Abstract:

In response to the requirements for dynamic walking ability assessment, training difficulty adjustment, and safety process monitoring in lower-limb rehabilitation for stroke patients, an embodied immersive virtual reality rehabilitation training and assessment system was constructed. The feasibility of measuring dynamic stability, body representation, and cognitive load was verified in a proof-of-concept study with healthy subjects. The system used an omnidirectional treadmill as the walking platform and employed full-body inertial motion capture to drive a first-person full-body virtual avatar. By combining head-mounted display position and orientation, event logs, and eye-tracking, the system enables the synchronous collection of data on walking kinematics, visual attention, and task behavior. A task library was built around straight walking, turning, obstacle avoidance, and dual-task walking. An index system was designed based on the root-mean-square of centroid acceleration, root-mean-square of acceleration jerk, proprioceptive localization error, pupil change, fixation/saccade characteristics, and dual-task cost. A baseline normalization threshold and hysteresis determination mechanism were introduced to form a prototype-level closed-loop of “state collection-rule determination - task adjustment-event recording”. In the lower-limb visibility experiment (N=27), the transparency of the virtual avatar’s lower limbs had a significant impact on proprioceptive localization error and embodied experience scores. The complete-invisibility condition produced higher localization errors and lower embodiment scores, while there was no significant difference in motion sickness scores. The semi-transparent condition showed a good balance between retaining body contour cues and reducing environmental occlusion. In the dual-task walking experiment (N=29), as the cognitive load increased from low to high, pupil statistics, pupil change, the number of fixations, and number of saccades generally increased, and the average fixation duration shortened, indicating that eye-movement features can reflect the load levels in dynamic walking. High gait difficulty also led to an increase in the root-mean-square of centroid acceleration and the convergence of lateral trunk swing, verifying the effectiveness of gait-difficulty manipulation. This system can integrate motor control, visual body cues, and cognitive load evidence in an immersive dynamic walking scenario, providing a methodological basis for task design, parameter adjustment, and pre-clinical evaluation of stroke rehabilitation training systems. The relevant thresholds and design strategies still need to be further verified in stroke patients.

Key words: immersive virtual reality, omnidirectional treadmill, stroke rehabilitation, inertial motion capture, dynamic stability, proprioceptive localization, dual-task, eye tracking