Virtual Reality – Lower Extremity

Evidence Reviewed as of before: 06-08-2017
Author(s): Tatiana Ogourtsova, PhD(c) OT; Adam Kagan BSc; Dr. Nicol Korner-Bitensky PhD OT; Annabel McDermott OT
Expert Reviewer: Francine Malouin PhD, PT
Patient/Family Information Table of contents

Introduction

Virtual Reality (VR) is an environment that is simulated by a computer. It provides an interactive multi-sensory stimulation in real-time. VR provides users with the opportunity to engage in activities within an environment that appears and feels similar to real world objects and events. Users can interact with a virtual environment through the use of standard input devices such as a keyboard and mouse, or through multimodal devices such as a wired glove. VR is becoming increasingly popular as it can be easily modified according to the needs of individuals, it is perceived as being fun and motivating for patients, and it allows researchers to incorporate elements such as feedback that have been shown to maximize motor learning. On the negative side, there is concern that the use of VR in the clinic is not possible due to the cost of the required equipment. While certainly true when this technology was created, the cost of virtual reality hardware and software has decreased and is now reasonably affordable for clinical use.

Note: In this module we did not differentiate between immersive and non-immersive VR. This categorization is determined mainly by the degree of ‘virtual presence’ the subject experienced during training, and this information was not made readily available in most of the studies reviewed.
Note: This review focuses on any type of therapy involving a virtual environment. For a specific review of commercial game systems used for physical rehabilitation (e.g. Sony Playstation EyeToy, Nintendo Wii), please see the Video Games module. Studies were excluded in instances where the intervention did not pertain to lower extremity/mobility rehabilitation (e.g. cognitive rehabilitation), no outcomes of interest pertained to lower extremity/mobility (e.g. gait parameters, balance, etc.), or where both groups received a form of VR-based rehabilitation.

To date 11 high quality RCTs, 7 fair quality RCTs, and 2 quasi-experimental design studies have investigated the effect of virtual-reality based training for the lower extremity/mobility rehabilitation in patients with stroke.

Overall, effects of virtual reality-based training on lower-extremity/mobility were examined predominantly among patients with chronic stroke and included the used of VR ankle, balance, postural control, stepping exercises and treadmill gait training. Improvements in outcomes such as balance, gait parameters, walking speed and endurance, and functional ambulation/mobility were found in patients receiving the VR-based training in comparison to those receiving conventional gait/balance training or conventional physical therapy or no additional VR training.

Patient/Family Information

Authors*: Tatiana Ogourtsova, PhD(c) OT, Amy Henderson, PhD Student, Neuroscience; Dr. Nicol Korner-Bitensky PhD OT, Mindy Levin, PhD PT; Geoffroy Hubert BSc. Lic. K. ; Elissa Sitcoff BSc. B.A.
Expert: Francine Malouin PhD, PT
Additional support from undergraduate students, School of Physical and Occupational Therapy, McGill University: Kareim Aziz, Sara Jafri, James Moore, Sebastien Mubayed, Roshnie Shah, Samrah Sher, and Peter Yousef

What is virtual reality?

Virtual Reality is an environment that is simulated by a computer. Most virtual reality environments are primarily visual experiences, displayed either on a computer screen or through special stereoscopic displays (see picture 1), and may also include auditory stimulation through speakers or headphones. Users can interact with the virtual environment through the use of devices such as a keyboard, a mouse, or a wired glove (see picture 2).

Are there different kinds of virtual reality?

Generally, there are two types of virtual reality: full immersion, and non-immersion.

  1. Full immersive VR is when the environment is viewed through a device such as a head-mounted display to create the illusion that one is inside the environment.
  2. Non-immersive, or partially immersive VR, is when the user views the scene on a computer screen and it appears as if he was watching TV.

Why use virtual reality after a stroke?

Loss of leg function, movement, and strength are common after a stroke, and can result in the impairment of walking and standing.

Virtual reality is becoming an increasingly popular intervention used to improve the use of one’s leg after a stroke. It can be easily modified according to the needs of the individual, is perceived as being fun and motivating for patients, and allows researchers to include elements such as feedback that have been shown to maximize learning.

Does it work for stroke?

Researchers have studied how different VR-based treatments designed for the recovery of walking ability and legs function can help patients with stroke:

In individuals with CHRONIC stroke (more than 6 months after stroke), studies found that:

  • IREX (Immersive Rehabilitation Exercise) system training is MORE helpful than comparison treatment(s) in improving balance, walking ability, and walking speed.
  • VR ankle training is MORE helpful than comparison treatment(s) in improving walking ability and spasticity.
  • VR + Robotics RARS (Rutgers Ankle Rehabilitation System) training is MORE helpful than comparison treatment(s) in improving walking ability. It is AS helpful as comparison treatment(s) in improving walking endurance and walking speed.
  • VR postural control training is AS helpful as comparison treatment(s) in improving balance, walking ability, and walking speed.
  • VR stepping exercise is MORE helpful than comparison treatment(s) in improving balance and walking speed.
  • VR treadmill gait training is MORE helpful than comparison treatment(s) in improving balance, walking ability, and walking speed. It is AS helpful as comparison treatment(s) in improving balance confidence, and ability to circumvent obstacles.

In individuals with stroke (acute, subacute and/or chronic), studies found that:

  • VR balance training is AS helpful than a comparison treatment in improving balance, walking ability and speed and pelvis control.

Side effects/risks?

Use of devices such as a head-mounted display can cause nausea and vertigo.

No real risks have been reported because of the absence of external manipulation. All activities are self-paced and under individual control and perception of movement.

Who provides the treatment?

VR treatments are usually provided by a Physical Therapist or Occupational Therapist. Presently most rehabilitation centers and private clinics are not equipped with this technology other than for research purposes. But, given the promising early evidence for the value of using VR, this treatment is likely to be integrated as part of post-stroke therapy in the future.

How many treatments?

Information on the amount and intensity of VR training needed is still not available. High quality studies need to be conducted before advice can be given regarding specific programs and content of treatment sessions.

How much does it cost?

There is concern that the use of VR in the clinic is not possible due to the cost of the required equipment. While certainly true when this technology was created, the cost of virtual reality hardware and software has decreased and should soon be reasonably affordable for clinical use.

