Use of a Novel Mixed Reality Application for over Ground Gait Speed Modulation

Research Objectives To examine gait modulation and variability among individuals using a novel mixed reality (MR) visual feedback application. Design Block randomized cross-over design and case study. Setting Clinical research laboratory. Participants Twelve individuals without known walking impairment and one individual with an incomplete thoracic SCI. Interventions Visual feedback of the participants' gait speed was provided by an application developed for a commercially available MR head-mounted device (HMD). Participants were asked to match their gait speed to a holographic floating ball during three conditions: 85%, 100%, and 115% of their self-selected speed. The ball was green if participants matched the target speed, blue if the gait was too slow, and disappeared if the gait was too fast. Participants completed 21 (participant with SCI) or 30 (other participants) 10-meter trials. Main Outcome Measures Gait speed matching error, and variability in stride length, and stride time. Results Participants met the target speeds with a 6% rate of error (< 0.1 m/s error). Among individuals without walking impairment, error decreased after the first of 30 walking trials using the MR device and was consistent across all target speeds. The individual with SCI exhibited a higher error in their 4th and 6th walking trials, which occurred at the slower speed (85%). Both groups showed more variability in stride length and stride time when using the MR-HMD device. Conclusions Individuals without known walking impairment required minimal practice to successfully adjust walking speed to match a visual target from a MR-HMD. However, individuals with gait impairments may require additional training or have more difficulty at slower speeds than individuals without gait impairment. Further research is needed on the effectiveness of MR visual feedback in clinical populations with gait impairments. Author(s) Disclosures Co-author Randy Trumbower received contracted research support from Onward. Megan Dass completed an internship at Microsoft. The authors have no other conflicts of interest to report.