VR and Orthoses for Rehabilitation in Multiple Sclerosis

Official title

Virtual Reality for Gait Training in Multiple Sclerosis (VIRTUE): an Interventional Feasibility Study

Overview

This non-drug, non-medical device, interventional study explores the feasibility of integrating virtual reality (VR) with wearable sensors to support gait training using a passive orthosis in individuals with multiple sclerosis (MS). The aim is to determine whether this approach can enhance clinical gait assessment and facilitate orthosis adaptation by replicating real-life scenarios within a safe and controlled environment. The virtual environment, accessed through a head-mounted display, will be delivered via a custom simulator incorporating standardized gait tasks embedded in everyday settings. This system is designed to minimize the artificial influence of clinical settings on walking performance, while providing clinicians with objective gait data for more comprehensive evaluation.

Detailed description

Patients with multiple sclerosis (MS) often experience significant gait impairments that impact their autonomy and overall quality of life. One of the primary rehabilitation strategies involves the use of walking braces. While these orthotic devices can support ambulation, their effective integration into daily life typically requires a period of adaptation and specific training. Traditionally, gait training and orthosis prescription occur in clinical settings, which may not fully reflect the real-world challenges that patients encounter. Moreover, current clinical assessments rely primarily on subjective observations and standardized scales, which may lack the sensitivity and objectivity needed to capture the full complexity of gait performance.

virtual reality (VR) offers a promising opportunity to simulate realistic walking environments in a controlled and safe setting, such as an outpatient clinic, potentially enhancing the outcomes of gait rehabilitation. Another promising technology in this domain is the use of wearable inertial sensors, which have been shown to effectively measure gait and postural parameters in people with MS. A further challenge associated with the use of orthotic devices is the physical and psychological stress they may cause, which can lead patients to discontinue their use. To evaluate such discomfort more objectively, recent studies have explored the use of physiological signal analysis and machine learning (ML) algorithms as an alternative or complement to self-reported questionnaires.

The integration of VR with wearable inertial and physiological sensors may allow for a more comprehensive and objective assessment of a patient's adaptation to walking braces. However, no validated system currently exists that combines these technologies for gait assessment and training with passive orthoses in people with MS.

The VIRTUE study aims to address this gap by developing and evaluating a VR-based platform (VIRTUE4MS) that replicates real-life scenarios, such as navigating through a museum, park, or grocery store, and enables standardized gait assessments within immersive environments. The system will employ both inertial and physiological wearable sensors to gather data on gait dynamics and user experience, ultimately supporting clinical decision-making regarding orthotic use. In this study, 12 patients with MS will perform walking and balance tasks over three sessions (T1, T2, T3), both with and without the Exoband brace, in VR and real-world conditions. Ultimately, this study seeks to explore an innovative, technology-supported approach to orthosis assessment and gait training that could complement traditional clinical tools and contribute to more effective, personalized rehabilitation strategies for individuals with MS.

Interventions

• Other VR and walking brace-based gait rehabilitation
  The study implements the use of VR and wearable sensors to enhance gait analysis in clinical practice. Participants will take part in two outpatient sessions (T1 and T2) involving the use of VR and wearable sensors, during which they will be asked to complete standardized gait tests and questionnaires. These two sessions will be separated by a one-week home phase (Th), during which participants will wear the walking brace in their daily activities and their gait and physiological data will be re

Primary outcome measures

• Score of the standardized tests and gait parameters [Time frame: From T1 (day 2) to T2 (day 9)]

Secondary outcome measures (12)

• NASA-TLX (NASA Task Load Index) questionnaire score [Time frame: T1 (day 2); T2 (day 10); T3 (day 70)]
• MSAQ (Motion Sickness Assessment Questionnaire) questionnaire score [Time frame: T0 (day 1); T1 (day 2); T2 (day 10)]
• IPQ (iGroupPresence Questionnaire) questionnaire score [Time frame: T1 (day 2); T2 (day 10)]
• MusiQoL (Multiple Sclerosis International Quality of Life) questionnaire score [Time frame: T1 (day 2), T2 (day 10), T3 (day 70)]
• BBS (Berg Balance Scale) questionnaire score [Time frame: T1 (day 2); T2 (day 10); T3 (day 70)]
• EDSS (Expanded Disability Status Scale) questionnaire score [Time frame: T0 (day 1)]
• MFIS (Modified Fatigue Impact Scale) questionnaire score [Time frame: T0 (day 1); T1 (day 2); Th (day 3-9); T2 (day 10); T3 (day 70)]
• MSWS-12 (Twelve-Item Multiple Sclerosis Walking Scale) questionnaire score [Time frame: T1 (day 2); T2 (day 10); T3 (day 70)]
• Timed 25-Foot Walk Test (T25FW) test score [Time frame: T1 (day 2); T2 (day 10); T3 (day 70)]
• 2MWT (2-Minute Walk Test) test score [Time frame: T1 (day 2); T2 (day 10); T3 (day 70)]
• TAM (Technology Acceptance Model) questionnaire score [Time frame: T0 (day 1); T2 (day 10)]
• TLSQ-WT (Tele-healthcare Satisfaction Questionnaire - Wearable Technology) questionnaire score [Time frame: T2 (day 10)]