Is virtual reality for me?

There is clear evidence that there are benefits to using virtual reality in comparison to regular therapy or no therapy. These benefits include walking strength, how fast you can walk, length of step, stamina, the community living skill “crossing the street”, and remapping of the brain. However, in terms of obstacle clearance, VR was not shown to be more effective than conventional therapy. More studies are needed to determine if VR is an effective intervention for stair-climbing and the community living skill “taking the train”. So, overall, VR is an effective treatment you may want to consider after a stroke. If you are interested in learning more about VR, speak to your rehabilitation provider about the possibility of using this treatment.

Clinician Information

Note: When reviewing the findings, it is important to note that they are always made according to randomized clinical trial (RCT) criteria – specifically as compared to a control group. To clarify, if a treatment is “effective” it implies that it is more effective than the control treatment to which it was compared. Non-randomized studies are no longer included when there is sufficient research to indicate strong evidence (level 1a) for an outcome.

To date 11 high quality RCTs, 7 fair quality RCTs, and 2 quasi-experimental design studies have investigated the effect of virtual-reality (VR) based training for the lower extremity/mobility rehabilitation in patients with stroke.

Results Table

View results table

Outcomes

Chronic phase - IREX (Immersive Rehabilitation Exercise) system training

Balance
Effective
1B

One high quality RCT (Kim et al., 2009) investigated the effect of VR-based training on balance in patients with chronic stroke. This high quality RCT randomized patients to receive VR balance/gait training using the IREX system or no VR training; both groups received conventional physical therapy balance training. Balance was measured by the Berg Balance Scale (BBS) and the Balance Performance Monitor system (BPM, static balance: mean, sway area, sway path, maximal velocity; dynamic balance: anterior-posterior, medio-lateral) at post-treatment (4 weeks). Significant between-group differences were found in balance (BBS, BPM dynamic balance: anterior-posterior, medio-lateral), favoring VR balance/gait training using the IREX system vs. no VR training.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that VR balance/gait training using the IREX system is more effective than a comparison intervention (no VR training) in improving balance in patients with chronic stroke.

Note: This may in part be due to greater treatment time.

Functional mobility
Effective
1A

Two high quality RCTs (You et al., 2005; Kim et al., 2009) investigated the effect of VR-based training on functional mobility in patients with chronic stroke.

The first high quality RCT (You et al., 2005) randomized patients to receive VR gait training using the IREX system or no treatment. Functional mobility was measured by the Modified Motor Assessment Scale and the Functional Ambulation Category Test at post-treatment (4 weeks). Significant between-group differences were found in both measures of functional mobility, favoring VR gait training using the IREX system vs. no treatment.

The second high quality RCT (Kim et al., 2009) randomized patients to receive VR balance/gait training using the IREX system or no VR training; both groups received conventional physical therapy balance training. Functional mobility was measured by the Modified Motor Assessment Scale at post-treatment (4 weeks). Significant between-group differences were found, favoring VR balance/gait training using the IREX system vs. no VR training.

Conclusion: There is strong evidence (Level 1a) from two high quality RCTs that VR gait training using the IREX system is more effective than comparison interventions (no treatment, no additional VR training) in improving functional mobility in patients with chronic stroke.

Gait parameters
Effective
1B

One high quality RCT (Kim et al., 2009) investigated the effect of VR-based training on gait parameters in patients with chronic stroke. This high quality RCT randomized patients to receive VR balance/gait training using the IREX system or no VR training; both groups received conventional physical therapy balance training. Gait parameters (cadence, step time, swing time, stance time, single support time, double support time, step length, stride length) were measured by the GAITRite system at post-treatment (4 weeks). Significant between-group differences in three gait parameters (cadence, step time, step length) were found, favoring VR balance/gait training using the IREX system vs. no VR training.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that VR balance/gait training using the IREX system is more effective than a comparison intervention (no VR training) in improving gait parameters in patients with chronic stroke.

Walking speed
Effective
1B

One high quality RCT (Kim et al., 2009) investigated the effect of VR-based training on walking speed in patients with chronic stroke. This high quality RCT randomized patients to receive VR balance/gait training using the IREX system or no VR training; both groups received conventional physical therapy balance training. Walking speed was measured by the 10-meter walking test at post-treatment (4 weeks). Significant between-group differences were found, favoring VR balance/gait training using the IREX system vs. no VR training.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that VR balance/gait training using the IREX system is more effective than a comparison intervention (no additional VR training) in improving walking speed in patients with chronic stroke.

Chronic phase - VR Ankle training

Gait parameters
Effective
2A

One fair quality RCT (Yom et al., 2015) investigated the effect of VR-based training on gait parameters in patients with chronic stroke. This fair quality RCT randomized patients to receive VR ankle training or no training; both groups received conventional physical therapy. Gait parameters were measured by the GAITRite system (velocity, cadence, step length, stride length, stance time percentage, swing time percentage, double limb support percentage) at post-treatment (6 weeks). Significant between-group differences were found in all gait parameters, favoring VR ankle training vs. no training.

Conclusion: There is limited evidence (Level 2a) from one fair quality RCT that VR ankle training is more effective than no training in improving gait parameters in patients with chronic stroke.

Mobility
Effective
2A

One fair quality RCT (Yom et al., 2015) investigated the effect of VR-based training on mobility in patients with chronic stroke. This fair quality RCT randomized patients to receive VR ankle training or no training; both groups received conventional physical therapy. Mobility was measured by the Timed Up and Go test at post-treatment (6 weeks). Significant between-group differences were found, favoring VR ankle training vs. no training.

Conclusion: There is limited evidence (Level 2a) from one fair quality RCT that VR ankle training is more effective than no training in improving mobility in patients with chronic stroke.

Spasticity
Effective
2A

One fair quality RCT (Yom et al., 2015) investigated the effect of VR-based training on spasticity in patients with chronic stroke. This fair quality RCT randomized patients to receive VR ankle training or no training; both groups received conventional physical therapy. Spasticity was measured by the Modified Ashworth Scale and the Tardieu Scale at post-treatment (6 weeks). Significant between-group differences were found for both measures of spasticity, favoring VR ankle training vs. no training.

