A large proportion of stroke survivors suffer from sensory loss, negatively impacting their independence, quality of life, and neurorehabilitation prognosis. Despite the high prevalence of somatosensory impairments, our understanding of somatosensory interventions such as sensory electrical stimulation (SES) in neurorehabilitation is limited. We aimed to study the effectiveness of SES combined with a sensory discrimination task in a well-controlled virtual environment in healthy participants, setting a foundation for its potential application in stroke rehabilitation. We employed electroencephalography (EEG) to gain a better understanding of the underlying neural mechanisms and dynamics associated with sensory training and SES. We conducted a single-session experiment with 26 healthy participants who explored a set of three visually identical virtual textures—haptically rendered by a robotic device and that differed in their spatial period—while physically guided by the robot to identify the odd texture. The experiment consisted of three phases: pre-intervention, intervention, and post-intervention. Half the participants received subthreshold whole-hand SES during the intervention, while the other half received sham stimulation. We evaluated changes in task performance—assessed by the probability of correct responses—before and after intervention and between groups. We also evaluated differences in the exploration behavior, e.g., scanning speed. EEG was employed to examine the effects of the intervention on brain activity, particularly in the alpha frequency band (8–13 Hz) associated with sensory processing. We found that participants in the SES group improved their task performance after intervention and their scanning speed during and after intervention, while the sham group did not improve their task performance. However, the differences in task performance improvements between groups only approached significance. Furthermore, we found that alpha power was sensitive to the effects of SES; participants in the stimulation group exhibited enhanced brain signals associated with improved touch sensitivity likely due to the effects of SES on the central nervous system, while the increase in alpha power for the sham group was less pronounced. Our findings suggest that SES enhances texture discrimination after training and has a positive effect on sensory-related brain areas. Further research involving brain-injured patients is needed to confirm the potential benefit of our solution in neurorehabilitation.

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To offer engaging neurorehabilitation training to neurologic patients, motor tasks are often visualized in virtual reality (VR). Recently introduced head-mounted displays (HMDs) allow to realistically mimic the body of the user from a first-person perspective (i.e., avatar) in a highly immersive VR environment. In this immersive environment, users may embody avatars with different body characteristics. Importantly, body characteristics impact how people perform actions. Therefore, alternating body perceptions using immersive VR may be a powerful tool to promote motor activity in neurologic patients. However, the ability of the brain to adapt motor commands based on a perceived modified reality has not yet been fully explored. To fill this gap, we “tricked the brain” using immersive VR and investigated if multisensory feedback modulating the physical properties of an embodied avatar influences motor brain networks and control. Ten healthy participants were immersed in a virtual environment using an HMD, where they saw an avatar from first-person perspective. We slowly transformed the surface of the avatar (i.e., the “skin material”) from human to stone. We enforced this visual change by repetitively touching the real arm of the participant and the arm of the avatar with a (virtual) hammer, while progressively replacing the sound of the hammer against skin with stone hitting sound via loudspeaker. We applied single-pulse transcranial magnetic simulation (TMS) to evaluate changes in motor cortical excitability associated with the illusion. Further, to investigate if the “stone illusion” affected motor control, participants performed a reaching task with the human and stone avatar. Questionnaires assessed the subjectively reported strength of embodiment and illusion. Our results show that participants experienced the “stone arm illusion.” Particularly, they rated their arm as heavier, colder, stiffer, and more insensitive when immersed with the stone than human avatar, without the illusion affecting their experienced feeling of body ownership. Further, the reported illusion strength was associated with enhanced motor cortical excitability and faster movement initiations, indicating that participants may have physically mirrored and compensated for the embodied body characteristics of the stone avatar. Together, immersive VR has the potential to influence motor brain networks by subtly modifying the perception of reality, opening new perspectives for the motor recovery of patients.