Eligibility criteria

Inclusion criteria

• Confirmed diagnosis of multiple sclerosis
• Age between 18 and 65 years
• Both sexes
• Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS > 100)
• Expanded Disability Status Scale (EDSS between 3 and 6 inclusive)
• Berg Balance Scale (BBS ≥ 46)
• Indication for the use of the Exoband orthosis for gait assistance
• Modified Fatigue Impact Scale (MFIS) physical subscale ≤ 20
• Signed informed consent

Exclusion criteria

• Presence of severe or current visual or auditory impairments
• Relapses within the last 3 months
• Presence of severe anxiety or depression
• Severe spasticity patterns in the lower limbs or fixed distal tendon contractures
• Presence of motion sickness symptoms induced by virtual reality (VR)

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation

N/A

Model

Single group

Masking

Open label

Primary purpose

Screening

Study locations

Italy · 2 centers

• IRCCS Istituto delle Scienze Neurologiche di Bologna - AUSL of Bologna — Bologna
• IRCCS Istituto delle Scienze Neurologiche di Bologna - AUSL of Bologna — Bologna

Publications

• Tsai MF, Bandini A, Wang RH, Zariffa J. Capturing Representative Hand Use at Home Using Egocentric Video in Individuals with Upper Limb Impairment. J Vis Exp. 2020 Dec 23;(166). doi: 10.3791/61898. PMID 33427235
• Casuso-Holgado MJ, Martin-Valero R, Carazo AF, Medrano-Sanchez EM, Cortes-Vega MD, Montero-Bancalero FJ. Effectiveness of virtual reality training for balance and gait rehabilitation in people with multiple sclerosis: a systematic review and meta-analysis. Clin Rehabil. 2018 Sep;32(9):1220-1234. doi: 10.1177/0269215518768084. Epub 2018 Apr 13. PMID 29651873
• Peruzzi A, Cereatti A, Della Croce U, Mirelman A. Effects of a virtual reality and treadmill training on gait of subjects with multiple sclerosis: a pilot study. Mult Scler Relat Disord. 2016 Jan;5:91-6. doi: 10.1016/j.msard.2015.11.002. Epub 2015 Nov 6. PMID 26856951
• Bettoni E, Ferriero G, Bakhsh H, Bravini E, Massazza G, Franchignoni F. A systematic review of questionnaires to assess patient satisfaction with limb orthoses. Prosthet Orthot Int. 2016 Apr;40(2):158-69. doi: 10.1177/0309364614556836. Epub 2014 Nov 26. PMID 25428901
• Marimon X, Mengual I, Lopez-de-Celis C, Portela A, Rodriguez-Sanz J, Herraez IA, Perez-Bellmunt A. Kinematic Analysis of Human Gait in Healthy Young Adults Using IMU Sensors: Exploring Relevant Machine Learning Features for Clinical Applications. Bioengineering (Basel). 2024 Jan 23;11(2):105. doi: 10.3390/bioengineering11020105. PMID 38391591
• Panizzolo FA, Cimino S, Pettenello E, Belfiore A, Petrone N, Marcolin G. Effect of a passive hip exoskeleton on walking distance in neurological patients. Assist Technol. 2022 Sep 3;34(5):527-532. doi: 10.1080/10400435.2021.1880494. Epub 2021 Mar 5. PMID 33481693
• Karunakaran KK, Pamula SD, Bach CP, Legelen E, Saleh S, Nolan KJ. Lower extremity robotic exoskeleton devices for overground ambulation recovery in acquired brain injury-A review. Front Neurorobot. 2023 May 25;17:1014616. doi: 10.3389/fnbot.2023.1014616. eCollection 2023. PMID 37304666
• Homayuni A, Abedini S, Hosseini Z, Etemadifar M, Ghanbarnejad A. Explaining the facilitators of quality of life in patients with multiple sclerosis: a qualitative study. BMC Neurol. 2021 May 11;21(1):193. doi: 10.1186/s12883-021-02213-9. PMID 33975555

Identifiers

NCT: NCT07096700 · VIRTUE

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