Conclusion: There is limited evidence (Level 2a) from one fair quality RCT that VR ankle training is more effective than no training in reducing spasticity in patients with chronic stroke.

Chronic phase - VR postural control training

Balance
Not Effective
1B

One high quality RCT (Lee et al., 2014) investigated the effect of VR-based training on balance in patients with chronic stroke. This high quality RCT randomized patients to receive VR postural control training or no VR training; both groups received physical therapy. Balance was measured by the Berg Balance Scale at post-treatment (4 weeks). No significant between-group differences were found.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that VR postural control training is not more effective than no VR training in improving balance in patients with chronic stroke.

Functional ambulation
Not Effective
1B

One high quality RCT (Park et al., 2013) investigated the effect of VR-based training on functional ambulation in patients with chronic stroke. This high quality RCT randomized patients to receive VR postural control training or no VR training; both groups received conventional physical therapy. Functional ambulation was measured by the Functional Ambulation Profile at post-treatment (4 weeks) and at follow-up (1 month). No significant between-group differences were found at either time point.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that VR postural control training is not more effective than no VR training in improving functional ambulation in patients with chronic stroke.

Gait parameters
Conflicting
4

Two high quality RCTs (Park et al., 2013; Lee et al., 2014) investigated the effect of VR-based training on gait parameters in patients with chronic stroke.

The first high quality RCT (Park et al., 2013) randomized patients to receive VR postural control training or no VR training; both groups received conventional physical therapy. Gait parameters (velocity, cadence, step/stride length of paretic/non-paretic limbs) were measured by the GAITRite system at post-treatment (4 weeks) and at follow-up (1 month). No significant between-group differences were found at post-treatment. At follow-up, a significant between-group difference was found for stride length (paretic and non-paretic limbs) only, favoring VR postural control training vs. no VR training.

The second high quality RCT (Lee et al., 2014) randomized patients to receive VR postural control training or no VR training; both groups received physical therapy. Gait parameters (velocity, cadence, step length/stride length of paretic/non-paretic limbs) were measured by the GAITRite system at post-treatment (4 weeks). Significant between-group differences were found for most gait parameters (velocity, step length/stride length of paretic/non-paretic limbs), favoring VR postural control training vs. no VR training.

Conclusion: There is conflicting evidence (Level 4) between two high quality RCTs regarding the effect of VR postural control training on gait parameters in patients with chronic stroke. While one high quality RCT found that VR postural control training was not more effective than a comparison intervention (physical therapy provided for 60-minute sessions, 5 times/week for 4 weeks); a second high quality RCT found that VR postural control training was more effective than a comparison intervention (physical therapy provided 30-minute session, 3 times/week for 4 weeks).

Note: Both studies provided the intervention at a comparable intensity and duration; accordingly, differences in the intensity of the comparison intervention between the two studies could account for differences in findings.

Mobility
Not Effective
1B

One high quality RCT (Lee et al., 2014) investigated the effect of VR-based training on mobility in patients with chronic stroke. This high quality RCT randomized patients to receive VR postural control training or no VR training; both groups received physical therapy. Mobility was measured by the Timed Up and Go test at post-treatment (4 weeks). No significant between-group differences were found.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that VR postural control training is not more effective than no VR training in improving mobility in patients with chronic stroke.

Walking speed
Not Effective
1B

One high quality RCT (Park et al., 2013) investigated the effect of VR-based training on walking speed in patients with chronic stroke. This high quality RCT randomized patients to receive VR postural control training or no VR training; both groups received conventional physical therapy. Walking speed was measured by the 10-meter walking test at post-treatment (4 weeks) and at follow-up (1 month). No significant between-group differences were found at either time point.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that VR postural control training is not more effective than no VR training in improving waking speed in patients with chronic stroke.

Chronic phase - VR + Robotics RARS (Rutgers Ankle Rehabilitation System) training

Gait parameters
Effective
1B

One high quality RCT (Mirelman et al., 2008) investigated the effect of VR-based training on gait parameters in patients with chronic stroke. This high quality RCT randomized patients to receive VR + the robotic Rutgers Ankle Rehabilitation System (RARS) or RARS only. Gait parameters (number of steps/day, average daily distance walked, velocity, cadence, stride length, longest consecutive locomotion period, longest distance traveled) were measured by the Patient Activity Monitor at post-treatment (4 weeks). A significant between-group difference was found in three gait parameters (number of steps/day, average daily distance, velocity) at post-treatment, favoring VR + RARS vs. RARS alone.

A further analysis (Mirelman et al., 2010) reported on gait parameters (change in ankle moment at push-off barefoot/shoes on; ankle power at push-off barefoot/shoes on; ankle range of motion barefoot/shoes on; knee flexion range of motion during stance/swing barefoot/shoes on; hip flexion range of motion during swing barefoot/shoes on; onset of push-off; self-selected velocity) measured by the Vicon Motion Capture System + Plug-In Gait model at post-treatment (4 weeks) and at follow-up (3 months). Significant between-group differences were found for some gait parameters at post-treatment (change in ankle moment at push-off – barefoot; ankle power at push-off – barefoot; knee flexion range of motion during stance/swing – barefoot; onset of push-off; self-selected velocity); and at follow up (ankle power at push-off – barefoot; ankle range of motion – barefoot; knee flexion ROM of the affected side during stance/swing – barefoot; onset of push-off; self-selected velocity), favoring VR + RARS vs. RARS alone.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that VR + robotic lower extremity training is more effective than a comparison intervention (robotic lower extremity training alone) in improving gait parameters in patients with chronic stroke.

Walking endurance
Not Effective
1B

One high quality RCT (Mirelman et al., 2008) investigated the effect of VR-based training on walking endurance in patients with chronic stroke. This high quality RCT randomized patients to receive VR + the robotic Rutgers Ankle Rehabilitation System (RARS) or robotics RARS alone. Walking endurance was measured by the 6-Minute Walk Test at post-treatment (4 weeks) and at follow-up (3 months). No significant between-group differences were found at either time point.

