AR Gait Training for Parkinson's Disease

Gait disorder in Parkinson's disease (PD), has been reported to be related to complexenvironments and stress situations. To perform precise evaluation on gait disorder, suchas freezing of gait, is not easy in clinical and/or lab environment, causing thedifficulty to make accurate classification of gait disorder. Designing a standardenvironment stimulation paradigm helps to promote precise classification of gaitdisorders. Monitoring the stress situation that causes gait disorder, and dynamicallymodifying environment assists in the facilitation of effective individualized gaitrehabilitation for PD patients.Although Gentile's taxonomy of tasks provides a structure to examine the complexity ofmovement task in accordance with environmental context, this taxonomy and environmentalcontext does not specifically reflects PD movement problems. In this on‐going project,the investigators developed an environment classification system based on Gentile'staxonomy, but added PD related factors, such as cognitive dual task to meet the needs ofthis population. Our preliminary results showed that this novel classificationsuccessfully induced different levels of gait and HRV responses, suggesting differentstress situations.For the following, the investigators plan to apply the Augment reality (AR) technique toproduce standard interactive testing and training environment. AR allows us to mimiccomplex environments in lab for evaluation and rehabilitation. In addition, AR couldinteractively change the difficulty of environment according to the patients'gait andstress situation which is important for developing effective personal rehabilitationprogramThe purposes for this project are as follows: 1. Test the AR environment stimulation on classifying patients and establish therelationships among challenging AR environment, pressure, and gait 2. Investigate the effects of interactive AR gait training on gait and stress forindividuals with PD.