Ecologically valid virtual reality-based technologies for assessment and rehabilitation of acquired brain injury: a systematic review.

Purpose: A systematic review was conducted to examine the state of the literature regarding using ecologically valid virtual environments and related technologies to assess and rehabilitate people with Acquired Brain Injury (ABI). Materials and methods: A literature search was performed following the PRISMA guidelines using PubMed, Web of Science, ACM and IEEE databases. The focus was on assessment and intervention studies using ecologically valid virtual environments (VE). All studies were included if they involved individuals with ABI and simulated environments of the real world or Activities of Daily Living (ADL). Results: Seventy out of 363 studies were included in this review and grouped and analyzed according to the nature of its simulation, prefacing a total of 12 kitchens, 11 supermarkets, 10 shopping malls, 16 streets, 11 cities, and 10 other everyday life scenarios. These VE were mostly presented on computer screens, HMD's and laptops and patients interacted with them primarily via mouse, keyboard, and joystick. Twenty-five out of 70 studies had a non-experimental design. Conclusion: Evidence about the clinical impact of ecologically valid VE is still modest, and further research with more extensive samples is needed. It is important to standardize neuropsychological and motor outcome measures to strengthen conclusions between studies. Systematic review registration: identifier CRD42022301560, https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=301560.

Brain activation by a VR-based motor imagery and observation task: An fMRI study.

Training motor imagery (MI) and motor observation (MO) tasks is being intensively exploited to promote brain plasticity in the context of post-stroke rehabilitation strategies. This may benefit from the use of closed-loop neurofeedback, embedded in brain-computer interfaces (BCI's) to provide an alternative non-muscular channel, which may be further augmented through embodied feedback delivered through virtual reality (VR). Here, we used functional magnetic resonance imaging (fMRI) in a group of healthy adults to map brain activation elicited by an ecologically-valid task based on a VR-BCI paradigm called NeuRow, whereby participants perform MI of rowing with the left or right arm (i.e., MI), while observing the corresponding movement of the virtual arm of an avatar (i.e., MO), on the same side, in a first-person perspective. We found that this MI-MO task elicited stronger brain activation when compared with a conventional MI-only task based on the Graz BCI paradigm, as well as to an overt motor execution task. It recruited large portions of the parietal and occipital cortices in addition to the somatomotor and premotor cortices, including the mirror neuron system (MNS), associated with action observation, as well as visual areas related with visual attention and motion processing. Overall, our findings suggest that the virtual representation of the arms in an ecologically-valid MI-MO task engage the brain beyond conventional MI tasks, which we propose could be explored for more effective neurorehabilitation protocols.

Design, development, and evaluation of an interactive personalized social robot to monitor and coach post-stroke rehabilitation exercises.

Socially assistive robots are increasingly being explored to improve the engagement of older adults and people with disability in health and well-being-related exercises. However, even if people have various physical conditions, most prior work on social robot exercise coaching systems has utilized generic, predefined feedback. The deployment of these systems still remains a challenge. In this paper, we present our work of iteratively engaging therapists and post-stroke survivors to design, develop, and evaluate a social robot exercise coaching system for personalized rehabilitation. Through interviews with therapists, we designed how this system interacts with the user and then developed an interactive social robot exercise coaching system. This system integrates a neural network model with a rule-based model to automatically monitor and assess patients' rehabilitation exercises and can be tuned with individual patient's data to generate real-time, personalized corrective feedback for improvement. With the dataset of rehabilitation exercises from 15 post-stroke survivors, we demonstrated our system significantly improves its performance to assess patients' exercises while tuning with held-out patient's data. In addition, our real-world evaluation study showed that our system can adapt to new participants and achieved 0.81 average performance to assess their exercises, which is comparable to the experts' agreement level. We further discuss the potential benefits and limitations of our system in practice.

The impact of exergames on the functional balance of a teenager with cerebral palsy - a case report.