Note: However, subgroup analyses of patients with moderate walking speed at baseline revealed significant between-group differences at post-treatment and at follow-up, favoring VR + RARS vs. RARS alone.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that VR + robotic lower extremity training is not more effective than a comparison intervention (robotic lower extremity training alone) in improving walking endurance in patients with chronic stroke.

Walking speed
Not effective
1B

One high quality RCT (Mirelman et al., 2008) investigated the effect of VR-based training on walking speed in patients with chronic stroke. This high quality RCT randomized patients to receive VR + the robotic Rutgers Ankle Rehabilitation System (RARS) or RARS alone. Self-selected walking speed over 7 meters was measured at post-treatment (4 weeks) and at follow-up (3 months). No significant between-group differences were found at either time point.

Note: However, subgroup analyses of patients with moderate walking speed at baseline revealed significant between-group differences at post-treatment and at follow-up, favoring VR + RARS vs. RARS alone.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that VR + robotics lower extremity training is not more effective than a comparison intervention (robotics lower extremity training alone) in improving walking speed in patients with chronic stroke.

Chronic phase - VR stepping exercise

Balance
Effective
1B

One high quality RCT (Llorens et al., 2015) and one quasi-experimental design study (Llorens et al., 2012) investigated the effect of VR-based training on balance in patients with chronic stroke.

The high quality RCT (Llorens et al., 2015) randomized patients to receive VR stepping exercises or no VR training; both groups received conventional physical therapy. Balance was measured by the Berg Balance Scale, Brunel Balance Assessment, and Tinetti Performance Oriented Mobility Assessment (balance, gait subtests) at post-treatment (4 weeks). Significant between-group differences were found on 2 of 3 balance measures (Berg Balance Scale, Brunel Balance Assessment) at post-treatment, favoring VR stepping exercises vs. no VR training.

The quasi-experimental design study (Llorens et al., 2012) assigned patients to receive VR stepping exercises. Balance was measured by the Berg Balance Scale, Brunel Balance Assessment, and Tinetti Performance Oriented Mobility Assessment (balance subtest) at baseline, at post-treatment (4-5 weeks) and at follow-up (8 weeks). Significant improvements were found on 2 of 3 balance measures (Berg Balance Scale, Brunel Balance Assessment) at post-treatment; differences did not remain significant at follow-up.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that VR stepping exercises are more effective than no VR training in improving balance in patients with chronic stroke. A quasi-experimental design study also found improvements in balance following VR stepping exercises.

Walking speed
Effective
1B

One high quality RCT (Llorens et al., 2015) investigated the effect of VR-based training on walking speed in patients with chronic stroke. This high quality RCT randomized patients to receive VR stepping exercises or no VR training; both groups received conventional physical therapy. Walking speed was measured by the 10-Meter Walking Test at post-treatment (4 weeks). Significant between-group differences were found, favoring VR stepping exercises vs. no VR training.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that VR stepping exercises are more effective than no VR training in improving walking speed in patients with chronic stroke.

Chronic phase - VR treadmill gait training

Balance
Effective
1A

Three high quality RCTs (Kang et al., 2012; Cho & Lee, 2013; Cho & Lee, 2014) and three fair quality RCTs (Jaffe et al., 2004; Yang et al., 2011; Kim et al., 2015) investigated the effect of VR-based training on balance in patients with chronic stroke.

The first high quality RCT (Kang et al., 2012) randomized patients to receive VR treadmill gait training with optic flow, conventional treadmill gait training or physical exercises; all groups received conventional physical therapy. Balance was measured by the Functional Reach Test at post-treatment (4 weeks). Significant between-group differences were found, favoring VR treadmill gait training with optic flow vs. physical exercises; there were no significant differences between VR treadmill gait training and conventional treadmill gait training.

Note: Significant between-group differences were also found favoring conventional treadmill gait training vs. physical exercises.

The second high quality RCT (Cho & Lee, 2013) randomized patients to receive VR treadmill gait training or conventional treadmill gait training; both groups received conventional rehabilitation. Balance was measured by the Berg Balance Scale (BBS) at post-treatment (6 weeks). Significant between-group differences were found, favoring VR treadmill gait training vs. conventional treadmill gait training.

The third high quality RCT (Cho & Lee, 2014) randomized patients to receive VR treadmill gait training or conventional treadmill gait training; both groups received conventional rehabilitation. Dynamic balance was measured by the BBS, and static balance was measured by the Good Balance SystemTM(postural sway: anteroposterior, mediolateral, velocity moment) at post-treatment (6 weeks). Significant between-group differences were found for dynamic balance only, favoring VR treadmill gait training vs. conventional treadmill gait training.

The first fair quality RCT (Jaffe et al., 2004) randomized patients to receive VR treadmill gait training or non-VR gait training. Balance was measured by a non-standardized 7-item balance test adapted from the Performance-Oriented Assessment of Mobility and the Physical Performance Test, at post-treatment (2 weeks) and at follow-up (4 weeks). No significant between-group differences were found at either time point.

The second fair quality RCT (Yang et al., 2011) randomized patients to receive VR treadmill gait training or conventional treadmill gait training. Balance in quiet stance (center of pressure [COP] displacement in medial-lateral direction [COPML], posterior/anterior direction [COPAP], total path excursion [COPE], sway area [COPA], and symmetry index [SI]), sit-to-stand transfer (COPML, COPAP, COPE, COPA, SI /paretic limb), and level walking (paretic limb stance time, step number, contact area) was measured by a pressure mat system at post-treatment (3 weeks). There was a significant between-group difference in only one measure of balance (quiet stance: COPML) favoring VR treadmill gait training vs. conventional treadmill gait training.

The third fair quality RCT (Kim et al., 2015) randomized patients to receive VR treadmill gait training or time-matched physical therapy; both groups received conventional physical therapy. Static balance was measured using the Balancia Software system and Wii FitTM balance board to assess postural sway path length (anterior/posterior, mediolateral, total) and postural sway speed at post-treatment (4 weeks). Significant between-group differences were found in both measures of static balance, favoring VR treadmill gait training vs. time-matched physical therapy.

Conclusion: There is strong evidence (Level 1a) from three high quality RCTs and one fair quality RCT that VR treadmill gait training is more effective than comparison interventions (conventional treadmill gait training, physical exercises, and time-matched physical therapy) in improving balance in patients with chronic stroke.

