Restorative Environments for Gait Therapy with VR (REGaitVR)

March 6, 2025 updated by: ETH Zurich

Effectiveness of Restorative Landscape Environments in Virtual Reality (VR) Used in Gait Training to Improve Gait Performance and Affect Restoration in Older Adults with Gait Insecurity - a Pilot Randomized Controlled Trial

The aim of our study is to investigate the effects of landscapes during gait therapy. The investigators will evaluate the impacts of restorative landscapes as they occur in urban, rural and forest environments. Older people will experience those landscapes using virtual reality (VR) goggles during their gait training. The investigators expect the landscapes to have an effect on the following three aspects: (1) stress reduction, (2) restoration of attention and (3) change in gait parameters. For this purpose, volunteers who are currently inpatient in one of our study centers and already participating in gait therapy will be assigned to a group. The control group will receive the standard therapy. The participants of the intervention groups will receive five additional VR training sessions to the standard therapy. In these sessions, the participants will walk through urban, rural and forest landscapes and perform balance improvement exercises. The five training sessions will take place within ten days. Allocation to the control or intervention groups and their landscapes is random. At the start and end of participation, tests defining stress levels and gait parameters are carried out so that comparisons can be made between before and after treatment. The goal of the study is to find out which type of landscape supports restoration and can therefore contribute to greater gait stability. The investigators expect that improved gait stability will be promoted by stress reduction and increased attention induced by the virtual environments. The investigators are investigating the consequences of repeated application of virtual landscapes and the relationship between the effect of the landscape and the preferences and habits of the study participants.

Study Overview

Detailed Description

In this study, the investigators aim to investigate the effectiveness of using restorative landscape environments during gait training to improve walking performance in older people with gait instability. The investigators will examine the effect of different landscape types (urban, rural, forest) on attention restoration and stress recovery based on a study protocol that defines the exact procedures to be used. The landscape scenes shown are prepared to be displayed in any head-mounted display (HMD). Thus, this training is not device specific. As a means to provide training in a virtual landscape the investigators will use as hardware a PC suitable for VR applications and a HTC Vive Pro Eye, which is a commercially available HMD widely used for gaming and for research projects on landscape perception. It can be used with a wireless adapter so that no cable connection between HMD and PC is required, which is more comfortable but not mandatory for conducting this study. This HMD has further the advantage of an included eye-tracker; however, eye-trackers can be adapted to other HMDs as well. The investigators investigate the general effects that virtual landscapes have on stress recovery, attention restoration, and subsequent changes in gait parameters. The results of this study allow us to draw generalizable conclusions about the creation of virtual landscapes that are ideal for supporting gait stability training.

This study examines the effectiveness of training sessions in one of three virtual scenes of different landscape types (urban, rural, and forest) in older adults with instability in gait compared to the usual care for gait instability. Training content and difficulty will be adapted to the individual's physical abilities. Before and after the intervention phase and during the training sessions, various low-risk measurements will be performed, including heart rate variability (HRV), electrodermal activity (EDA), recording of gait parameters, eye-tracking, and standardized interviews to assess recovery and stress management, landscape perception, and balance confidence.

This study contributes to basic research investigating how training in virtual landscapes can promote the improvement of gait stability by contributing to stress reduction as well as recovery of attention, and by providing safe environments for training close to everyday life.

World's population is ageing. This comes along with increasing health-related costs. While it is well known that experiencing landscapes can promote human restoration and foster human health, older people with physical impairments have limited access to landscapes. Therefore, recent research is investigating the benefits of simulated landscapes, in particular with regard to the restorative value of experiencing virtual landscapes. Furthermore, virtual reality (VR) is increasingly implemented in physical rehabilitation to improve walking ability, because it provides new motivating means for performing required exercises in controlled and save environments. Yet, highly immersive high-fidelity VR landscape environments are not employed in such settings although there is great potential to significantly alter the effectiveness of training interventions through their additional restorative effects. Further, it is still unclear which specific landscape elements in an environment foster or hinder the effect of restoration. The influence of the content characteristics of the VR environments needs to be further investigated, linking them to physiological responses, perceptions as well as to meanings and values they have for people.

Therefore, the main goal of the study "REGaitVR RCT" is (1) to investigate the effectiveness of using restorative landscape environments during gait training to improve walking performance in older people with gait instability, and (2) to analyse the effect of the meaning of landscape elements and psychophysiological responses on restoration. To this end, the investigators will examine the effect of different immersive VR landscape types (urban, rural, forest) on attention restoration and stress recovery, and subsequent changes in gait parameters of older people with gait instability in a randomized controlled pilot trial.

