Immersive Virtual Reality to Improve Gait in Parkinson's Disease

Study Overview
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Brief Summary
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Parkinson's Disease (PD) patients suffer from gait impairments responsible for falls and bad quality of life: reduced speed and stride length, randomness in stride duration variability (reduced Long-Range Autocorrelations (LRA)). On the other hand, treadmill walking has shown long-term effectiveness on PD patients' gait and quality of life. The purpose of this single blinded randomized controlled trial is to study the effect of a combination of immersive virtual reality and treadmill walking on LRA.

Detailed Description
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BACKGROUND Parkinson's disease (PD) is the second most common degenerative neurological disease. PD induces gait disorders that lead to increased risk of falls. These falls seriously affect patients' quality of life and generate significant health care costs. Unfortunately, gait disorders do not respond well to drug treatments and their management is mainly based on rehabilitation treatment. The rehabilitation approach comprises two steps: a functional assessment of locomotor capacities followed by completion of a therapeutic physical exercise program. Like heart rate, stride duration varies in the short and long term according to a complex dynamic of temporal variations. These variations present long-range autocorrelations (LRA): the stride duration does not vary randomly but in a structured way. The study of LRA is based on complex mathematical methods requiring recording of 512 consecutive gait cycles. LRA are altered in PD patients whose gait rhythm is excessively random. Alteration of LRA is correlated with neurological impairments (Hoehn & Yahr scale and UPDRS) and patients' locomotor stability (ABC scale & BESTest). Measurement of LRA would be the first available objective and quantitative biomarker of stability and risk of falling in patients with PD. Guidelines concerning rehabilitation programs for PD patients are based on education (prevention of falls and inactivity,...), physical exercises, functional training (double task, complex tasks,...), learning, adaptation strategies (cueing) and action observation. The combination between immersive virtual reality (iVR) and treadmill walking will be developped. Treadmill walking has shown long-term effectiveness on PD patients' gait and quality of life. A study carried out recently has shown that a single treadmill session reduces the stride duration variability during the intervention. There remains then to determine the long-term effect of this rehabilitation method on LRA, apart from the intervention, when walking overground. Combining iVR with treadmill walking rehabilitation offers interesting insights. Indeed, for stroke patients, this combination is more effective than classical techniques. For PD patients, non-immersive virtual reality methods (Wii, Kinect) have shown relative efficacy. Indeed, the use of non-immersive virtual reality on treadmill induces more efficient cognitive engagement and frontal lobe activation among PD patients. Non immersive VR gives longer-term effects and a greater decrease in the number of falls than without virtual reality. Furthermore, iVR makes it possible to give a functional character to reeducation and to enrich feedbacks. Indeed, iVR allows to give patients a visual flow when walking on treadmill as if they were walking overground and patients could benefit from it. But apart from a feasibility study, the therapeutic interest of iVR has not been studied yet for PD patients, especially iVR combined with treadmill walking. iVR is now easily accessible and its price is reduced, suggesting a potential for everyday clinical practice. Indeed, these new devices of good quality seem to have a good potential for neurorehabilitation. The purpose of this single blinded randomized controlled trial is then to study the effect of a comibination of immersive virtual reality and treadmill walking on LRA. METHODS Patients: This study will be unicentric. 46 PD patients will be included, 23 in the intervention group and 23 in the control group. Patients will be recruited from the department of Neurology of Cliniques universitaires Saint-Luc (Brussels, Belgium). The study was approved by the local ethics committee. All patients will give informed written consent to the study. Eligibility criteria will be described in another section. Functional assessment: Functional assessments will cover the 3 domains of International Classification of Functioning, Disability and Health (ICF) : body functions and structures, activity and participation. Assessments will be described in another section. LRA analysis: At least 512 consecutive gait cycles will be recorded when walking overground at a self-selected speed on an oval track of 42 meters. The duration of each cycle will be measured using an accelerometer, placed on the head of the fibula, at an acquisition frequency of 512 Hz. LRA will be analyzed using the integrated method validated by our team for the analysis of physiological signals. This method combines calculation of the Hurst exponent (H) obtained by the Rescaled Range Analysis and the α exponent obtained by the Power Spectral Density Analysis. Consistency of the values of H and α is verified through the relation d = H-[(1 + α) / 2]. The presence of LRA can be shown with a high level of proof when these 3 conditions are met: H > 0.5 α is significantly different from 0 and less than 1 d ≤ 0.10 If an inconsistency appears between H and α, the Randomly Shuffled Surrogate Data Test is applied in order to reject null hypothesis of an absence of temporal structure in studied series. Procedure: PD patients will follow a total of 18 treadmill exercise sessions with 3 sessions a week spread over 6 weeks. Sessions will be held at Cliniques universitaires Saint-Luc. During sessions, patients will walk 45 minutes at their comfortable speed on the treadmill with 1 pause allowed if necessary. The speed is determined according to the following technique: increase of the treadmill speed in increments of 0.10 m/s, with a starting speed of 0.15 m/s, until that the patient indicates that speed is too fast. Speed is then reduced by 0.10 m/s to have a comfortable walking speed. Every week, this walking speed will be re-evaluated. When walking on treadmill, patients will be secured with a harness (LiteGait, Mobility Research, Inc.). Patients from the intervention group will wear a virtual reality headset while walking on the treadmill. Patients will walk in a straight line in a coherent, immersive and simple virtual environment created from a graphics software (Unity, USA). Before the first session, a 15-minute session will focus on patient familiarization with iVR. Patients from the control group will walk on the treadmill without iVR. Patients will also receive a short familiarization to the treadmill before strating the experimentation. Statistical analyses: To compare between the effect of the different treatments proposed by the two studies on LRA (primary outcome), a two-way repeated measures ANOVA (Group x Time) will be performed.

