyze the long-term effects of various rehabilitation programs. Therefore, we aim to investigate the effects of applying balance training using fully immersive virtual reality devices on the balance and walking abilities of stroke patients.
This study focused on stroke patients admitted to a hospital located in Bundang-gu, Seongnam-si, Gyeonggi-do, Korea. The necessary sample size was calculated using G*Power software (version 3.1.9, University Düsseldorf, Germany), with alpha set at 0.05 and power at 0.8. An effect size of 0.45 was determined based on the Berg Balance Scale (BBS) from a prior pilot test. Thus, a total of 51 participants was required, and the study included three groups of 20 individuals each, accounting for possible dropouts by adding 3 participants per group. Inclusion criteria included a diagnosis of stroke for at least 2 years, a functional gait category score of 3 or higher, a score of 41 or higher on the Berg Balance Scale, and a score of 24 or higher on the Korean Mini-Mental State Examination (K-MMSE). Exclusion criteria involved individuals with other neurological conditions and those with visual or hearing impairments. The study period was from April 10, 2023, to July 16, 2023. Before the experiment began, informed consent was obtained from all participants who met the inclusion criteria. The study received approval from the Institutional Review Board of Bundang Jesaeng Hospital (Approval No: DMC 2023-03-002).
Sixty participants were chosen for the trial, and to minimize selection bias, a research assistant not involved in the intervention used the permuted block randomization of the randomization program (Random allocation software version 1.0, M. Saghaei MD, Department of Anesthesia, Isfahan University of Medical Sciences, Isfahan, Iran) to divide 20 into three groups according to the order of subject recruitment. The block size was designated, and 20 people were assigned to each group. Treatment was conducted twice daily for 30 minutes each session over 8 weeks. The VRT group performed VR and traditional physical therapy for 30 minutes each for 60 minutes, the VR group performed VR training for 30 minutes each for 60 minutes, and the TPT group performed traditional physical therapy for 30 minutes each for 60 minutes. In the VRT group, two people were eliminated due to early discharge and abandonment, and in the VR group, one person was discharged early, and in the TPT group, one person was discharged early and two people gave up halfway, and finally 54 subjects participated in the study (Figure 1). The general average characteristics of the subjects who finally participated in this study were 31 men and 23 women, age 58 years, height 165, weight 63, onset date 53 months, infarction 41 patients, hemorrhage 13 patients, left paralysis, 22 patients, right paralysis, 32 patients, cognitive score was 25 points (Table 1).
Virtual Reality training was conducted using the Oculus Quest 2, a standalone VR headset known for its portability and ease of use. Participants engaged in balance training using commercially available sports games specifically designed for VR platforms. The selection of games aimed to simulate real-world activities while challenging participants to perform goal-oriented movements in a standing position. We conducted a pre-evaluation on all patients to determine their balance ability and then designed a VR treatment session. Throughout every session, therapists and support staff monitored the patients' condition continuously to ensure safe participation, providing immediate assistance as needed. Safety education was conducted before each session to familiarize patients with the VR equipment and environment, and each game was practiced once before proceeding.
The VR intervention consisted of three games: Tennis, Bowling, and Air Gun. Training intensity was divided into beginner, intermediate, and advanced. Weeks 1-2 were conducted at beginner level, weeks 3-5 were conducted at intermediate level, and weeks 6-8 were conducted at advanced level. The duration of one session was about 8 minutes, with 8 minutes of virtual reality training and 2 minutes of rest, so each session took 10 minutes. Therefore, a total of 3 sets of each training were performed, 1 set each. In the Tennis game, participants faced an in-game AI opponent and used the handheld touch controllers to simulate hitting a virtual ball with a racket. All virtual reality training sessions were conducted by holding the controller with the non-paretic hand. The Bowling game required participants to roll a virtual bowling ball to knock down pins, promoting upper extremity movement without adherence to typical bowling postures. The Air Gun game involved aiming and shooting at targets flying in various directions, encouraging participants to engage in dynamic movements while maintaining balance.
Each VR training session lasted 30 minutes, and participants in the VRT group received an additional 30 minutes of traditional physical therapy, resulting in a total intervention duration of 60 minutes per session (Figure 2).
