🤖 AI Summary
This study addresses the limitation of existing virtual reality (VR) rehabilitation for multiple sclerosis, which predominantly targets gait performance while neglecting cognitive and physical burden. To overcome this, we propose a threshold-anchored efficiency framework that incorporates clinically referenced speed thresholds and multimodal VR feedback. Through Pareto frontier analysis, the framework jointly optimizes gait performance and overall patient workload. The research identifies five non-dominated feedback conditions, demonstrating that spatial auditory feedback effectively closes speed gaps while maintaining low burden levels. By transcending single-metric limitations, this work establishes a novel paradigm for personalized VR rehabilitation that simultaneously balances therapeutic efficacy and patient tolerability.
📝 Abstract
Reduced walking speed in people with multiple sclerosis (MS) is associated with an increased risk of falls. However, virtual reality (VR)-based rehabilitation studies often emphasize performance improvements without considering the cognitive and physical effort required to achieve them. This study introduces a threshold-anchored efficiency framework that jointly evaluates gait performance and overall effort. A normative walking-velocity target of \(T=1.29\) m/s was derived from the mean walking speed of non-fallers in an independent MS gait dataset and used as a clinically motivated reference point. Thirty-four adults with MS were evaluated across eight VR feedback conditions spanning unimodal, bimodal, and multimodal feedback. For each condition, we quantified the proportion of the velocity gap to the target that was closed and the associated cognitive and physical burden. Pareto efficiency analysis identified five non-dominated conditions: Static Visual, Spatial Auditory, Auditory+Visual, Auditory+Vibrotactile, and Multimodal, whereas Spatial Vibrotactile and Vibrotactile+Visual were dominated. Spatial Auditory showed a favorable performance-effort trade-off, closing 72.7% of the velocity gap while maintaining below-average burden. Multimodal feedback achieved the greatest gap closure (95.6%) but also imposed the highest burden. These findings demonstrate that greater gait improvement does not necessarily correspond to greater rehabilitation efficiency and provide a quantitative framework for comparing VR feedback strategies according to both performance gains and participant burden.