Abstract
Background There is a lack of studies related to virtual reality (VR)–augmented balance training on postural control in people with Parkinson disease (PD).
Objective The purposes of this study were: (1) to examine the effects of VR-augmented balance training on the sensory integration of postural control under varying attentional demands and (2) to compare the results with those of a conventional balance training (CB) group and an untrained control group.
Design A longitudinal, randomized controlled trial was used.
Setting The intervention was conducted in the clinic, and the assessment was performed in a research laboratory.
Patients Forty-two people with PD (Hoehn and Yahr stages II–III) were recruited.
Intervention The VR and CB groups received a 6-week balance training program.
Measurements The sensory organization tests (SOTs) of computerized posturography with single- and dual-task conditions were conducted prior to training, after training, and at follow-up. Equilibrium scores, sensory ratios, and verbal reaction times (VRTs) were recorded.
Results There were no significant differences in equilibrium scores or VRTs between the VR and CB groups. However, the equilibrium scores in SOT-6 (ie, unreliable vision and somatosensation) of the VR group increased significantly more than that of the control group after training. The equilibrium scores in SOT-5 (ie, unreliable somatosensation with eyes closed) of the CB group also increased significantly more than that of the control group after training.
Limitations The functional significance of the improvements in equilibrium scores in the SOTs was not known, and the sample size was small.
Conclusions Both VR and CB training improved sensory integration for postural control in people with PD, especially when they were deprived of sensory redundancy. However, the attentional demand for postural control was not changed after either VR or CB training.
People with idiopathic Parkinson disease (PD) commonly experience postural instability during daily activities.1 Some studies have suggested that postural instability is the underlying cause of falling in people with PD.2–4 Impaired somatosensation, visual sense, and smaller base of support are reported to be related to postural instability in people with PD.5 Furthermore, deficits in the central integration of vision, somatosensation, and vestibular systems,6–8 as well as a cortically mediated decline in attentional capacity,9,10 may contribute to postural instability in people with PD. A previous study has shown that balance training performed under various sensory input manipulations can improve sensory integrative ability of postural control in patients with hemiplegia.11 The question would be whether balance training with an emphasis on sensory integrative ability can affect postural control ability in people with PD in varying sensory environments and with varying attentional demands.
Virtual reality (VR) is an augmented reality-based therapeutic condition for motor and cognitive training, providing not only fundamental elements of motor learning (eg, repetitive practice and feedback)12 but also a virtual environment for attention and motivation.13 Only a few studies have examined the application of VR training in people with PD.14–16 Both Weghorst14 and Riess15 reported that an immobile, helpless person with PD could walk almost normally by enhancing visual feedback about self-motion with an augmented reality device. Albani and associates16 tested 10 controls and 2 women with PD by using common daily activities in the virtual environment and suggested that VR could work as an external stimulus for them to explore varying motor plans by the creation of mental images. However, no study has yet reported the effects of VR-augmented balance training on the sensory integrative ability for postural control in people with PD with varying attentional demands. In this study, a new dynamic balance board with a tilting function (which was controlled by body weight) was developed as a human-machine interface for VR training. The VR-augmented balance training with the dynamic balance board (ie, VR training) was designed to produce somatosensory challenges while the participant maintained balance during varying visual tasks.
The sensory organization test (SOT), a component of computerized dynamic posturography (CDP), provides a quantitative assessment of sensory integrative ability among the 3 main sensory systems (ie, vision, somatosensory, and vestibular systems) involved in balance and stability.17,18 The SOT consists of 6 sensory conditions: eyes open, eyes closed, sway vision, eyes-open sway support, eyes-closed sway support, and sway vision–sway support. Furthermore, the SOT can provide information related to the integration of all 3 systems for postural control to maintain balance.19
The purposes of this study were: (1) to examine the effects of VR training on sensory integration under single- and dual-task conditions and (2) to compare the results with those of a conventional balance training (CB) group and an untrained control group. The purpose of including an untrained control group was to eliminate the time effect of degeneration on the postural control of the people with PD. The null hypotheses were: (1) there were no significant training effects (ie, before training versus after training and at follow-up) on sensory organization (ie, on visual, somatosensory, and vestibular systems) and attentional demand, and (2) there were no significant group effects (ie, VR group versus CB group and control group) on sensory organization and attentional demand.
