Purpose:
Wearable lower-limb robotic exoskeletons have developed rapidly in recent years for the gait rehabilitation and ambulatory assistance of people with spinal cord injury (SCI). However, the learning process to use an exoskeleton is lengthy and tedious as it requires the learning of sequential sub-tasks to trigger steps, e.g., shifting the weight between legs and hip thrust. Timely, the emergence of exoskeletons has coincided with the commercialization of low-cost head-mounted displays (HMDs) that make immersive virtual reality (IVR) a viable rehabilitation tool. HMDs could be a valuable tool to promote the learning of using exoskeletons. However, it is still an open question how immersive virtual environments should be designed to enhance the learning of this especially complex motor task.
Methods:
In this study, we developed an HMD-IVR-based system for training to control wearable lower-limb exoskeletons. The system simulates a virtual walking task of an avatar resembling the sub-tasks needed to trigger steps with an exoskeleton. We ran an experiment with forty healthy participants to investigate the effects of first- (1PP) vs. third-person perspective (3PP) and the provision (or not) of concurrent visual feedback of participants' movements on the walking performance -- namely distance walked, trunk inclination, and stride length --, as well as the effects on embodiment, usability, cybersickness, and perceived workload.
Results:
We found that all participants learned to execute the walking task. However, no clear combination of perspective and visual feedback improved the learning of all sub-tasks concurrently. Instead, the key seems to lie in selecting the appropriate perspective and visual feedback for each sub-task. In particular, the 1PP improved the stride length while training with concurrent visual feedback did not enhance learning overall. Notably, participants embodied the avatar across all training modalities with low cybersickness levels. Still, participants' cognitive load remained high, leading to marginally acceptable usability scores.
Conclusion:
Our findings suggest that to maximize learning, patients should train sub-tasks sequentially using the most suitable combination of person's perspective and visual feedback for each sub-task. This research offers valuable insights for future developments in IVR to support individuals with SCI in improving the learning of walking with wearable exoskeletons.