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BACKGROUND: Current robot-aided training allows for high-intensity training but might hamper the transfer of learned skills to real daily tasks. Many of these tasks, e.g., carrying a cup of coffee, require manipulating objects with complex dynamics. Thus, the absence of somatosensory information regarding the interaction with virtual objects during robot-aided training might be limiting the potential benefits of robotic training on motor (re)learning. We hypothesize that providing somatosensory information through the haptic rendering of virtual environments might enhance motor learning and skill transfer. Furthermore, the inclusion of haptic rendering might increase the task realism, enhancing participants' agency and motivation. Providing arm weight support during training might also enhance learning by limiting participants' fatigue. METHODS: We conducted a study with 40 healthy participants to evaluate how haptic rendering and arm weight support affect motor learning and skill transfer of a dynamic task. The task consisted of inverting a virtual pendulum whose dynamics were haptically rendered on an exoskeleton robot designed for upper limb neurorehabilitation. Participants trained with or without haptic rendering and with or without weight support. Participants' task performance, movement strategy, effort, motivation, and agency were evaluated during baseline, short- and long-term retention. We also evaluated if the skills acquired during training transferred to a similar task with a shorter pendulum. RESULTS: We found that haptic rendering significantly increases participants' movement variability during training and the ability to synchronize their movements with the pendulum, which is correlated with better performance. Weight support also enhances participants' movement variability during training and reduces participants' physical effort. Importantly, we found that training with haptic rendering enhances motor learning and skill transfer, while training with weight support hampers learning compared to training without weight support. We did not observe any significant differences between training modalities regarding agency and motivation during training and retention tests. CONCLUSION: Haptic rendering is a promising tool to boost robot-aided motor learning and skill transfer to tasks with similar dynamics. However, further work is needed to find how to simultaneously provide robotic assistance and haptic rendering without hampering motor learning, especially in brain-injured patients. Trial registration https://clinicaltrials.gov/show/NCT04759976.

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Developing motor and cognitive skills is needed to achieve expert (motor) performance or functional recovery from a neurological condition, e.g., after stroke. While extensive practice plays an essential role in the acquisition of good motor performance, it is still unknown whether certain person-specific traits may predetermine the rate of motor learning. In particular, learners’ functional brain organisation might play an important role in appropriately performing motor tasks. In this paper, we aimed to study how two critical cognitive brain networks—the Attention Network (AN) and the Default Mode Network (DMN)—affect the posterior motor performance in a complex visuomotor task: virtual surfing. We hypothesised that the preactivation of the AN would affect how participants divert their attention towards external stimuli, resulting in robust motor performance. Conversely, the excessive involvement of the DMN—linked to internally diverted attention and mind-wandering—would be detrimental for posterior motor performance. We extracted seven widely accepted microstates—representing participants mind states at rest—out of the Electroencephalography (EEG) resting-state recordings of 36 healthy volunteers, prior to execution of the virtual surfing task. By correlating neural biomarkers (microstates) and motor behavioural metrics, we confirmed that the preactivation of the posterior DMN was correlated with poor posterior performance in the motor task. However, we only found a non-significant association between AN preactivation and the posterior motor performance. In this EEG study, we propose the preactivation of the posterior DMN—imaged using EEG microstates—as a neural trait related to poor posterior motor performance. Our findings suggest that the role of the executive control system is to preserve an homeostasis between the AN and the DMN. Therefore, neurofeedback-based downregulation of DMN preactivation could help optimise motor training.

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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.**

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Combining immersive virtual reality (VR) using head-mounted displays (HMDs) with assisting robotic devices might be a promising procedure to enhance neurorehabilitation. However, it is still an open question how immersive virtual environments (VE) should be designed when interacting with rehabilitation robots. In conventional training, the robot is usually not visually represented in the VE, resulting in a visuo-haptic sensory conflict between what users see and feel. This study aimed to investigate how motivation, embodiment, and presence are affected by this visuo-haptic sensory conflict. Using an HMD and a rehabilitation robot, 28 healthy participants performed a path-tracing task, while the robot was either visually reproduced in the VE or not and while the robot either assisted the movements or not. Participants’ performance and visual attention were measured during the tasks, and after each visibility/assistance condition, they reported their motivation, presence, and embodiment with questionnaires. We found that, independently of the assistance, the robot visibility did not affect participants’ motivation, presence, embodiment, nor task performance. We only found a greater effort/importance reported when the robot was visible. The visual attention was also slightly affected by the robot’s visibility. Importantly, we found that the robotic assistance hampered presence and embodiment, but improved motivation. Our results indicate no disadvantage of not reproducing robotic devices in VEs when using HMDs. However, caution must be put when developing assisting controllers, as they might hamper users’ affect.