Traditional physical therapy sessions were conducted by experienced physical therapists trained in Bobath therapy [23] and proprioceptive neuromuscular facilitation techniques [24]. The therapy sessions were tailored to meet each participant's specific requirements, concentrating on enhancing joint flexibility, muscle power, and overall functional movement. Specific exercises included passive and active range of motion exercises, mat exercises targeting core stability, and weight-bearing activities to promote balance and coordination.
Participants in the TPT group received 60 minutes of traditional physical therapy per session, with no additional VR training.
The Berg Balance Scale (BBS) is a tool used to evaluate balance in individuals prone to falling, especially elderly individuals or those with neurological conditions. It includes 14 items, each scored on a 5-point scale from 0 to 4, with a maximum possible score of 56 points [25]. This tool is highly reliable and valid for assessing balance ability, showing an intra-rater reliability of r＝0.99 and an inter-rater reliability of r＝0.98 [26].
The Timed Up and Go (TUG) test is utilized to assess balance and mobility in individuals who have experienced a stroke. This single-task evaluation involves walking along a 3-meter straight path, including making a 180-degree turn [27]. The test is conducted at a comfortable walking speed, repeated three times, and the average time is recorded. It demonstrates high reliability and validity, with intra-rater reliability at r＝0.99 and inter-rater reliability at r＝0.98 [28].
The 10 m walk test is a commonly used scale to evaluate walking speed [29]. Subjects were asked to walk a distance of 14m at a comfortable speed considering accelerators and decelerators, and this was done three times and the average value was calculated(Arya et al., 2019). This measurement tool showed significant reliability (0.95-0.99) and high validity (0.60-0.94) in stroke patients [30].
In this study, a gait analyzer (Zebris FDM-T System, Zebris Medica GmbH, Isny, Germany) was employed for measuring the participants’ gait ability. The gait analyzer used in the study is a system that integrates a pressure measurement sensor and a treadmill, which collects pressure signals as the participant walks on the treadmill and automatically analyzes 14 spatiotemporal parameters related to gait through Zebris FDM-T software (version 1.18.44) [31]. In this study measured, among 14 gait parameters, velocity, cadence, stride time, step length of paretic side, stride length, and single limb support of paretic side. Zebris FDM-T has an intraclass correlation coefficient (0.96) are high [32].
The Activities-specific Balance Confidence (ABC) scale comprises 16 activities and measures an individual's self-efficacy in balance functions while inversely assessing the fear of falling. To evaluate balance, participants are asked questions about various daily life scenarios, with responses recorded at 10% intervals from 0% (no confidence) to 100% (complete confidence). This study measured changes in the total score across the 16 items. The ABC scale has demonstrated excellent reliability, with a test-retest reliability of ICC 0.85 (95% CI: 0.68 – 0.93) over a one-month interval in patients with chronic stroke [33].
The statistical analysis of this study was performed using SPSS (Version 21, SPSS Inc., Chicago, IL, USA). The chi-square test was used to test the homogeneity of categorical variables, and the independent t-test was used for continuous variables of general characteristics and dependent variables. The paired t-test was applied to analyze differences within groups before and after training, and one-way ANOVA was used to compare differences between groups. A significance level of α＝0.05 was set for all statistical analyses.
This study included 60 participants in total. In the VRT group, 2 participants were excluded due to early discharge and dropout. In the VR group, 1 participant was discharged early. In the TPT group, 1 participant was discharged early and 2 participants dropped out. Consequently, 54 participants completed the study (Figure 1).
The general characteristics of the participants are as follows (Table 1).
The changes in balance ability are as follows (Table 2):
All groups demonstrated significant improvements in the Berg Balance Scale (BBS) scores from pre- to post-intervention (p<0.05). When comparing the groups, both the VRT and VR groups showed significantly greater improvements than the TPT group (p<0.05).
All groups exhibited significant improvements in the Timed Up and Go Test (TUG) before and after the intervention (p<0.05). The VR group, in particular, showed the most notable changes compared to the other two groups (p<0.05).
The changes in temporal walking ability are as follows (Table 3):
All groups demonstrated significant improvements in the 10-meter walking test (10MWT) from pre- to post-intervention (p<0.05). When comparing the groups, the VR group exhibited significantly greater improvements than the other two groups (p<0.05).