Study Type

Interventional

Enrollment (Estimated)

84

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

  • Name: Laura Schalbetter, MSc.
  • Phone Number: +41 (0)44 633 34 25
  • Email: schalaur@ethz.ch

Study Contact Backup

Study Locations

      • Schaffhausen, Switzerland, 8208
      • St. Gallen, Switzerland, 9000
        • Not yet recruiting
        • Geriatrische Klinik St. Gallen
        • Contact:
    • Zürich

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Older Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  • age: > 65 years
  • german-speaking
  • ability to give informed consent
  • attends gait safety training (usual care)
  • inpatient for a duration of min. 2 weeks in one of the study sites
  • items 7 - 15 of the De Morton Mobility Index (DEMMI): min. 2 points, max. 9 points
  • 3-minute walking distance: > 30 m without rest, with or without walking aids, overground walking on flat surface

Exclusion Criteria:

  • epilepsy
  • Partial weight bearing or conservatively or surgically treated billing with weight bearing as determined by symptoms
  • Severe hearing impairment (if not corrected with hearing aid)
  • Injuries to the eyes, face, or neck that prevent comfortable use of VR glasses.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Treatment
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: forest
virtual reality (VR) assisted gait therapy in a forest landscape
Participants in the intervention groups will receive 5 VR training sessions over 10 days in addition to their usual care. Each participant will wear the HMD for 25 minutes in each of this training sessions, whereby he or she will first sit for 5 minutes looking at a forest-landscape. This is followed by 20 minutes of independent exploration of the virtual environment by walking. Depending on the user's gait stability, walking aids (such as walking sticks or rollators) may be used. This phase aims at keeping the participant walking.
Experimental: urban
virtual reality (VR) assisted gait therapy in a urban landscape
Participants in the intervention groups will receive 5 VR training sessions over 10 days in addition to their usual care. Each participant will wear the HMD for 25 minutes in each of this training sessions, whereby he or she will first sit for 5 minutes looking at an urban-landscape. This is followed by 20 minutes of independent exploration of the virtual environment by walking. Depending on the user's gait stability, walking aids (such as walking sticks or rollators) may be used. This phase aims at keeping the participant walking.
Experimental: rural
virtual reality (VR) assisted gait therapy in a rural landscape
Participants in the intervention groups will receive 5 VR training sessions over 10 days in addition to their usual care. Each participant will wear the HMD for 25 minutes in each of this training sessions, whereby he or she will first sit for 5 minutes looking at a rural-landscape. This is followed by 20 minutes of independent exploration of the virtual environment by walking. Depending on the user's gait stability, walking aids (such as walking sticks or rollators) may be used. This phase aims at keeping the participant walking.
No Intervention: control
standard gait therapy

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Gait Stability
Time Frame: at day 0 and day 11
The German version of the Activities-specific Balance Confidence (ABC) Scale is used to assess balance self-confidence in older people. Self-report of fear of falling correlates with performance on the blindfolded and one-legged tests, and in addition, fear of falling can lead to activity limitation, resulting in a decline in physical performance. It has a 11-point response scale (no confidence 0% - 100% completely confident) and the overall score it calculated by summing the scores and dividing by the number of items (16). Cut-off scores are < 50% (lower level of physical functioning), 50-80% (moderate level) and > 80% (high level), a score smaller than 67% indicated a risk for falling. The ABC scale can be complected within 5-10 minutes.It could show an internal consistency of the ABC scale of 0.94 and a test-retest reliability of 0.85 (95% CI, 0.68, 0.93).
at day 0 and day 11