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Motor learning is a complex cognitive and motor process underlying neurorehabilitation. Cognitive (e.g., attentional) engagement is important for motor learning, especially early in the learning process. In this study, we investigated if task instructions enforcing the underlying task rule of a virtual sailing task modulate attentional engagement and motor learning. Our results suggest that enforcing the rule of a motor task using explicit knowledge or visual cues enhances motor learning compared with no enforcement of task rules. Further, training with visual cues may support early visuo-attentional engagement.@en

Virtual reality (VR) is a promising tool to promote motor (re)learning in healthy users and brain-injured patients. However, in current VR-based motor training, movements of the users performed in a three-dimensional space are usually visualized on computer screens, televisions, or projection systems, which lack depth cues (2D screen), and thus, display information using only monocular depth cues. The reduced depth cues and the visuospatial transformation from the movements performed in a three-dimensional space to their two-dimensional indirect visualization on the 2D screen may add cognitive load, reducing VR usability, especially in users suffering from cognitive impairments. These 2D screens might further reduce the learning outcomes if they limit users’ motivation and embodiment, factors previously associated with better motor performance. The goal of this study was to evaluate the potential benefits of more immersive technologies using head-mounted displays (HMDs). As a first step towards potential clinical implementation, we ran an experiment with 20 healthy participants who simultaneously performed a 3D motor reaching and a cognitive counting task using: (1) (immersive) VR (IVR) HMD, (2) augmented reality (AR) HMD, and (3) computer screen (2D screen). In a previous analysis, we reported improved movement quality when movements were visualized with IVR than with a 2D screen. Here, we present results from the analysis of questionnaires to evaluate whether the visualization technology impacted users’ cognitive load, motivation, technology usability, and embodiment. Reports on cognitive load did not differ across visualization technologies. However, IVR was more motivating and usable than AR and the 2D screen. Both IVR and AR rea ched higher embodiment level than the 2D screen. Our results support our previous finding that IVR HMDs seem to be more suitable than the common 2D screens employed in VR-based therapy when training 3D movements. For AR, it is still unknown whether the absence of benefit over the 2D screen is due to the visualization technology per se or to technical limitations specific to the device.

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Learning a new motor task is a complex cognitive and motor process. Especially early during motor learning, cognitive functions such as attentional engagement, are essential, e.g., to discover relevant visual stimuli. Drawing participant’s attention towards task-relevant stimuli—e.g., with task instructions using visual cues or explicit written information—is a common practice to support cognitive engagement during training and, hence, accelerate motor learning. However, there is little scientific evidence about how visually cued or written task instructions affect attentional brain networks during motor learning. In this experiment, we trained 36 healthy participants in a virtual motor task: surfing waves by steering a boat with a joystick. We measured the participants’ motor performance and observed attentional brain networks using alpha-band electroencephalographic (EEG) activity before and after training. Participants received one of the following task instructions during training: (1) No explicit task instructions and letting participants surf freely (implicit training; IMP); (2) Task instructions provided through explicit visual cues (explicit-implicit training; E-IMP); or (3) through explicit written commands (explicit training; E). We found that providing task instructions during training (E and E-IMP) resulted in less post-training motor variability—linked to enhanced performance—compared to training without instructions (IMP). After training, participants trained with visual cues (E-IMP) enhanced the alpha-band strength over parieto-occipital and frontal brain areas at wave onset. In contrast, participants who trained with explicit commands (E) showed decreased fronto-temporal alpha activity. Thus, providing task instructions in written (E) or using visual cues (E-IMP) leads to similar motor performance improvements by enhancing activation on different attentional networks. While training with visual cues (E-IMP) may be associated with visuo-attentional processes, verbal-analytical processes may be more prominent when written explicit commands are provided (E). Together, we suggest that training parameters such as task instructions, modulate the attentional networks observed during motor practice and may support participant’s cognitive engagement, compared to training without instructions.