Significant changes in velocity were observed in all groups before and after the intervention (p<0.05). Notably, the VR group demonstrated the most substantial changes compared to the other two groups (p<0.05).
No significant changes were observed in cadence before and after the intervention in all groups.
The changes in spatial walking ability are as follows (Table 3):
While significant changes in step length were observed before and after the intervention in the VRT and VR groups (p<0.05), no significant changes were found in the TPT group. When comparing the groups, the VR group exhibited significant improvements compared to both the VRT and TPT groups (p<0.05).
Significant changes in stride length before and after the intervention were observed in both the VRT and VR groups, excluding the TPT group (p<0.05). However, no significant differences were found between the three groups.
Except for the TPT group, the other two groups showed significant changes in single limb support (SLS) before and after the intervention (p<0.05). In the comparison between groups, the VR group showed significant improvements compared to the TPT group (p<0.05).
The changes in confidence are as follows (Table 4): Except for the TPT group, the other two groups showed significant changes in the Activities-specific Balance Confidence (ABC) scales before and after the intervention (p<0.05). In the comparison between groups, the VR group showed significant improvements compared to the other two groups (p<0.05).
The purpose of this study is to investigate the impact of balance training using fully immersive virtual reality (VR) devices on the balance, walking ability, and confidence of chronic stroke patients. Regarding balance ability, the study results showed significant effects on the Berg Balance Scale (BBS) scores and the Time Up and Go test (TUG) across all groups. Notably, the two groups that received VR training showed greater improvements compared to the traditional physical therapy group. These results are consistent with the findings of De Rooij et al [3], and several previous studies [34-36]. Lee et al. [37] investigated the impact of VR training on the balance abilities of 50 stroke patients and found significant effects on BBS and TUG, with greater improvements over time. VR training is superior to traditional physical therapy in enhancing new motor and sensory abilities, improves motivation by providing a multi-sensory learning environment [29], and enhances the ability of the central nervous system to adapt to complex external environments, thereby improving physical control [30]. Therefore, the improvement in balance ability through VR is considered to be due to the enhanced ability to adapt to external environments provided by a multi-sensory learning environment, allowing better control of body position and direction.
In the study of temporal walking variables (10m walking test, velocity, cadence), significant effects were observed in the 10m walking test and velocity, but not in cadence, across all groups. The two groups that received VR training showed greater changes compared to the group that received traditional physical therapy. These results are consistent with the findings of Ghai et al [29]. Additionally, the systematic review by Lee et al [38] found that VR training is effective in improving the 10m walking test and walking speed in chronic stroke patients, which aligns with the results of Kim et al [39], who conducted VR training on 10 stroke patients and found improvements in walking speed. There is a positive relationship between weight-bearing ability and walking ability [31]. According to a previous study targeting 18 stroke patients using a fully immersive virtual reality device, balance training using a touch controller-based virtual reality device induces trunk movement in more diverse directions and improves posture strategies for this, thereby enhancing walking ability [33]. Therefore, it is believed that temporal changes in gait variables through VR are improved as weight bearing capacity and posture strategy ability are improved. Furthermore, cadence, which represents step frequency, is not directly related to increased walking speed [32], which explains the lack of effect.
In terms of spatial walking ability, significant improvements in step length, stride length, and single-leg support time were observed in the two VR-trained groups compared to the traditional physical therapy (TPT) group, which did not show such improvements. These results are consistent with the findings of Kim et al [39]. In the study conducted by Lee et al [40], where 10 chronic stroke patients underwent VR training for four weeks, VR training showed significant effects on step length and stride length, with greater effects over time. Additionally, Kim et al [39] found significant changes in step length and stride length after VR training on 10 stroke patients, and Cho et al [40] observed significant improvements in single-leg support. VR training enhances environmental diversity and enjoyment, enabling challenging balance training and dual-task training experiences. This leads to increased confidence and improvements in spatial walking variables through enjoyable experiences in various environments [33]. Furthermore, increased stability can improve spatiotemporal walking parameters [34]. Therefore, the changes in spatial walking ability observed in this study are thought to be due to the increase in stability and confidence provided by VR training.
