The effects of augmented and virtual reality gait training on balance and gait in patients with Parkinson’s disease

Autor: Kubilay Gulcan, Arzu Guclu-Gunduz, Evren Yasar, Ulas Ar, Yesim Sucullu Karadag, Fettah Saygili
Rok vydání: 2022
Předmět:
Zdroj: Acta Neurologica Belgica.
ISSN: 2240-2993
0300-9009
DOI: 10.1007/s13760-022-02147-0
Popis: Augmented reality (AR) and virtual reality (VR) facilitate motor learning by enabling the practice of task-specific activities in a rich environment. Therefore, AR and VR gait training may improve balance and gait in Parkinson's Disease (PD).Thirty patients with PD were randomly divided into study (n = 15) and control (n = 15) groups. The study group was given AR and VR gait training combined with conventional training. The control group was given conventional training only. The training was applied to both groups 3 days a week for 6 weeks. Motor symptoms with the Unified Parkinson Disease Rating Scale-Motor Examination (UPDRS-III), balance with posturography and Berg Balance Scale (BBS), perceived balance confidence with Activity-Specific Balance Confidence Scale (ABC), gait with spatio-temporal gait analysis, and functional mobility with Timed Up and Go Test (TUG) were assessed.At the end of the study; UPDRS-III, posturography measurements, BBS, ABC, spatio-temporal gait parameters, and TUG improved in the study group (p 0.05), while BBS, ABC, and only spatial gait parameters (except for step width) improved in the control group (p 0.05). There was no change in posturography measurement, temporal gait parameters, and TUG in control group (p 0.05). When the developed parameters in both groups were compared, the amount of improvement in BBS and ABC was found similar (p 0.05), while the improvement in the other parameters was found higher in the study group (p 0.05).It was concluded that AR and VR gait training provides the opportunity to practice walking with different tasks in increasingly difficult environments, thus improving balance and walking by facilitating motor learning.
Databáze: OpenAIRE
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