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Despite recent advances in robot-assisted training, the benefits of haptic guidance on motor (re)learning are still limited. While haptic guidance may increase task performance during training, it may also decrease participants' effort and interfere with the perception of the environment dynamics, hindering somatosensory information crucial for motor learning. Importantly, haptic guidance limits motor variability, a factor considered essential for learning. We propose that Model Predictive Controllers (MPC) might be good alternatives to haptic guidance since they minimize the assisting forces and promote motor variability during training. We conducted a study with 40 healthy participants to investigate the effectiveness of MPCs on learning a dynamic task. The task consisted of swinging a virtual pendulum to hit incoming targets with the pendulum ball. The environment was haptically rendered using a Delta robot. We designed two MPCs: the first MPC—end-effector MPC—applied the optimal assisting forces on the end-effector. A second MPC—ball MPC—applied its forces on the virtual pendulum ball to further reduce the assisting forces. The participants' performance during training and learning at short- and long-term retention tests were compared to a control group who trained without assistance, and a group that trained with conventional haptic guidance. We hypothesized that the end-effector MPC would promote motor variability and minimize the assisting forces during training, and thus, promote learning. Moreover, we hypothesized that the ball MPC would enhance the performance and motivation during training but limit the motor variability and sense of agency (i.e., the feeling of having control over their movements), and therefore, limit learning. We found that the MPCs reduce the assisting forces compared to haptic guidance. Training with the end-effector MPC increases the movement variability and does not hinder the pendulum swing variability during training, ultimately enhancing the learning of the task dynamics compared to the other groups. Finally, we observed that increases in the sense of agency seemed to be associated with learning when training with the end-effector MPC. In conclusion, training with MPCs enhances motor learning of tasks with complex dynamics and are promising strategies to improve robotic training outcomes in neurological patients.

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In immersive virtual reality, the own body is often visually represented by an avatar. This may induce a feeling of body ownership over the virtual limbs. Importantly, body ownership and the motor system share neural correlates. Yet, evidence on the functionality of this neuroanatomical coupling is still inconclusive. Findings from previous studies may be confounded by the congruent vs. incongruent multisensory stimulation used to modulate body ownership. This study aimed to investigate the effect of body ownership and congruency of information on motor performance in immersive virtual reality. We aimed to modulate body ownership by providing congruent vs. incongruent visuo-tactile stimulation (i.e., participants felt a brush stroking their real fingers while seeing a virtual brush stroking the same vs. different virtual fingers). To control for congruency effects, unimodal stimulation conditions (i.e., only visual or tactile) with hypothesized low body ownership were included. Fifty healthy participants performed a decision-making (pressing a button as fast as possible) and a motor task (following a defined path). Body ownership was assessed subjectively with established questionnaires and objectively with galvanic skin response (GSR) when exposed to a virtual threat. Our results suggest that congruency of information may decrease reaction times and completion time of motor tasks in immersive virtual reality. Moreover, subjective body ownership is associated with faster reaction times, whereas its benefit on motor task performance needs further investigation. Therefore, it might be beneficial to provide congruent information in immersive virtual environments, especially during the training of motor tasks, e.g., in neurorehabilitation interventions.@en

Sensory loss in patients with neurological injuries is associated with poor neurorehabilitation training outcomes. However, in robotic neurorehabilitation, sensory interventions receive systematically less attention than motor training. To boost the potential of robotic rehabilitation, we are evaluating the feasibility of employing a haptic robotic device for the assessment and training of touch sensibility. Here, we present preliminary results on the test-retest reliability from 20 healthy participants. Participants performed a sensory discrimination task, where different surfaces were rendered by the haptic device, while they were passively moved by the robot and when they actively explored the surfaces. Participants' performance from two consecutive days was compared and no significant differences were found, neither for active nor passive exploration. However, the active condition had poor reliability, while the passive condition had moderate reliability, suggesting that sensory assessment may benefit from robotic guidance to achieve a more repeatable tactile evaluation.

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