In terms of activity-specific balance confidence, significant effects were observed in the two VR-trained groups, excluding the TPT group. This is consistent with the findings of Singh et al [35], showing that VR training is effective in reducing fear of falling and increasing confidence. De Rooij et al [36] found that VR training provides stroke patients with insights into their capabilities and limitations, enhancing confidence in their walking abilities. Kawk [33] found that VR training increases confidence in stroke patients by providing various environments, enabling them to return to daily life. Therefore, these results suggest that the increase in confidence is due to the insights provided by VR training and training in diverse environments.
In this study, 3 people were discharged early and 3 people dropped out, resulting in a total of 6 dropouts. The early discharged patient was discharged to another hospital, and the three who dropped out were due to schedule changes that prevented them from continuing to participate in the study. In order to reduce dropout due to early discharge, it seems necessary to collaborate with other hospitals to find ways to allow study participants to continue the study after transfer, and to reduce dropout due to schedule changes, provide more flexible schedule adjustment options. It is believed that this will be necessary.
Future research needs to proceed in the following directions: First, research is needed to compare and analyze the effectiveness of VR treatment for patients with various types of stroke. For example, by investigating differences in treatment effectiveness between mild, moderate, and severe patient groups, tailored rehabilitation programs could be developed. Second, through research comparing the effectiveness of VR treatment in the early and late stages of rehabilitation, the optimal treatment method for each stage can be derived. Third, research examining the long-term effects of VR training is needed. This will track the patient's condition for a certain period of time after treatment and provide information on the continued effectiveness of VR treatment and prevention of recurrence.
This study had several limitations. First, the limited sample size and study at a single institution may limit the generalizability of the results. Second, the study period was relatively short, so long-term effects could not be evaluated. Third, critically ill patients who were unable to participate in standing VR therapy or patients with severe balance impairment were excluded from the study. To compensate for these limitations, future studies need to conduct larger sample sizes, multicenter studies, and include patients with different severities.
This study investigated the effects of fully immersive virtual reality balance training on balance, gait, and confidence in chronic stroke patients. The results confirmed that balance training through virtual reality positively impacted balance, gait ability, and confidence, with greater effects observed with longer training durations. Additionally, traditional physical therapy showed limited improvement in spatial gait ability for patients who had suffered from chronic stroke for more than two years. Therefore, a therapeutic approach using virtual reality is recommended to improve balance and gait ability in chronic stroke patients.
The author has no potential conflicts of interest in relation to the authorship and/or publication of this article.
General Characteristics of Subjects (N＝54)
| VRT group (n＝18) | VR group (n＝19) | TPT group (n＝17) | F/X2(p) | |
|---|---|---|---|---|
| Height (cm) | 165.14 (8.01)a | 166.11 (7.70) | 166.58 (7.74) | 0.153(0.859)c |
| Weight (kg) | 61.40 (8.54) | 64.94 (6.06) | 65.14 (7.21) | 1.485(0.236)c |
| Age (year) | 57.72 (11.28 | 60.47 (11.42) | 57.82 (10.26) | 0.370(0.692)c |
| MMSE-K (score) | 26.00 (1.53) | 25.95 (1.47) | 25.94 (1.56) | 0.008(0.992)c |
| Onset (months) | 50.00 (17.26) | 60.42 (18.83) | 48.12 (15.20) | 2.714(0.076)c |
| Gender | ||||
| Male | 10(60.0％) | 11(53.3％) | 10(53.3％) | 0.041(0.980)b |
| Female | 8(40.0％) | 8(46.7％) | 7(47.7％) | |
| Diagnosis | ||||
| Infarction | 15(83.3%) | 14(73.7%) | 12(70.6%) | 0.858(0.651)b |
| Hemorrhage | 3(16.7%) | 5(26.3%) | 5(29.4%) | |
| Affected side | ||||
| Left | 8(44.4%) | 7(36.8%) | 7(41.2%) | 1.418(0.492)b |
| Right | 10(55.6%) | 12(63.2%) | 10(58.8%) | |
a Mean±SD. b Chi-square test. c One-way anova test. MMSE, mini-mental state examination. VRT group, virtual reality and traditional physical therapy. VR group, virtual reality. TPT, traditional physical therapy.