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Variability (Gait Parameter)
Time Frame: day 0 - 11
[%] Defined as the coefficient of variation in cycle time, greater variability in step time may be a predictor of future falls. Fallers have significantly greater gait variability than non-fallers, who have comparable results to young subjects.
day 0 - 11
Speed (Gait Parameter)
Time Frame: day 0 - 11
[m/s] Fallers have a slower mean forward walking speed. Older people with slow walking speeds (≤ 1.3 m/s) are almost 8 times more likely to fall.
day 0 - 11
Asymmetry (Gait Parameter)
Time Frame: day 0 - 11
[%] Gait asymmetry increases with age and has been identified as a factor associated with falls in older adults. It is greater in people at risk of falling than in those who do not fall. Asymmetry is inversely correlated with preferred walking speed, and asymmetric gait is positively correlated with fall risk and dependence in activities of daily living.
day 0 - 11
Stance (Gait Parameter)
Time Frame: day 0 - 11
[%] The greater the variability in the proportion of the cycle in which the foot touches the ground, the greater the change for future mobility disability.
day 0 - 11
Max. Heel Clearance (Gait Parameter)
Time Frame: day 0 - 11
[m] The height of the foot during the swing phase appears to be an important gait parameter related to the risk of falling, as insufficient clearance can directly lead to stumbling, which is a major cause of falls in the elderly. Clearance parameters are a significant predictor of falls.
day 0 - 11
1-Minute-Sit-to-Stand Test (1-Min-STST)
Time Frame: at day 0 and day 11
It is a measure for mobility related functions and physical performance often used to access older people. It is a simple and quick exercise to assess the functional status of a patient and the gesture of getting up is an essential everyday activity. The test will be conducted according to the protocol of Hollier (2022, https://www.pcrs-uk.org/sites/default/files/2022-December-PCRU-1-MSTST.pdf). Reference Values of the sit-to-stand test given by Strassmann et al. 2013 (DOI: 10.1007/s00038-013-0504-z)
at day 0 and day 11
Perceived Restorativeness Scale (PRS) (Attention Restoration)
Time Frame: day 0 - 11
The operationalization of the Attention Restoration Theory (ART) can be found in the Perceived Restorativeness Scale (PRS) from Hartig et al. (1996). This scale is a valid and reliable measure of quality in restoration in different environments and has proved the sensitivity to theoretically relevant differences between environments. This self-report measurement is used in the majority of studies where researchers wanted to quantify restoration of environment. Answers can be given from 0 (not true at all) to 10 (Completely true).The scale has 26 items which can be divided into 7 categories: being away (max. point: 30), coherence (max. point: 24), compatibility (max. point: 30), fascination (max. point: 36), familiarity (max. point: 6), preference (max. point: 12), scope (may. point: 18). The investigators will use the German translation from Cervinka et al. (2016).
day 0 - 11
Perceived Stress Scale (PSS) (Stress Reduction)
Time Frame: day 0 - 11

To measure the stress level of patients in hospital the investigators will use the self-reported Perceived Stress Scale (PSS) which is the most widely used scale for measuring the perception of stress of an individual. The 10-item scale is easy to understand and the scoring is from 1 (Never) to 5 (Very Often). We will use the German version of the PSS-10 translated and verified by Schneider et al. (2020). A score from 10 to 50 can be reached.

  • Scores ranging from 10-23 would be considered low stress.
  • Scores ranging from 24-36 would be considered moderate stress.
  • Scores ranging from 37-50 would be considered high perceived stress

EDA can be measured with only two electrodes on the skin surface. The investigators will use the Empatica E4 wristband for the measurement.

day 0 - 11
Skin Conductance Levels (SCL) (Stress Reduction)
Time Frame: day 0 - 11

As a non-invasive method, Electrodermal Activity (EDA) measurements is used widely for detecting stress and emotions [101] as it is controlled by the autonomic nervous system. It's a real-time measurement, related to the level of physiological arousal. It is a widely used method in attention restoration studies (VR and real). The two components, tonic and phasic, can be used to analyse two different characteristics. The tonic, also called skin conductance level (SCL), is related to the slow-changing signals.

Stress Recovery can be shown by an lower level of skin conductance fluctuations.

EDA can be measured with only two electrodes on the skin surface. The investigators will use the Empatica E4 wristband for the measurement.

day 0 - 11
Non-Specific Skin Conductance Responses (NS-SCRs) (Stress Reduction)
Time Frame: day 0 - 11

As a non-invasive method, Electrodermal Activity (EDA) measurements is used widely for detecting stress and emotions as it is controlled by the autonomic nervous system. It's a real-time measurement, related to the level of physiological arousal. It is a widely used method in attention restoration studies (VR and real). The two components, tonic and phasic, can be used to analyse two different characteristics. the phasic component, also called skin conductance response (SCR), can be associated with a stimulus.

NS-SCRs is used for epoch-based studies and can indicate an overall arousal; there usually expressed as average of intervals with responses per unit of time; The mean amplitude of NS-SCR can indicate a change in the level of stress. During rest we have 1-3 NS-SCRs/min, whereas we can have over 20 NS-SCRs/min in high arousal situations.

EDA can be measured with only two electrodes on the skin surface. The investigators will use the Empatica E4 wristband for the measurement.

day 0 - 11
Event-related Skin Conductance Responses (ER-SCRs) (Stress Reduction)
Time Frame: day 0 - 11

For quantifying the response to a given stimulus (used in stimulus-driven studies).

EDA can be measured with only two electrodes on the skin surface. The investigators will use the Empatica E4 wristband for the measurement.

day 0 - 11
Standard deviation of all NN (normal-to-normal) intervals (SDNN) (Heart Rate Variability (HRV), Stress Reduction)
Time Frame: day 0 - 11

The fluctuation of the length of heart beat intervals, also called Heart Rate Variability (HRV) represents the ability of the heart to respond to stimuli (physiological and environmental). Several studies have shown, that HRV is a good indicator of stress as well as perceived valence (i.e., like or dislike) of image content. The measurement is non-invasive and can be done with the Empatica E4 wristband as well.