Method
Design Overview
This study was a prospective, single-blinded, randomized controlled trial designed to analyze the immediate and lasting effects of training. The estimated power was set at 0.8, with a confidence interval of 26, which yielded an estimated sample size of 14 participants for each group.
Participants and Recruitment
Participants were diagnosed by a neurologist as having idiopathic PD according to Gelb's diagnostic criteria.20 The people diagnosed with PD were screened by a physical therapist for study eligibility. The inclusion criteria were: (1) idiopathic PD, (2) intact cognition (Mini-Mental State Examination [MMSE] score >24),21 (3) Hoehn and Yahr (H-Y) stages II and III, (4) previous lack of participation in balance or gait training, and (5) able to follow simple commands and having no uncontrolled chronic diseases. The exclusion criteria were: (1) a history of other neurological, cardiovascular, or orthopedic diseases affecting postural stability and (2) on-off motor fluctuation and dyskinesia above grade 3 on the Unified Parkinson's Disease Rating Scale (UPDRS).22 Figure 1 shows that 67 patients attended the Center for Parkinsonism and Movement Disorder in National Taiwan University Hospital for initial physical screening from November 2007 to March 2008 and that 25 patients were excluded for not meeting the eligibility criteria (n=19) or declined to participate for personal reasons (n=6). A total of 42 patients were recruited for preintervention assessment and were randomized by the screening physical therapist into 3 groups by drawing an assignment card in a block (block randomized design). A posttraining assessment was conducted within 7 days after the 6-week training program (from January 2008 to May 2008), and a follow-up assessment was conducted 4 weeks after training (from February 2008 to June 2008). All participants signed a consent form, which was reviewed and approved by the Ethics Committee of National Taiwan University Hospital.
Flow diagram of total experimental procedure.
Approximately 2 hours after medication, the participants received the clinical assessments, including the UPDRS motor subsection and the MMSE, which were administered by one blinded, trained physical therapist. Based on the pharmacodynamics of levodopa (the onset is ∼20–40 minutes and the duration of effect is 2–4 hours after medication), the patients received the assessment at a late period of their on phase.23 Additionally, the basic data pertaining to patients such as age, duration of the disease, and medications currently used were recorded. The medications (either dopamine agonists or dopamine replacement anti-parkinsonian medications) were kept at consistent dosages throughout the course of study. The eligible participants then received a preintervention outcome assessment.
Following the preintervention outcome assessment, the participants were randomly allocated into the VR group, the CB group, or the untrained control group. Age-stratified randomization (55–64, 65–74, and 75–85 years) was used to ensure the numbers of participants at each age level were proportionate among groups. Participants in the VR and CB groups received VR and conventional balance training, respectively, for 6 weeks, but the CG group did not receive any physical therapy. Two licensed physical therapists were responsible for conducting the VR and CB training programs separately (ie, each provided one type of training), and the laboratory assessment for all participants was conducted by another licensed therapist who was blinded to the assignment and training of all 3 groups. During the entire experiment period, patients received training and follow-up assessments 2 hours after taking their medicine. No adverse effect was observed during training except that the patients might have a tendency to fall. However, the patients were guarded by the therapist to avoid falling, and no actual falling was reported.
VR Balance Training System
The hardware system for VR training in this study included a dynamic balance board, a 55.88-cm (22-inch) LCD screen, and a personal computer. The dynamic balance board was designed by the Cycling and Health Center, Taichung, Taiwan, and was composed of a tiltable footplate, dual-shaft hinge module, and sensor for interactive training (Fig. 2A). The dual-shaft hinge module allowed for the tilting movement of the plate in different directions, and the sensor detected the body-weight shift direction, then sent electric signals as the controller to drive the object (eg, simulated board) in the VR environment (Figs. 2B and 2C).
(A) Simplified mechanical structure of the dynamic balance board. (B) Virtual reality balance training system with the dynamic balance board. (C) Simulated outdoor environment (D) Simulated indoor environment.
