Real-time modulation of visual feedback on human full-body movements in a virtual mirror: development and proof-of-concept

Background: Virtual reality (VR) provides interactive multimodal sensory stimuli and biofeedback, and can be a powerful tool for physical and cognitive rehabilitation. However, existing systems have generally not implemented realistic full-body avatars and/or a scaling of visual movement feedback. We developed a virtual mirror that displays a realistic full-body avatar that responds to full-body movements in all movement planes in real-time, and that allows for the scaling of visual feedback on movements in real-time. The primary objective of this proof-of-concept study was to assess the ability of healthy subjects to detect scaled feedback on trunk flexion movements. Methods: The virtual mirror was developed by integrating motion capture, virtual reality and projection systems. A protocol was developed to provide both augmented and reduced feedback on trunk flexion movements while sitting and standing. The task required reliance on both visual and proprioceptive feedback. The ability to detect scaled feedback was assessed in healthy subjects (n = 10) using a two-alternative forced choice paradigm. Additionally, immersion in the VR environment and task adherence (flexion angles, velocity, and fluency) were assessed. Results: The ability to detect scaled feedback could be modelled using a sigmoid curve with a high goodness of fit (R-2 range 89-98%). The point of subjective equivalence was not significantly different from 0 (i.e. not shifted), indicating an unbiased perception. The just noticeable difference was 0.035 +/- 0.007, indicating that subjects were able to discriminate different scaling levels consistently. VR immersion was reported to be good, despite some perceived delays between movements and VR projections. Movement kinematic analysis confirmed task adherence. Conclusions: The new virtual mirror extends existing VR systems for motor and pain rehabilitation by enabling the use of realistic full-body avatars and scaled feedback. Proof-of-concept was demonstrated for the assessment of body perception during active movement in healthy controls. The next step will be to apply this system to assessment of body perception disturbances in patients with chronic pain.