Note: One of the high quality RCTs found that VR treadmill training was not more effective than conventional treadmill training; two fair quality RCTs found that VR treadmill gait training was not more effective than comparison interventions (conventional treadmill gait training, non-VR gait training) in improving balance in patients with chronic stroke. Differences among studies including outcome measures used, duration of interventions and comparison interventions could account for difference in findings.

Balance confidence
Not Effective
1a

Two high quality RCTs (Yang et al., 2008; Kim et al., 2016) and one fair quality RCT (Jung et al., 2012) investigated the effect of VR-based training on balance confidence in patients with chronic stroke.

The first high quality RCT (Yang et al., 2008) randomized patients to receive VR treadmill gait training or conventional treadmill gait training. Balance confidence was measured by the Activities-Specific Balance Confidence (ABC) Scale at post-treatment (3 weeks) and at follow-up (1 month). No significant between-group differences were found at either time point.

The second high quality RCT (Kim et al., 2016) randomized patients to receive VR treadmill gait training, time-matched community ambulation training, or no additional training; all groups received physical therapy. Balance confidence was measured by the ABC Scale at post-treatment (4 weeks). There were no significant differences between VR treadmill training and community ambulation training. Significant between-group differences were found in favour of VR treadmill gait training vs. no additional training.

Note: Significant between-group differences were also found favoring community ambulation training vs. no additional training.

The fair quality RCT (Jung et al., 2012) randomized patients to receive VR treadmill gait training or conventional treadmill gait training. Balance confidence was measured by the ABC Scale at post-treatment (3 weeks). Significant between-group differences were found, favoring VR treadmill gait training vs. conventional treadmill gait training.

Conclusion: There is strong evidence (Level 1a) from two high quality RCTs that VR treadmill gait training is not more effective than comparison interventions (conventional treadmill gait training, community ambulation training) in improving balance confidence in patients with chronic stroke.

Note: However, one of the high quality RCTs found that VR treadmill gait training was more effective than no additional training; a fair quality RCT found that VR treadmill training was more effective than conventional treadmill training.

Gait parameters
Conflicting
4

Three high quality RCTs (Cho & Lee, 2013; Cho & Lee, 2014; Kim et al., 2016) and one fair quality RCT (Jaffe et al., 2004) investigated the effect of VR-based training on gait parameters in patients with chronic stroke.

The first high quality RCT (Cho & Lee, 2013) randomized patients to receive VR treadmill gait training or conventional treadmill gait training; both groups received conventional rehabilitation. Gait parameters (velocity, cadence, step length, stride length, single limb support) were measured by the GAITRite system at post-treatment (6 weeks). Significant between-group differences were found for 2 of 5 gait parameters (velocity, cadence), favoring VR treadmill gait training vs. conventional treadmill gait training.

The second high quality RCT (Cho & Lee, 2014) randomized patients to receive VR treadmill gait training or conventional treadmill gait training; both groups received conventional rehabilitation. Gait parameters (gait speed, cadence, step length, stride length and single/double limb support) were measured by the GAITRite system at post-treatment (6 weeks). Significant between-group differences were found for all gait parameters, favoring VR treadmill gait training vs. conventional treadmill gait training.

The third high quality RCT (Kim et al., 2016) randomized patients to receive VR treadmill gait training, time-matched community ambulation training, or no additional training; all groups received physical therapy. Gait parameters (velocity, cadence, paretic step and stride lengths) were measured by the GAITRite system at post-treatment (4 weeks). No significant between-group differences were found between any group.

The fair quality RCT (Jaffe et al., 2004) randomized patients to receive VR treadmill gait training or non-VR gait training. Gait parameters (at fast and comfortable speed: velocity, cadence, stride length, step length) were measured by the Stride Analyzer gait analysis system, at post-treatment (2 weeks) and at follow-up (4 weeks). Significant between-group differences were found for 2 measures (fast speed: velocity, stride length) at post-treatment, favoring VR treadmill gait training vs. non-VR gait training. Differences did not remain significant at follow-up.

Conclusion: There is conflicting evidence (Level 4) regarding the effect of VR treadmill gait training on gait parameters in patients with chronic stroke. One high quality RCT found VR treadmill gait training to be more effective than conventional treadmill gait training, whereas another high quality RCT found it was not more effective than community ambulation training or no training. A third high quality RCT and a fair quality RCT found mixed results when comparing VR treadmill gait training with conventional treadmill gait training and non-VR gait training (respectively).

Functional ambulation
Effective
1b

One high quality RCT (Yang et al., 2008) investigated the effect of VR-based training on functional ambulation in patients with chronic stroke. This high quality RCT randomized patients to receive VR treadmill gait training or conventional treadmill gait training. Functional ambulation was measured by the Community Walk Test (CWT) and the Walking Ability Questionnaire (WAQ) at post-treatment (3 weeks) and at follow-up (1 month). There was a significant between-group difference in one measure of functional ambulation (CWT) at post-treatment, favoring VR treadmill gait training vs. conventional treadmill gait training; this difference did not remain significant at follow-up. However, there was a significant between-group difference in the other measure of functional ambulation (WAQ) at follow-up, favoring VR treadmill gait training vs. conventional treadmill gait training.

Conclusion: There is moderate evidence (Level 1b) from one high quality RCT that VR treadmill gait training is more effective than a comparison intervention (conventional treadmill gait training) in improving functional ambulation in patients with chronic stroke.

Mobility
Effective
1a

Four high quality RCTs (Kang et al., 2012; Cho & Lee, 2013; Cho & Lee, 2014; Kim et al., 2016) and one fair quality RCT (Jung et al., 2012) investigated the effect of VR-based training on mobility in patients with chronic stroke.

The first high quality RCT (Kang et al., 2012) randomized patients to receive VR treadmill gait training with optic flow, conventional treadmill gait training or physical exercises; all groups received conventional physical therapy. Mobility was measured by the Timed Up and Go test (TUG) at post-treatment (4 weeks). Significant between-group differences were found, favoring VR treadmill gait training with optic flow vs. conventional treadmill gait training; and favoring VR treadmill gait training with optic flow vs. physical exercises.

