AR Gait Training for Parkinson's Disease
Recruiting now · Not applicable
Conditions studied: PD - Parkinson's Disease
In brief
Gait disorders in Parkinson's disease (PD), particularly in complex environments or under stress, present challenges for accurate evaluation and classification, such as in cases of freezing of gait. Traditional clinical and laboratory settings often fail to replicate the complexity needed for precise classification, making effective rehabilitation difficult. This study aims to address these challenges by developing an augmented reality (AR)-based environment that mimics real-world stressors and dynamically adapts to the patient's condition. The AR system is designed to facilitate individualized gait training and rehabilitation by modifying environmental difficulty based on real-time feedback from gait performance and stress levels. Building on Gentile's taxonomy of tasks, the investigators have incorporated PD-specific factors, such as cognitive dual tasks, into our environment classification system. Preliminary results suggest that this system effectively elicits varying gait and heart rate variability (HRV) responses, indicating different stress levels. This trial will further test the AR environment's ability to classify patients based on their responses to complex, interactive environments, while also investigating the effects of adaptive AR-based gait training on both gait and stress management in individuals with PD.
Key facts
- Study ID
- NCT06598878
- Run by
- Chang Gung University
- People needed
- 60
- Starts
- 2024-10-04
- Expected to finish
- 2026-07-01
- Last updated by the study team
- 2024-10-08
Who can join
Age: 20 and older. Sex: any. Healthy volunteers: not accepted.
You may qualify if…
- Clinical diagnosis of Parkinson disease.
You may not qualify if…
- Musculoskeletal injuries on legs
- Osteoporosis.
- Any peripheral or central nervous system injury or disease patients.
Where it is running
- Chang Gung University — Taoyuan, Taiwan (enrolling)
Full record on ClinicalTrials.gov
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