The 3-dimensional (3D) VR games (using Virtools 3.5*) were developed by National Formosa University and authorized by the Cycling and Health Center. The first game-based VR experience was called Bang Bang Ball. While the participants played this game, 1 to 5 virtual balls sequentially appeared on a virtual plate that had a hole in the central position, and the virtual plate would move in the same direction as the dynamic balance board. The other VR game, called Simulated Board Driving, included an outdoor simulated environment (see park environment in Fig. 2C) with straight and circular movements and an indoor simulated environment (see living room in Fig. 2D) with multiple turns. The goal of Bang Bang Ball was to practice weight shifting in different directions for targeting, and the purpose of Simulated Board Driving was to control weight shifting in daily environments.
Intervention (Balance Training Programs)
The rationale for the intervention was to improve standing balance, and the dosage of exercise used was modified from the studies of Betker and associates24 and Hirsch and associates,25 in which balance rehabilitation was provided 2 to 3 times a week for 3 to 10 weeks. The present study provided training for 30 minutes twice a week for 6 weeks. No harness was used during training, and manual contact was provided if the patient showed a tendency to fall. No patient fell to the ground during training. The training programs were individualized for the participants in the VR and CB groups.
VR-augmented balance training.
Participants were in VR-augmented balance training while under the effects of their medication (2 hours after taking the medicine). In each session, the participants underwent 10 minutes of stretching exercises as a warm-up to increase the flexibility of the trunk, thighs, and shanks. Then, participants were instructed to stand on the VR balance board in front of the screen at a distance of 50 cm to receive 20-minute VR challenges. In the VR intervention, patients tried to navigate the dynamic balance board by moving their weight to control the simulated board in the virtual environment. Participants were instructed to use the ankle strategy if possible during the training.26 The VR training modes included 10 minutes of the 3D ball-rolling game and 10 minutes of indoor-outdoor virtual activities. The training program was designed to progress from simple to complex, and upper extremities were held to the side of the trunk or on the waist (Appendix 1) (see video recorded during the training program). The VR controlling system also was monitored by the therapist to increase the difficulty by reducing weight-shifting sensitivity and the direction of movement in the reverse mode (ie, a backward weight shift to drive the virtual board forward) of the dynamic balance board.
CB training.
Participants in the CB training were under the effects of their medication (2 hours after taking medicine). In each session, the participants underwent 10 minutes of stretching exercises and 20 minutes of intervention. The protocol of CB training was modified from a previous study in people with PD.24 In general, the training protocol was composed of 3 dimensions: (1) static stance, (2) dynamic weight shifting, and (3) external perturbations. For the static stance, patients were encouraged to stand on pieces of foam (each 4 cm thick) with eyes open or closed for approximately 60 seconds depending upon the patient's ability, and the difficulty was increased by adding more foam pieces and reducing the base of support (shoulder width/partial tandem/tandem) over 6 weeks (Appendix 2). For dynamic weight shifting, a physical therapist threw a ball in multiple directions, and patients had to catch the ball by stepping forward and laterally and squatting approximately 30 times depending upon the patient's tolerance. Patients were instructed to use an ankle strategy if possible during the training.26 In addition, a tiltboard was used as external perturbation to facilitate postural reflexes under unexpected destabilizing situations.
Assessment Procedure
The assessment procedure prior to training, after training, and at follow-up included: a single primary task (SOT while standing), a single secondary task (cognitive test while sitting), and a dual task (SOT plus cognitive test while standing). The sequence of the 3 tasks was randomly assigned.
Single primary task (while standing).
The SOT was performed using the SMART balance system† as follows. Participants stood barefoot on the force platforms while aligning their feet properly by manual instruction, and the standard foot position was checked across trials. During testing, participants wore a vest-like harness to prevent falling. All participants completed 2 SOT sessions, with a 5-minute seated rest between sessions. Participants were allowed to have 1 practice trial for each sensory condition to minimize any immediate practice effect between the first and second testing protocols.27 Patients were requested to stand as still as possible, and the force platforms recorded the center-of-pressure (COP) pathway to infer center-of-gravity (COG) sway. A fall was registered with an equilibrium score of zero when the patient required assistance or took a step away from the forceplates. Fair-to-good reliability of the SOT in older adults,28 in patients with stroke (intraclass correlation coefficient=.81),29 and in adults who were healthy in our own laboratory30 have been reported, but reliability of the SOT has not been reported for people with PD.