SDNN is the index of physiological resilience against stress

day 0 - 11
Root Mean Square of Successive Differences (RMSSD) (Heart Rate Variability (HRV), Stress Reduction)
Time Frame: day 0 - 11

The fluctuation of the length of heart beat intervals, also called Heart Rate Variability (HRV) represents the ability of the heart to respond to stimuli (physiological and environmental). Several studies have shown, that HRV is a good indicator of stress as well as perceived valence (i.e., like or dislike) of image content. The measurement is non-invasive and can be done with the Empatica E4 wristband as well.

RMSSD is known as the value for the body's ability to recover, the greater this number, the better.

day 0 - 11
LF/HF-ratio (Heart Rate Variability (HRV), Stress Reduction)
Time Frame: day 0 - 11

The fluctuation of the length of heart beat intervals, also called Heart Rate Variability (HRV) represents the ability of the heart to respond to stimuli (physiological and environmental). Several studies have shown, that HRV is a good indicator of stress as well as perceived valence (i.e., like or dislike) of image content. The measurement is non-invasive and can be done with the Empatica E4 wristband as well.

The ratio of the power in low frequency range (0.04Hz and 0.15Hz) to the power in high frequency range (0.15Hz and 0.4Hz) can indicate changes in stress levels

day 0 - 11
Heart Rate change (ΔHR) (Meaning / Valence of Landscapes)
Time Frame: day 1 - 10

In addition, HRV is an indicator of perceived valence (i.e., like or dislike) of image content.

Pre- and post-stimulus Inter-Beat Intervals (IBIs) are combined to construct a heart rate change time course with respect to the mean pre-stimulus heart rate (= baseline value). Immediate, dramatic deceleration in heart rate has been associated with negatively valent stimuli, whereas positively valent stimuli come along with an immediate deceleration followed by a slight acceleration before decelerating again.

day 1 - 10
Questionnaire / structured interview on landscape preferences and meanings ascribed to landscapes (Meaning / Valence of Landscapes)
Time Frame: day 0
Further, qualitative interviews will be used to gain further insight into individual landscape preferences and valuation, bonds and relations to the perceived landscapes, as well as meanings and feelings people associate with the landscapes: Where they live? Where have they used to live? Do they have access to the landscapes? Do they spend time there?
day 0
Gaze patterns
Time Frame: day 1 - 10
To understand the process of observation and to connect the single changes in HRV and EDA with what the user is focusing at in the virtual reality scene, the investiagtors will use eye-tracking to record the eye movements. Using eye tracking helps to understand the visual attention and arousal of the user, due to analysing the fixations within a scene. Analysing the duration of fixations can help to interpret greater interest and emotional arousal. Lower numbers of fixations and saccades and longer fixation durations are observed in natural scenes compared to urban views. Additionally the environmental components of the restorative benefits can be explored using eye tracking. The investigators will use the HMD HTC Vive Pro Eye VR with integrated eye tracking powered by Tobii (120Hz Frequency, 0.5°-1.1° Accuracy). For the recording we will use scripts provided by Chamberlain et al. (2023).
day 1 - 10

Other Outcome Measures

Outcome Measure
Measure Description
Time Frame
Age (Demographic data)
Time Frame: day 0
Age have been shown to influence heart rate responses to stress. Gait is affected by age.
day 0
Height (Demographic data)
Time Frame: day 0
Gait is affected by height.
day 0
Weight (Demographic data)
Time Frame: day 0
Gait is affected by weight
day 0
Gender (Demographic data)
Time Frame: day 0
These data will be used to analyse the study results for differences in gender. Gender have been shown to influence heart rate responses to stress
day 0
Education (Demographic data)
Time Frame: day 0
These data will be used to analyse the study results for differences in other relevant participant characteristics
day 0
Diagnosis and reason for gait stability training
Time Frame: day 0
These data will be used to analyse the study results for differences in reasons for training in gait stability
day 0
Time since last fall
Time Frame: day 0
A history of falls may increase fear of falling, which in turn can lead to gait abnormalities
day 0

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Investigators

  • Principal Investigator: Ulrike Wissen Hayek, Dr., ETH Zurich

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

April 23, 2024

Primary Completion (Estimated)

August 31, 2025

Study Completion (Estimated)

August 31, 2025

Study Registration Dates

First Submitted

February 26, 2024

First Submitted That Met QC Criteria

March 4, 2024

First Posted (Actual)

March 12, 2024

Study Record Updates

Last Update Posted (Actual)

March 25, 2025

Last Update Submitted That Met QC Criteria

March 6, 2025

Last Verified

March 1, 2025

More Information

Terms related to this study

Other Study ID Numbers

  • 2023-01894
  • 000005739 (Registry Identifier: Swiss National Clinical Trial Portal (SNCTP))

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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