Note: There were no significant differences between conventional treadmill gait training and physical exercises.

The second high quality RCT (Cho & Lee, 2013) randomized patients to receive VR treadmill gait training or conventional treadmill gait training; both groups received conventional rehabilitation. Mobility was measured by the TUG at post-treatment (6 weeks). Significant between-group differences were found, favoring VR treadmill gait training vs. conventional treadmill gait training.

The third high quality RCT (Cho & Lee, 2014) randomized patients to receive VR treadmill gait training or conventional treadmill gait training; both groups received conventional rehabilitation. Mobility was measured by the TUG at post-treatment (6 weeks). Significant between-group differences were found, favoring VR treadmill vs. conventional treadmill gait training.

The forth high quality RCT (Kim et al., 2016) randomized patients to receive VR treadmill gait training, time-matched community ambulation training, or no additional training; all groups received physical therapy. Mobility was measured by the TUG at post-treatment (4 weeks). Significant between-group differences were found, favoring VR treadmill gait training vs. no additional training. There were no significant differences between VR treadmill training and community ambulation training.

Note: There were no significant differences between community ambulation training and no additional training.

The fair quality RCT (Jung et al., 2012) randomized patients to receive VR treadmill gait training or conventional treadmill gait training. Mobility was measured by the TUG at post-treatment (3 weeks). Significant between-group differences were found, favoring VR treadmill gait training vs. conventional treadmill gait training.

Conclusion: There is strong evidence (Level 1a) from four high quality RCTs and one fair quality RCT that VR treadmill gait training is more effective than comparison interventions (conventional treadmill gait training, physical exercises, no additional training) in improving mobility in patients with chronic stroke.

Note: Results from one high quality RCT showed that VR treadmill training was not more effective than community ambulation training.

Obstacle clearance
Not Efective
2B

One fair quality RCT (Jaffe et al., 2004) investigated the effect of VR-based training on obstacle clearance performance in patients with chronic stroke. This fair quality RCT randomized patients to receive VR treadmill gait training or non-VR gait training. Obstacle clearance performance was measured by the height of the longest obstacle successfully negotiated at post-treatment (2 weeks) and at follow-up (4 weeks). No significant between-group differences were found at either time point.

Conclusion: There is limited evidence (Level 2b) from one fair quality RCT that VR treadmill gait training is not more effective than a comparison intervention (non-VR gait training) in improving obstacle clearance performance in patients with chronic stroke.

Walking endurance
Conflicting
4

Two high quality RCTs (Kang et al., 2012; Kim et al., 2016) and one fair quality RCT (Jaffe et al., 2004) investigated the effect of VR-based training on walking endurance in patients with chronic stroke.

The first high quality RCT (Kang et al., 2012) randomized patients to receive VR treadmill gait training with optic flow, conventional treadmill gait training or physical exercises; all groups received conventional physical therapy. Walking endurance was measured by the 6-Minute Walk Test (6MWT) at post-treatment (4 weeks). Significant between-group differences were found, favoring VR treadmill gait training with optic flow vs. conventional treadmill gait training; and favoring VR treadmill gait training with optic flow vs. physical exercises.

Note: There were no significant differences between conventional treadmill gait training and physical exercises.

The second high quality RCT (Kim et al., 2016) randomized patients to receive VR treadmill gait training, time-matched community ambulation training, or no additional training; all groups received physical therapy. Walking endurance was measured by the 6MWT at post-treatment (4 weeks). No significant differences were found between VR treadmill gait training and community ambulation training, or between VR treadmill gait training and no training.

Note: There was a significant between-group difference in walking endurance, in favour of community ambulation training vs. no training.

The fair quality RCT (Jaffe et al., 2004) randomized patients to receive VR treadmill gait training or non-VR gait training. Walking endurance was measured by the 6MWT at post-treatment (2 weeks) and at follow-up (4 weeks). No significant between-group differences were found at either time point.

Conclusion: There is conflicting evidence (Level 4) regarding the effect of VR treadmill gait training on walking endurance in patients with chronic stroke. One high quality RCT found that VR treadmill training was more effective than conventional treadmill training and physical exercises, whereas a second high quality RCT and a fair quality RCT found it was not more effective than no training and non-VR gait training.

Walking speed
Effective
1A

Two high quality RCTs (Yang et al., 2008; Kang et al., 2012) investigated the effect of VR-based training on walking speed in patients with chronic stroke.

The first high quality RCT (Yang et al., 2008) randomized patients to receive VR treadmill gait training or conventional treadmill gait training. Walking speed was measured by the 10-meter walking test at post-treatment (3 weeks) and at follow-up (1 month). Significant between-group differences were found at post-treatment, favoring VR treadmill gait training vs. conventional treadmill gait training; differences did not remain significant at follow-up.

The second high quality RCT (Kang et al., 2012) randomized patients to receive VR treadmill gait training with optic flow, conventional treadmill gait training or physical exercises; all groups received conventional physical therapy. Walking speed was measured by the 10-meter walking test at post-treatment (4 weeks). Significant between-group differences were found, favoring VR treadmill gait training with optic flow vs. conventional treadmill gait training; and favoring VR treadmill gait training with optic flow vs. physical exercises.

Note: There were no significant differences between conventional treadmill gait training and physical exercises.

Conclusion: There is strong evidence (Level 1a) from two high quality RCTs that VR treadmill gait training is more effective than comparison interventions (conventional treadmill gait training, physical exercises) in improving walking speed in patients with chronic stroke.

Phase not specific to one period - VR balance training

Balance
Not Effective
2B

One quasi-experimental design study (Cikajlo et al., 2012) investigated the effect of VR-based training on balance in patients with stroke. This quasi-experimental design study allocated patients with subacute/chronic stroke to receive VR balance training or non-VR balance training; both groups received conventional rehabilitation. Balance was measured by the Berg Balance Scale and timed stance (affected and non-affected limbs) at post-treatment (3 weeks). No significant between-group differences were found.

Conclusion: There is limited evidence (Level 2b) from one quasi-experimental design study that VR balance training is not more effective than a comparison intervention (non-VR balance training) in improving balance in patients with stroke.

