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Feasibility of Real-Time Visual Feedback in Augmented Reality to Reduce Gait Asymmetry Post-Stroke

StatusNot Yet Recruiting
PhaseNot applicable
Started
View on ClinicalTrials.gov ↗
Trial flagged as At Risk
Primary completion moved at least 10 months later Sep 15, 2026 → Jul 15, 2027
See other at-risk trials from McGill University

Record History

  1. Notable Primary completion pushed from Sep 15, 2026 to Jul 15, 2027 Start date: Apr 15, 2026 to Jan 15, 2027 · Eligibility criteria expanded, about 8 words · Secondary endpoints: details revised at 6 of 11 entries Show 3 more changesShow less
    • Start date: Apr 15, 2026 to Jan 15, 2027
    • Eligibility criteria expanded, about 8 words
    • Secondary endpoints: details revised at 6 of 11 entries
  2. Notable Start date: Sep 15, 2025 to Apr 15, 2026v3
  3. Minor Re-verified, no change to tracked fieldsv2
  4. Minor Study First Submitted
  • Stopped: an ongoing trial was terminated, suspended or withdrawn.
  • Notable: the trial’s plan changed such as a big move in its timeline or size, a new primary endpoint, sponsor or phase, or recruiting opened or resumed.
  • Minor: routine progress and housekeeping, such as sites added or enrollment closed.
3,289 trials monitored
See 141 trials at risk
Unilateral motor deficits, such as paresis and tone disorders, are frequent consequences of stroke and lead to gait impairments. Among these, spatial asymmetry is characterized by differences in step length between the paretic and non-paretic limbs, resulting in balance problems and an increased risk of falls. Conventional rehabilitation has shown limited effectiveness in addressing this issue, highlighting the need for innovative approaches. Real-time feedback interventions, particularly through augmented reality (AR), may help improve gait asymmetry by providing a more natural and interactive learning environment. This study aims to compare the effectiveness of two types of real-time visual feedback, an avatar-based system and visual bars, in improving gait symmetry and other locomotor parameters in individuals post-stroke. It will also assess the acceptability and usability of the intervention, participants' sense of presence, and the potential for cybersickness induced by these systems. A repeated-measures design will be used to evaluate the immediate effectiveness of the two types of visual feedback on gait asymmetry and other locomotor parameters in adults in the subacute phase after stroke. Participants, aged 18 to 65 and presenting spatial asymmetry, will perform walking trials in an AR environment while being exposed to both feedback modalities in randomized order. Spatiotemporal and kinematic data will be collected using inertial sensors, while questionnaires will assess acceptability, usability, sense of presence, and cybersickness. Participants will be evaluated in a 45-m long corridor (free of traffic) and will perform nine walking trials (three per condition) under three randomized conditions: (1) a lateral view avatar displayed on the paretic side, previously shown to provide optimal feedback on step length; (2) a visual bar feedback representing bilateral step lengths; and (3) a "control" condition with no additional feedback. Each walking trial, lasting 2.5 minutes, will consist of a pre-adaptation phase without feedback (30 s), followed by an adaptation phase with feedback (1 min), and a post-adaptation phase without feedback (1 min). The investigators expect that avatar-based feedback will be more effective than visual bars in improving spatial symmetry. The investigators also anticipate that both feedback modalities will be well accepted and usable by participants without inducing cybersickness, but that the sense of presence will be higher with avatar-based feedback. This study will shed light on locomotor adjustment mechanisms and may lay the groundwork for future clinical trials. By offering a personalized, evidence-based approach, these results could help transform post-stroke rehabilitation through the integration of innovative tools to optimize functional recovery.
Trial Details
NCT Number NCT07178535
Lead Sponsor McGill University
Conditions Stroke
Enrollment 20 participants
Start Date
Primary Completion (estimated)
Study Completion (estimated)
Updated on ClinicalTrials.gov