During testing, participants were instructed to stand as still as possible with their arms at their sides and eyes looking forward. Fifteen to thirty seconds' rest was allowed between sensory conditions. Three trials of each sensory condition (SOT-1 to SOT-6) were performed, for a total of 18 trials. The SOT assessed 3 sensory systems (visual, somatosensory, and vestibular systems) during standing under 6 sensory conditions (recorded as SOT-1 to SOT-6). The force platforms were fixed for conditions 1 to 3 and were sway referenced for conditions 4 to 6, and the sensory conditions with sway-referenced support would make the somatosensory information unreliable.31
Single secondary task (while sitting).
Participants were in a sitting position to receive 4 sessions of an auditory arithmetic subtraction task for practicing. In each session, 6 real and 4 false auditory signal trials were randomly distributed to prevent an anticipatory effect (33% catch trials).31,32 Participants were instructed to answer as quickly as possible by subtracting 1 after hearing the 2-digit number (ie, counting backward).33
Dual task (while standing).
Participants were instructed to stand as still as possible with the same rules as for the primary task. In addition, during 20 seconds of each SOT trial, a concurrent auditory arithmetic subtraction task was given in the middle of the trial (at 10 seconds). Participants were requested to subtract 1 as quickly as possible after hearing the 2-digit number.33 Three trials of each sensory condition were performed.
Outcome Measures
The outcome measures (ie, dependent variables) included the equilibrium scores at the 6 conditions of the SOT (ie, SOT-1 to SOT-6), sensory ratios (percentage), and the verbal reaction time (VRT) (milliseconds) during single and dual tasks. The equilibrium scores and sensory ratios were measured by computerized dynamic posturography (SMART Balance Master†) consisting of 2 movable AMTI force platforms‡ mounted with 5 strain gauges (sampling rate=100 Hz), a monitor providing visual feedback of the user's movement, and a visual surround. Variables of the SOT were analyzed by commercial software† and averaged in each condition for statistical analysis.
The VRT was measured with a microphone and a sound meter. During a dual task, the synchronized switch would start the SMART Balance Master and the personal computer at the same time, and the computer could produce a digital number 10 seconds later (written in Matlab 7.0)§ to the participant's ear phone. Then, the microphone could pick up the verbal response of the participant and send signals to a sound meter that was connected to a Biopac MP100 system‖ to have the VRT analyzed by the Acknowledge software.# Three trials of VRT in each sensory condition were averaged for statistical analysis.
Data Analysis
The equilibrium score was an index of postural stability under varying sensory conditions and was calculated by relating the peak anterior-posterior COG sway angle to the theoretical sway stability limit (ie, 12.5°).18,29 Thus, the equilibrium score reflected the extent to which the individual's sway movements approached the limits of stability for the 20-second quiet stance trials. The ratio scores were the sensory ratios among the average equilibrium scores on specific pairs of sensory test conditions.18,29 The sensory ratios for somatosensory, visual, and vestibular function and visual preference were indicated by the SOM ratio (SOT-2/SOT-1), VIS ratio (SOT-4/SOT-1), VEST ratio (SOT-5/SOT-1), and PREF ratio ([SOT-3 + SOT-6]/[SOT-2 + SOT-5]), respectively.34
Verbal reaction time was defined as the time interval between the onset of auditory stimulus and the onset of the participant's verbal response.33 The cognitive task alone in a sitting position was the single secondary task for practicing verbal response (VRT) and for checking the difficulty of the task itself on participants at rest among groups. The verbal response as the baseline or the single secondary task in a standing posture was obtained during the SOT-1 trial of dual tasks. Thus, the VRT obtained during SOT-2 to SOT-6 would be compared with the VRT obtained during SOT-1 during a dual task.