Mobility
Not Effective
2B

One quasi-experimental design study (Cikajlo et al., 2012) investigated the effect of VR-based training on mobility in patients with stroke. This quasi-experimental design study allocated patients with subacute/chronic stroke to receive VR balance training or non-VR balance training; both groups received conventional rehabilitation. Mobility was measured by the Timed Up and Go Test at post-treatment (3 weeks). No significant between-group differences were found.

Conclusion: There is limited evidence (Level 2b) from one quasi-experimental design study that VR balance training is not more effective than a comparison intervention (non-VR balance training) in improving mobility in patients with stroke.

Pelvis control
Not Effective
2B

One fair quality RCT (Mao et al., 2015) investigated the effect of VR-based training on pelvis control in patients with stroke. This fair quality RCT randomized patients with acute/subacute stroke to receive VR body-weight supported treadmill training or over ground walking training. Pelvis control (tilt, obliquity, rotation) was measured by the Vicon Motion Capture System + Plug-in-Gait model at post-treatment (3 weeks). No significant between-group differences were found.

Conclusion: There is limited evidence (Level 2b) from one fair quality RCT that VR treadmill training is not more effective than a comparison intervention (over ground walking training) in improving pelvis control in patients with stroke.

Walking speed
Not Effective
2B

One quasi-experimental design study (Cikajlo et al., 2012) investigated the effect of VR-based training on walking speed in patients with stroke. This quasi-experimental design study allocated patients with subacute/chronic stroke to receive VR balance training or non-VR balance training; both groups received conventional rehabilitation. Walking speed was measured by the 10 Meter Walk Test at post-treatment (3 weeks). No significant between-group differences were found.

Conclusion: There is limited evidence (Level 2b) from one quasi-experimental designs study that VR balance training is not more effective than a comparison intervention (non-VR balance training) in improving walking speed in patients with stroke.

References

Cikajlo, I., Rudolf, M. Goljar, N., Burger, H., & Matjacic, Z. (2012). Telerehabilitation using virtual reality task can improve balance in patients with stroke. Disability & Rehabilitation, 34(1), 13-8.https://www.ncbi.nlm.nih.gov/pubmed/21864205

Cho, K. H., & Lee, W. H. (2013). Virtual walking training program using a real-world video recording for patients with chronic stroke: a pilot study. American journal of physical medicine & rehabilitation 92,(5), 371-384.Virtual Walking Training Program

Cho, K. H., & Lee, W. H. (2014). Effect of treadmill training based real-world video recording on balance and gait in chronic stroke patients: a randomized controlled trial. Gait & posture, 39(1), 523-528.http://www.sciencedirect.com/science/article/pii/S0966636213005985

Jaffe, D.L., Brown, D.A., Pierson-Carey, C.D., Buckley, E.L., & Lew, HL. (2004). Stepping over obstacles to improve walking in individuals with poststroke hemiplegia. Journal of Rehabilitation Research & Development, 41, 283-292.https://www.ncbi.nlm.nih.gov/pubmed/15543446

Jung, J., Yu, J., & Kang, H. (2012). Effects of virtual reality treadmill training on balance and balance self-efficacy in stroke patients with a history of falling. Journal of Physical Therapy Science, 24(11), 1133-1136.https://www.jstage.jst.go.jp/article/jpts/24/11/24_1133/_article/-char/ja/

Kang, H. K., Kim, Y., Chung, Y., & Hwang, S. (2012). Effects of treadmill training with optic flow on balance and gait in individuals following stroke: randomized controlled trials. Clinical rehabilitation, 26(3), 246-255.http://journals.sagepub.com/doi/abs/10.1177/0269215511419383

Kim, J.H., Jang, S.H., Kim, C.S., Jung, J.H., & You, J.H. (2009) Use of virtual reality to enhance balance and ambulation in chronic stroke: A double-blind, randomized controlled study. American Journal of Physical Medicine & Rehabilitation, 88, 693–701.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4211206/

Kim, N., Park, Y., & Lee, B. H. (2015). Effects of community-based virtual reality treadmill training on balance ability in patients with chronic stroke. Journal of physical therapy science, 27(3), 655-658.https://www.jstage.jst.go.jp/article/jpts/27/3/27_jpts-2014-536/_article

Kim, N., Lee, B., Kim, Y., & Min, W. (2016). Effects of Virtual Reality Treadmill Training on Community Balance Confidence and Gait in People Post-Stroke: a randomized controlled trial. Journal of Experimental Stroke & Translational Medicine, 9(1).Effects of virtual reality treadmill training on community balance confidence and gait in people post stroke

Lee, C. H., Kim, Y., & Lee, B. H. (2014). Augmented reality-based postural control training improves gait function in patients with stroke: Randomized controlled trial. Hong Kong Physiotherapy Journal, 32(2), 51-57.http://www.sciencedirect.com/science/article/pii/S1013702514000219

Lloréns, R., Alcaniz, A., Colomer, C., & Navarro, M.D. In Wiederhold, B., & Riva, G. (Eds.). (2012). Balance recovery through virtual stepping exercises using Kinect skeleton tracking: a followup study with chronic stroke patients. Annual Review of Cybertherapy and Telemedicine 2012: Advanced Technologies in the Behavioral, Social and Neurosciences, 181, 108-112.http://www.nrhb.webs.upv.es/wp-content/uploads/2015/07/NRHB_2012_CYBER_1.pdf

Lloréns, R., Gil-Gómez, J. A., Alcañiz, M., Colomer, C., & Noé, E. (2015). Improvement in balance using a virtual reality-based stepping exercise: a randomized controlled trial involving individuals with chronic stroke. Clinical rehabilitation, 29(3), 261-268.http://journals.sagepub.com/doi/abs/10.1177/0269215514543333

Mao, Y., Chen, P., Li, L., Li, L., & Huang, D. (2015). Changes of pelvis control with subacute stroke: A comparison of body-weight-support treadmill training coupled virtual reality system and over-ground training. Technology and health care, 23(s2), S355-S364.http://content.iospress.com/articles/technology-and-health-care/thc972