Changes in balance according to experimental method
| Variables | VRT group (n＝18) | VR (n＝19) | TPT (n＝17) | F | P | Scheffe | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Pre-test | Post-test | Change | Pre-test | Post-test | Change | Pre-test | Post-test | Change | ||||
| BBS (score) | 45.44±2.47a | 47.22±2.31 | 1.77±1.06*** | 46.84±1.50 | 49.42±1.89 | 2.57±1.12*** | 46.12±1.79 | 46.82±1.87 | 0.70±1.10** | 13.135 | 0.000 | C |
| TUG (sec) | 18.45±3.41a | 16.90±3.44 | -1.54±0.57*** | 17.81±3.01 | 15.45±3.62 | -2.36±1.05*** | 17.74±4.04 | 17.28±3.78 | -0.45±0.70** | 24.824 | 0.000 | C |
a Mean±SD. Signifiantly differences between pre and posttest (*p<0.05, **p<0.01, ***p<0.001). BBS, Berg balance scale. TUG, Timed up and go test. A, VRT group. B, VR group. C, TPT group.
Changes in Walking according to experimental method
| Variables | VRT group (n＝18) | VR (n＝19) | TPT (n＝17) | F | P | Scheffe | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Pre-test | Post-test | Change | Pre-test | Post-test | Change | Pre-test | Post-test | Change | ||||
| 10WMT (score) | 18.00±2.35a | 16.87±3.07 | -1.12±1.32** | 17.05±2.08 | 14.64±2.25 | -2.40±0.91*** | 17.41±1.71 | 16.76±2.2 | -0.27±0.82** | 13.066 | 0.000 | A·C |
| Velocity (km/h) | 1.70±0.55 | 1.96±0.46 | 0.26±0.17*** | 1.72±0.48 | 2.20±0.37 | 0.48±0.22*** | 1.71±0.60 | 1.81±0.63 | 0.05±0.13* | 19.162 | 0.000 | C |
| Cadence (step/min) | 82.39±13.20 | 82.61±13.10 | 0.22±1.16 | 82.26±21.19 | 82.84±20.36 | 0.57±1.92 | 82.71±21.60 | 83.88±20.73 | 0.52±3.33 | 0.292 | 0.748 | A·B·C |
| Step length (cm) | 29.77±11.06 | 30.44±10.77 | 0.66±0.90** | 30.63±9.61 | 31.53±9.70 | 0.89±1.10** | 30.29±10.52 | 30.12±10.39 | 0.88±1.93 | 4.073 | 0.023 | A·C |
| Stride length (cm) | 65.33±20.67 | 66.11±20.88 | 0.77±0.87** | 65.79±19.58 | 66.42±19.52 | 0.63±0.95** | 65.29±20.71 | 65.88±20.73 | 0.94±2.13 | 0.023 | 0.977 | A·B·C |
| SLS (%GC) | 27.23±7.13 | 27.51±7.00 | 0.27±0.55* | 27.17±6.23 | 27.90±6.18 | 0.72±0.45*** | 27.15±6.24 | 27.27±6.48 | 0.12±0.86 | 4.295 | 0.019 | C |
a Mean±SD. Signifiantly differences between pre and posttest (*p<0.05, **p<0.01, ***p<0.001). 10MWT, 10M walking test. SLS, Single limb support. A, VRT group. B, VR group. C, TPT group.
Changes in confidence according to experimental method
| Variables | VRT group (n＝18) | VR (n＝19) | TPT (n＝17) | F | P | Scheffe | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Pre-test | Post-test | Change | Pre-test | Post-test | Change | Pre-test | Post-test | Change | ||||
| ABC (score) | 983.89±343.27a | 1029.44±318.55 | 45.55±53.71* | 918.95±448.92 | 1031.05±475.03 | 112.10±83.63* | 882.35±461.74 | 911.18±432.72 | 28.82±83.73 | 6.316 | 0.004 | A·C |
a Mean±SD. Signifiantly differences between pre and posttest (*p<0.05, **p<0.01, ***p<0.001). ABC, Activities-specific balance confidence scales. A, VRT group. B, VR group. C, TPT group.
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