All data were analyzed using SPSS version 11.0.** The intention-to-treat analysis was used for missing data. If 1 person dropped out, his or her score from the previous testing session carried forward as a method for intention-to-treat analysis. Descriptive statistics were used to present each variable as mean ± standard deviation. The Kolmogorov-Smirnov test and the Mauchly test were used to assess the normality and homogeneity of variance, respectively. If the assumption of homogeneity of variance was not met, the Greenhouse-Geisser adjustment was used. One-way analyses of variance (ANOVAs) were used to test whether there were any differences among groups in baseline demographics and preintervention assessments. Separate 3-way mixed-model ANOVAs (3 groups × 2 tasks × 3 times) were used to test the interactions among the groups (ie, VR, CB, and control), tasks (ie, single and dual), and time effect (ie, before training, after training, and at follow-up) of variables in the SOT. A 2-way mixed model ANOVA (3 groups × 3 times) was used to test the interaction of time and group for the VRT. If a significant interaction was found, a post hoc analysis for multiple comparisons was used with Bonferroni adjustment. The probability for a type I error (α level) was set at less than .05/3.
Role of the Funding Source
Cycling and Health Center, Taichung, Taiwan, provided technical support of the VR balance training board. The study was partly supported by National Science Council, Taipei, Taiwan (NSC 97-2314-B-002-009-MY3).
Results
Participants
Of the 42 randomized participants, 38 completed the 6-week training protocols, and 32 were assessed at the 4-week follow-up. Reasons for dropout are shown in Figure 1. The group comparisons for the demographic characteristics and baseline values are summarized in Table 1. There were no significant differences in age, weight, disease duration, disease severity, or cognitive function among groups before training.
Demographic Characteristics and Baseline Data of Participants (N=42)a
Training Effects on Equilibrium Score
There were no significant differences in the baseline equilibrium scores (pretraining) among the VR, CB, and control groups. After training, there also was no significant difference between VR and CB groups. However, the ANOVA revealed a significant group × time interaction in condition SOT-6 between the VR group and the control group. The VR group increased the equilibrium score of SOT-6 (vestibular organization under unreliable vision) after training significantly more (P<.001) than the control group. This effect was not significant at follow-up.
The ANOVA for the CB group revealed significant group × time interactions in conditions SOT-5 and SOT-6. The CB training significantly (P<.001) increased the equilibrium score of SOT-5 (vestibular organization with eyes closed) after training more than the control group (Tab. 2).
Equilibrium Scores for the Sensory Organization Test (SOT) Among Groups Before and After Training and at Follow-up During Single and Dual Tasksa
Post hoc analysis of the training effect within groups (ie, after training compared with before training) indicated that VR training significantly (P<.001) increased the equilibrium score of SOT-6 after training and at follow-up and that the CB training significantly (P<.001) increased the equilibrium scores of SOT-5 and SOT-6 after training and at follow-up. The control group had no significant change in SOT-5 or SOT-6 either after training or at follow-up (Tab. 2). In general, the data reported reflect that both the VR and CB groups improved in 1 SOT condition, whereas the control group did not change significantly in any SOT condition.
Training Effects on Sensory Ratio
There were no significant differences in the baseline sensory ratios among groups. There was no significant effect after VR training (Tab. 3). However, CB training significantly increased the vestibular sensory ratio from baseline to after training and at follow-up (P<.001). Furthermore, CB training significantly increased the vestibular sensory ratio more than that of the control group (P=.006).
Sensory Ratio of Sensory Organization Test (SOT) Among Groups Before and After Testing and at Follow-up During Single and Dual Tasksa
Dual Task Effect
There were no significant differences in equilibrium scores between single and dual tasks or in sensory ratios of all 3 groups before and after training and at follow-up (Tabs. 2 and 3).
As for VRT, the single secondary task performed while the participant was seated did not show any significant group × time interaction, or a main effect of group and time (Tab. 4). Therefore, the arithmetic subtraction task (cognitive task) would provide the same difficulty to each group at rest before and after training and at follow-up. In some groups, at the initial and immediate postintervention assessments, the VRTs of SOT-1 while the participant was standing were significantly longer than the VRT while the participant was sitting, probably because of the increased demand of standing for all groups (Tab. 4). However, there was no significant difference in SOT-1 among groups.