Official Title
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Use of Immersive Virtual Reality on Treadmill to Improve Gait in Parkinson's Disease: a Single Blinded, Randomized Controlled Trial

Conditions
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Parkinson Disease, Gait Disorders, Neurologic

Intervention / Treatment
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* Other: Treadmill + VR
* Other: Treadmill


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Parkinson's Disease diagnosis made according to UK Brain Bank criteria Hoehn and Yahr score of 1 to 3 (physically independent, able to walk unassisted) Optimal drug treatment for at least 4 weeks at the time of inclusion In ON phase during assessments and treatment sessions Exclusion Criteria: Other pathologies that increase risk of falling Other pathologies that increase risk of nausea and vertigo Contraindication to physical exercising (ACSM criteria) Freezing of gait
Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Treatment
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Double


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Intervention group<br> | Other: Treadmill + VR<br>* Patients will walk on the tredmill with the virtual reality headset. Patients will walk in a straight line in a coherent, immersive and simple virtual environment. Before the first session, a 15-minute session will focus on patient familiarization with iVR<br>|
| Active Comparator: Control group<br> | Other: Treadmill<br>* Patients will walk on the treadmill without iVR. Patients will also receive a short familiarization to the treadmill before strating the experimentation.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Long-Range Autocorrelations: H exponent | First, stride duration will be assessed using accelerometers. After this, temporal varibility of stride duration will be assessed using the Rescaled Range Analysis (H exponent) to get the Long Range Autocorrelations. | Change from baseline in H exponent at an expected average of 6 (T1), 18 (T2) and 30 (T3) weeks | 
| Long-Range Autocorrelations: Alpha exponent | First, stride duration will be assessed using accelerometers. After this, temporal varibility of stride duration will be assessed using the Power Spectral Density (Alpha exponent) to get the Long Range Autocorrelations. | Change from baseline in Alpha exponent at an expected average of 6 (T1), 18 (T2) and 30 (T3) weeks | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Mean gait speed | Total walking distance (m)/ Acquisition duration (s) | Change from baseline in mean gait speed at an expected average of 6 (T1), 18 (T2) and 30 (T3) weeks | 
| Step length | Gait speed (m/s)*60/Gait cadence (steps/min) | Change from baseline in step length at an expected average of 6 (T1), 18 (T2) and 30 (T3) weeks | 
| Gait cadence | Total number of steps (#)/Acquisition duration (min) | Change from baseline in gait cadence at an expected average of 6 (T1), 18 (T2) and 30 (T3) weeks | 
| Coefficient of variation of stride duration | [SD/mean stride duration] * 100 | Change from baseline in coefficient of variation at an expected average of 6 (T1), 18 (T2) and 30 (T3) weeks | 
| Movement Disorder Society-Unified Parkinson Disease Rating Scale (MDS-UPDRS) | A global scale about Parkinson's Disease symptoms ranging from 0-272. MDS-UPDRS part III is the motor subscale ranging from 0-132. Higher values represent a worse outcome. | Change from baseline in MDS-UPDRS at an expected average of 6 (T1), 18 (T2) and 30 (T3) weeks | 
| 2 minutes walk distance |  | Change from baseline in 2 minutes walk distance at an expected average of 6 (T1), 18 (T2) and 30 (T3) weeks | 
| Balance Evaluation Systems Test (BESTest) |  | Change from baseline in BESTest at an expected average of 6 (T1), 18 (T2) and 30 (T3) weeks | 
| Simplified version of the Activities-specific Balance Confidence Scale (ABC-Scale) | It is a questionnaire to assess the degree of confidence of the person in his balance associated with gestures of daily life. The score is a percentage obtained as follows: (total score obtained from the 15 items / 45) x 100. Minimum score is 0% and maximum score is 100%. Each item scores from 0 to 3. Higher values represent a better outcome. | Change from baseline in ABC-Scale at an expected average of 6 (T1), 18 (T2) and 30 (T3) weeks | 
| Fall diary | Number of falls that occur during the follow up, assessed by the patient | Change from baseline in number of falls at an expected average of 6 (T1), 18 (T2) and 30 (T3) weeks | 
| The 39-items Parkinson's Disease Questionnaire (PDQ-39) | This is a 39 items quality of life questionnaire specific to Parkinson's disease. Each item scores from 0 to 4. The total score is from 0 to 156. Higher values represent a worse outcome. | Change from baseline in PDQ-39 at an expected average of 6 (T1), 18 (T2) and 30 (T3) weeks | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Parkinson's Disease, Virtual reality, Long range autocorrelations