Hiding Assistive Robots During Training in Immersive VR Does not Affect Users' Motivation, Presence, Embodiment, Performance, nor Visual Attention

Development and Validation of a Kinematically Accurate Upper-Limb Exoskeleton Digital Twin for Stroke Rehabilitation

Rehabilitation robotics combined with virtual reality using head-mounted displays enable naturalistic, immersive, and motivating therapy for people after stroke. There is growing interest in employing digital twins in robotic neurore-habilitation, e.g., in telerehabilitation for virtual coaching and monitoring, as well as in immersive virtual reality applications. However, the kinematic matching of the robot's visualization with the real robot movements is hardly validated, potentially affecting the users' experience while immersed in the virtual environment due to a visual-proprioceptive mismatch. The kinematic mismatch may also limit the validity of assessment measures recorded with the digital twin. We present the development and low-cost kinematic validation of a digital twin of a seven active degrees-of-freedom exoskeleton for stroke rehabilitation. We validated the kinematic accuracy of the digital twin end-effector by performing two tasks-a planar reaching task and a 3D functional task-performed by a single healthy participant. We computed the end-effector position and rotation from the forward kinematics of the robot, the digital twin, and data recorded from the real robot using a low-cost tracking system based on HTC VIVE trackers and compared them pair-wise. We found that the digital twin closely matches the forward kinematics and tracked movement of the real robot and thus provides a reliable platform for future research on digital twins for stroke rehabilitation.

Naturalistic visualization of reaching movements using head-mounted displays improves movement quality compared to conventional computer screens and proves high usability

BACKGROUND

The relearning of movements after brain injury can be optimized by providing intensive, meaningful, and motivating training using virtual reality (VR). However, most current solutions use two-dimensional (2D) screens, where patients interact via symbolic representations of their limbs (e.g., a cursor). These 2D screens lack depth cues, potentially deteriorating movement quality and increasing cognitive load. Head-mounted displays (HMDs) have great potential to provide naturalistic movement visualization by incorporating improved depth cues, reduce visuospatial transformations by rendering movements in the space where they are performed, and preserve eye-hand coordination by showing an avatar-with immersive VR (IVR)-or the user's real body-with augmented reality (AR). However, elderly populations might not find these novel technologies usable, hampering potential motor and cognitive benefits.

METHODS

We compared movement quality, cognitive load, motivation, and system usability in twenty elderly participants (>59 years old) while performing a dual motor-cognitive task with different visualization technologies: IVR HMD, AR HMD, and a 2D screen. We evaluated participants' self-reported cognitive load, motivation, and usability using questionnaires. We also conducted a pilot study with five brain-injured patients comparing the visualization technologies while using an assistive device.

RESULTS

Elderly participants performed straighter, shorter duration, and smoother movements when the task was visualized with the HMDs than screen. The IVR HMD led to shorter duration movements than AR. Movement onsets were shorter with IVR than AR, and shorter for both HMDs than the screen, potentially indicating facilitated reaction times due to reduced cognitive load. No differences were found in the questionnaires regarding cognitive load, motivation, or usability between technologies in elderly participants. Both HMDs proved high usability in our small sample of patients.

CONCLUSIONS

HMDs are a promising technology to be incorporated into neurorehabilitation, as their more naturalistic movement visualization improves movement quality compared to conventional screens. HMDs demonstrate high usability, without decreasing participants' motivation, and might potentially lower cognitive load. Our preliminary clinical results suggest that brain-injured patients may especially benefit from more immersive technologies. However, larger patient samples are needed to draw stronger conclusions.*.

Enhancing touch sensibility by sensory retraining in a sensory discrimination task via haptic rendering

Stroke survivors are commonly affected by somatosensory impairment, hampering their ability to interpret somatosensory information. Somatosensory information has been shown to critically support movement execution in healthy individuals and stroke survivors. Despite the detrimental effect of somatosensory impairments on performing activities of daily living, somatosensory training—in stark contrast to motor training—does not represent standard care in neurorehabilitation. Reasons for the neglected somatosensory treatment are the lack of high-quality research demonstrating the benefits of somatosensory interventions on stroke recovery, the unavailability of reliable quantitative assessments of sensorimotor deficits, and the labor-intensive nature of somatosensory training that relies on therapists guiding the hands of patients with motor impairments. To address this clinical need, we developed a virtual reality-based robotic texture discrimination task to assess and train touch sensibility. Our system incorporates the possibility to robotically guide the participants' hands during texture exploration (i.e., passive touch) and no-guided free texture exploration (i.e., active touch). We ran a 3-day experiment with thirty-six healthy participants who were asked to discriminate the odd texture among three visually identical textures –haptically rendered with the robotic device– following the method of constant stimuli. All participants trained with the passive and active conditions in randomized order on different days. We investigated the reliability of our system using the Intraclass Correlation Coefficient (ICC). We also evaluated the enhancement of participants' touch sensibility via somatosensory retraining and compared whether this enhancement differed between training with active vs. passive conditions. Our results showed that participants significantly improved their task performance after training. Moreover, we found that training effects were not significantly different between active and passive conditions, yet, passive exploration seemed to increase participants' perceived competence. The reliability of our system ranged from poor (in active condition) to moderate and good (in passive condition), probably due to the dependence of the ICC on the between-subject variability, which in a healthy population is usually small. Together, our virtual reality-based robotic haptic system may be a key asset for evaluating and retraining sensory loss with minimal supervision, especially for brain-injured patients who require guidance to move their hands.