Verbal Reaction Time (VRT) for Arithmetic Subtraction Under Single Secondary Task and Dual Task Sensory Organization Test (SOT) Conditions Among Groups Before and After Training and at Follow-upa
There were no significant differences in VRT between SOT-1 and SOT-6 in any of the 3 groups while standing (Tab. 4). As the VRT at SOT-1 with eyes open could be viewed as the single secondary task while standing, the attentional demand under dual task conditions did not seem to affect sensory integration in postural control in any group.
Discussion
The major findings of this study were: (1) VR-augmented balance training significantly improved the sensory integrative ability for postural control when both visual and somatosensory inputs were unreliable compared with the control group, (2) CB training significantly improved the sensory integrative ability for postural control when vision was deprived and the somatosensory input was unreliable compared with the control group, and (3) neither VR training nor CB training significantly affected the attentional demand for postural control during the SOT.
Comparisons Between VR and CB Training
The data reflected that both the VR and CB groups improved in 1 SOT condition, whereas the control group did not change significantly in any SOT condition. The fact that both the VR and CB groups demonstrated significant improvement in sensory integrative ability for postural control in conditions under which both vision and somatosensation were altered suggested that both groups offered similar training effects for people with PD. The nonsignificant difference between the VR and CB groups could be related to their similar treatment principles (ie, monitoring visual, somatosensory, and vestibular information during training) adopted for balance training; a short duration (ie, 6 weeks) of training (longer duration of training might have enhanced the differences between groups), and a small sample size.
The 2 training groups were different in that the VR group significantly improved in condition SOT-6 (ie, unreliable vision and somatosensory condition) and the CB group significantly improved in condition SOT-5 (ie, somatosensory condition unreliable with eyes closed). The difference in training effect might have been the result of the specific training situation offered by the VR training device being similar to the test condition of SOT-6. In this study, virtual activities in the VR training could provide visual feedback from the virtual object on the screen by self-initiated weight shift (internal feedback) on the dynamic balance board, and the accelerated or augmented optical flow was under different proprioceptive information.14–16 Therefore, the central organization and integration of vestibular information under unreliable vision and somatosensation were improved. On the other hand, the CB training, with eyes open or closed, foam, and ball catching, had error correction feedback mainly from the therapist's verbal instruction (external feedback). A recent study indicated that there was a significant correlation between the SOT Falls Severity Scale and disease severity in people with PD34 and that SOT-6 was the most sensitive condition for detecting a high risk of falls in older adults.35 Therefore, both VR and CB training would be good for balance training, but VR training might be especially beneficial for fall prevention under unreliable visual and somatosensory conditions.
The study by Frenklach and associates36 indicated that people with PD were unable to use the impaired proprioceptive feedback on the dynamic moving surface for orientation and that they had to rely on vestibular feedback only, or on vestibular and visual feedback. However, some researchers believed that people with PD were not highly visually dependent.5 Therefore, vestibular function would be important for postural stability in people with PD. Although impaired motor learning was found in people with PD, previous studies suggested these people still preserved the ability to learn new postural tasks.37,38 Based on neurophysiology, previous studies suggested that the cerebellum was responsible for feedforward and supervised learning, but that the basal ganglia were important for internal feedback to maximize the reward.38–40 Furthermore, the cerebellum has been shown to be an important neural module to integrate multiple sensory information from visual, vestibular, and somatosensory components in order to execute vestibular spinal reflex to assist postural control.39 Therefore, the people with impaired basal ganglia in our study might learn to integrate visual and vestibular information more efficiently through the cerebellum, which then would influence the brain stem and spinal cord to improve postural control. Whether there was a direct training effect on the basal ganglia could not be proved in this study.
Effects Under Attentional Demand
A previous study in people with PD indicated that the cognitive subtraction task could reduce the performance of a primary walking task.33 However, the current study did not find reduced VRT during postural control in changing sensory environments after VR and CB training. The capacity-sharing model of attention suggests that dual task interference would occur only if the available resource capacity was exceeded.41 In this study, an auditory interference presented only once (at 10 seconds) during a 20-second SOT trial might not be strong enough to reduce sensory integration ability for postural control.