Mirelman, A., Bonato, P., & Deutsch, J.E. (2008). Effects of training with a robot-virtual reality system compared with a robot alone on the gait of individuals after stroke. Stroke, 40, 169-174.https://www.ncbi.nlm.nih.gov/pubmed/18988916

Mirelman, A., Patritti, B.L., & Bonato, P., & Deutsch, J. (2010). Effects of virtual reality training on gait biomechanics of individuals post-stroke. Gait & Posture, 31, 433–437.https://www.ncbi.nlm.nih.gov/pubmed/20189810

Park, Y. H., Lee, C. H., & Lee, B. H. (2013). Clinical usefulness of the virtual reality-based postural control training on the gait ability in patients with stroke. Journal of exercise rehabilitation, 9(5), 489.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3836554/

Yang, Y-R., Tsai, M.P., Chuang T.-Y., Sung W.-H., & Wang, R.-Y. (2008). Virtual reality-based training improves community ambulation in individuals with stroke: A randomized controlled trial. Gait and Posture, 28(2), 201-206.https://www.ncbi.nlm.nih.gov/pubmed/18358724

Yang, S., Hwang, W.-H., Tsai Y.-C., Liu F.-K., Hsieh L.-F., & Chern J.-S. (2011). Improving balance skills in patients who had stroke through virtual reality treadmill training. American Journal of Physical Medicine & Rehabilitation, 90(12), 969-78.https://www.ncbi.nlm.nih.gov/pubmed/22019971

Yom, C., Cho, H. Y., & Lee, B. (2015). Effects of virtual reality-based ankle exercise on the dynamic balance, muscle tone, and gait of stroke patients. Journal of physical therapy science, 27(3), 845-849.https://www.jstage.jst.go.jp/article/jpts/27/3/27_jpts-2014-575/_article

You, S.H., Jang, S.H., Kim, Y-H., Hallett, M., Ahn, S. H., Kwon, Y-H, Kim, J.H. Lee, M. Y. (2005). Virtual reality-induced cortical reorganization and associated locomotor recovery in chronic stroke: An experimenter-blind randomized study. Stroke, 36, 1166-1171.http://stroke.ahajournals.org/content/strokeaha/36/6/1166.full.pdf

Excluded Studies:

bin Song, G., & cho Park, E. (2015). Effect of virtual reality games on stroke patients’ balance, gait, depression, and interpersonal relationships. Journal of physical therapy science, 27(7), 2057-2060.

Reason for exclusion: gaming intervention.

Cho, K. H., Lee, K. J., & Song, C. H. (2012). Virtual-reality balance training with a video-game system improves dynamic balance in chronic stroke patients. The Tohoku journal of experimental medicine, 228(1), 69-74.

Reason for exclusion: gaming intervention using WiiFit console.

Cho, K.H., Kim, M.K., Lee, H.J., & Lee, W.H. (2015) Virtual reality training with cognitive load improves walking function in chronic stroke patients. Tohoku Journal of Experimental Medicine, 236 (4), 273-80.

Reason for exclusion: both treatment groups received VR training: VR training with cognitive load vs. treadmill VR training.

da Fonseca, E. P., da Silva, N. M. R., & Pinto, E. B. (2017). Therapeutic effect of virtual reality on post-stroke patients: Randomized clinical trial. Journal of Stroke and Cerebrovascular Diseases, 26(1), 94-100.

Reason for exclusion: gaming intervention.

Deutsch, J.E., Burdea, J.L., & Boian, R. (2001). Post-Stroke Rehabilitation with the Rutgers Ankle System: A Case Study. Presence, 10, 416-430.

Reason for exclusion: case-report

Flynn, S., Palma, P., & Bender, A. (2007). Feasibility of using the Sony PlayStation 2 gaming platform for an individual poststroke: a case report. Journal of Neurologic Physical Therapy, 31, 180–189.

Reason for exclusion: case-report

Fung, J., Richards, C.L., Malouin, F., McFadyen, B.J., & Lamontagne, A. (2006). A treadmill and motion coupled virtual reality system for gait training post-stroke. Cyberpsychology & Behavior, 9, 157-162.

Reason for exclusion: Feasibility study (n=2).

Katz, N., Ring, H., Naveh, Y., Kizony, R., Feintuch, U., Weiss, P.L. (2005). Interactive virtual environment training for safe street crossing of right hemisphere stroke patients with unilateral spatial neglect. Disability and Rehabilitation, 27, 1235-1244.

Reason for exclusion: intervention targets cognitive function and visuospatial abilities, namely unilateral spatial neglect, and not lower extremities/mobility/balance. No outcomes pertaining to lower-extremities, balance, nor mobility are included.

Kim, D.Y., Ku, J., Chang W.H. et al. (2010). Assessment of post-stroke extrapersonal neglect using a three-dimensional immersive virtual street crossing program. Acta Neurologica Scandinavica, 121, 171–177.

Reason for exclusion: Not an intervention-based study.

Lloréns, R., Noé, E., Colomer, C., & Alcañiz, M. (2015). Effectiveness, usability, and cost-benefit of a virtual reality–based telerehabilitation program for balance recovery after stroke: A randomized controlled trial. Archives of physical medicine and rehabilitation, 96(3), 418-425.Reason for exclusion: both treatment groups received VR training.

McEwen, D., Taillon-Hobson, A., Bilodeau, M., Sveistrup, H., & Finestone, H. (2014). Virtual Reality Exercise Improves Mobility After Stroke. Stroke, 45(6), 1853-1855.

Reason for exclusion: both treatment groups received VR training.

San Lam, Y.S., Man, D.W., Tam, S.F., Weiss, P.L. (2006). Virtual reality training for stroke rehabilitation. Neurorehabilitation, 21, 245-253.

Reason for exclusion: intervention targets cognitive function rehabilitation, and not lower extremities/mobility/balance. No outcomes pertaining to lower-extremities, balance, nor mobility are included.

Singh, D. K. A., Nordin, N. A. M., Aziz, N. A. A., Lim, B. K., & Soh, L. C. (2013). Effects of substituting a portion of standard physiotherapy time with virtual reality games among community-dwelling stroke survivors. BMC neurology, 13(1), 199.Reason for exclusion: gaming intervention.

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