新型物理疗法杂志

抽象的

Closed-Loop VR-Based Interaction to Improve Walking in Parkinson's Disease

Raymond Chong, Kyoung-Hyun Lee, John Morgan, Shyamal Mehta, Jake Griffin, Jason Marchant, Nathan Searle, Joey Sims and Kapil Sethi

Visual cueing have been reported to help improve walking in people with Parkinson’s disease. However, many of these studies incorporate instructions and familiarization/practice, making it unclear whether the visual cues themselves were really effective or what parameters of walking are mutable. Here we used a closed-loop virtual visual cueing system to probe the automatic locomotor structures in subjects with idiopathic Parkinson’s disease and no freezing episodes. The cues moved in synchrony to the velocity of each subject’s walking but in the opposite direction, thereby giving rise to the perception of walking across a stationary landscape. In the absence of explicit instructions and practice, the virtual visual cues induced spontaneous changes among various walking kinematics in moderate-severe but not early-stage subjects. The largest effect was seen in the decrease in time to execute the first step (step initiation). Subjects completed the first step faster in the presence of the visual cues. Step length and walking speed on the other hand, decreased with exposure to the cues, i.e. subjects started out fast but then slowed down in the remainder of the walk. We conclude that the novel effects of the closed-loop visual cues produce mixed outcomes in walking performance. While step initiation improved spontaneously, the normalization of speed and step length would require cognitive strategies and practice as indicated in previous studie