Limitations of the Study
There were some limitations in this study. First, we trained and assessed people with PD of mild-to-moderate severity during the on phase, making it impossible to apply these training effects to those with more-severe disease during the off phase or to those with other atypical symptoms (ie, multiple systems atrophy or progressive supranuclear palsy). Second, it is important to modify the hardware or software of a VR training system to create an individualized training program. Third, the power for nonsignificant changes of SOT-1 to SOT-4 ranged from 0.08 to 0.62 (the power for significant change was ∼0.8), and more homogenous samples and larger sample sizes are suggested for future study. Fourth, a concurrent secondary task needs to be given continuously or more than once during the 20-second SOT trials.
Conclusion
Stance stability in a deprived sensory redundancy environment was significantly improved after 6 weeks of either VR or CB training in people with PD. When compared with the control group, it was shown that the VR training mainly enhanced the ability to use vestibular information for postural control under unreliable vision and somatosensation in people with mild-to-moderate PD. The CB training mainly increased the ability to use vestibular information for postural control under unreliable somatosensation with deprived vision. Neither training approach demonstrated a significant effect on reducing the attentional demand for postural stability. Therefore, both VR and CB training could be considered in clinics as methods to improve sensory integrative ability for postural stability in people with PD.
The Bottom Line
What do we already know about this topic?
There is very little known to date about the effect of virtual reality–augmented balance (VR) training on postural control in people with Parkinson disease (PD). In addition, the mechanisms of VR training on walking or standing balance are not clear.
What new information does this study offer?
The VR-augmented balance training with a tiltable board can improve the sensory integration ability in people with Parkinson disease. The effect is not significantly different from that of the conventional balance training.
If you're a patient, what might these findings mean for you?
Your physical therapist might recommend that you try standing on a balance board with an interactive game or on foam to improve your balance ability.
Appendix 1.
Virtual Reality–Augmented Balance Training Protocols
Appendix 2.
Conventional Balance Training Protocols
Footnotes
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All authors provided concept/idea/research design. Mr Yen, Dr K.-H. Lin, Dr Hu, and Dr Lu provided writing and data analysis. Mr Yen, Dr K.-H. Lin, and Dr Lu provided data collection. Dr. K.-H. Lin provided project management and fund procurement. Dr Wu provided participants. Dr K.-H. Lin and Dr Hu provided facilities/equipment. Dr Hu, Dr Wu, Dr Lu, and Dr C.-H. Lin provided consultation (including review of manuscript before submission).
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The authors thank Mr Jason Chen in the Cycling & Health Tech Industry R & D Center, Taichung, Taiwan, for developing the dynamic tilting balance board for VR training. The authors also thank Assistant Professor Jason Chien-Shun Lo and Mr Chen-Shin Yu, Department of Multimedia Design, National Formosa University, Yunlin, Taiwan, for their effort in constructing the simulated (virtual) indoor and outdoor activities for training.
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The study was partly supported by the National Science Council, Taipei, Taiwan (NSC 97-2314-B-002-009-MY3).
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Trial registration: ClinicalTrials.gov Identifier: NCT01301651.
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↵* Dassault Systemes, 10 rue Marcel Dassault, 78140 Vélizy, Villacoublay, France.
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↵† Neurocom International Inc, 9570 SE Lawnfield Rd, Clackamas, OR 97015-6676.
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↵‡ Advanced Mechanical Technology Inc, 176 Waltham St, Watertown, MA 02472-4800.
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↵§ The MathWorks, 3 Apple Hill Dr, Natick, MA 01760-2098.
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↵‖ BIOPAC Systems Inc, 42 Aero Camino, Goleta, CA 93117.
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↵# Acknowledge Software Inc, 873 Embarcadero Rd, Palo Alto, CA 94303.
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↵** SPSS Inc, 233 S Wacker Dr, Chicago, IL 60606.
- Received February 3, 2010.
- Accepted January 31, 2011.
- © 2011 American Physical Therapy Association
References
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