VReeze: an open-source virtual reality for the examination of freezing of gait in Parkinson's disease - a study design of a crossover repeated measures study for validation

VReeze:一款用于研究帕金森病步态冻结的开源虚拟现实系统——一项交叉重复测量研究的设计验证

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Abstract

INTRODUCTION: Parkinson's disease is the second most prevalent neurodegenerative disease worldwide, with up to 70% of patients exhibiting freezing of gait (FOG). FOG is defined as transient episodes when one is unable to effectively engage in the stepping process (despite the intention to walk), which decreases or completely ceases forward movement. Although several FOG triggers have been identified, eliciting FOG remains challenging in research, hindering progress in research and therapy. Virtual reality (VR) offers a promising approach to evoke FOG during overground walking by combining environmental and neuropsychological triggers. This project aims to validate an existing open-source VR-FOG toolbox that integrates multiple triggers. METHODS: A within-subject repeated measures crossover study design with a 1-hour washout period will be used for this project to validate the VR-FOG toolbox. This will consist of three blocks (baseline non-VR, VR non-FOG and VR-FOG). All participants will first complete a baseline walking trial without VR, then be randomised to either the VR non-FOG environment-a virtual replica of the laboratory-or the VR-FOG environment containing multiple virtual FOG triggers. After a 1-hour washout period, they will complete the remaining VR condition. A crossover design will minimise ordering effects of VR conditions on FOG frequency and duration. Twenty participants with Parkinson's disease with FOG will be tested at St. Pölten University of Applied Sciences (Austria) and 20 at the University of Exeter (UK) and will be recruited from local communities. Multisite testing will verify that the VR-FOG environment triggers FOG regardless of testing location. ETHICS AND DISSEMINATION: Ethical approval was obtained from the Lower Austrian Ethics Commission and the University of Exeter review boards. All data will be anonymised, used solely for this project and securely stored in General Data Protection Regulation-compliant repositories. Study results will be presented at scientific conferences and published in peer-reviewed journals.

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