PURPOSE: To understand the impact of an intensive rehabilitation program based on exergames in balance and lower limb function in a teenager with cerebral palsy. METHODS: The rehabilitation program comprised different customised exergames and was delivered in 5 weekly sessions of 30 min for 4 weeks. Pre-, post-, and 1-month Follow-up assessments included the following metrics: Berg Balance Scale (BBS), Dynamic Gait Index (DGI), Gross Motor Function Measure (GMFM), Posturography, and Gait analysis. RESULTS: We observed increased scores after the intervention of 9/72 points in GMF - Module E (Walk, Run and Jump) and of 9/56 points in BBS, sustained at Follow-up. Changes in function, specifically in the quality and independence of the performance of specific movements such as turning 360°, increased distance reaching forward, walk behind, step over obstacles, and step stairs up and down were also observed. Gait kinematics and Spatio-temporal parameters tended to get closer to the 50th percentile. CONCLUSIONS: We observed positive changes in motor function of a teenager with cerebral palsy, with sustained increased scores at a 1-month Follow-up. Findings are suggestive that intensive rehabilitation programs using exergames with high customisation features are a potentially valuable rehabilitation tool for training balance in teenagers with Cerebral Palsy.Implications for rehabilitationExergames may be a useful for providing balance training for teenagers who have a mixed form of cerebral palsy.Exergames that require body displacement may be suitable for modulating gait kinematics and spatio-temporal parameters.The customisation of virtual rehabilitation tools seems to impact the motivation and effort of the user positively.

NeuroAIreh@b: an artificial intelligence-based methodology for personalized and adaptive neurorehabilitation.

Cognitive impairments are a prevalent consequence of acquired brain injury, dementia, and age-related cognitive decline, hampering individuals' daily functioning and independence, with significant societal and economic implications. While neurorehabilitation represents a promising avenue for addressing these deficits, traditional rehabilitation approaches face notable limitations. First, they lack adaptability, offering one-size-fits-all solutions that may not effectively meet each patient's unique needs. Furthermore, the resource-intensive nature of these interventions, often confined to clinical settings, poses barriers to widespread, cost-effective, and sustained implementation, resulting in suboptimal outcomes in terms of intervention adaptability, intensity, and duration. In response to these challenges, this paper introduces NeuroAIreh@b, an innovative cognitive profiling and training methodology that uses an AI-driven framework to optimize neurorehabilitation prescription. NeuroAIreh@b effectively bridges the gap between neuropsychological assessment and computational modeling, thereby affording highly personalized and adaptive neurorehabilitation sessions. This approach also leverages virtual reality-based simulations of daily living activities to enhance ecological validity and efficacy. The feasibility of NeuroAIreh@b has already been demonstrated through a clinical study with stroke patients employing a tablet-based intervention. The NeuroAIreh@b methodology holds the potential for efficacy studies in large randomized controlled trials in the future.

Feasibility, Acceptability, and Preliminary Impact of Full-Body Interaction on Computerized Cognitive Training Based on Instrumental Activities of Daily Living: A Pilot Randomized Controlled Trial with Chronic Psychiatric Inpatients.

Objective: To conduct a pilot randomized control trial to assess the feasibility and acceptability of full-body interaction cognitive training (FBI-CT) inspired by instrumental activities of daily living in chronic psychiatric inpatients and to explore its preliminary impact on cognitive and noncognitive outcomes. Materials and Methods: Twenty psychiatric inpatients met the inclusion criteria and were randomly allocated to the FBI-CT group (n = 10) or the tablet-based CT group (T-CT) (n = 10). Neuropsychological assessments were performed at baseline, postintervention, and 3-month follow-up. Results: Both groups presented high completion rates at postintervention and follow-up. Participants reported high satisfaction following the interventions, with the FBI-CT group exhibiting slightly higher satisfaction. A within-group analysis showed significant improvements in the FBI-CT group for processing speed and sustained attention for short periods (P = 0.012), verbal memory (P = 0.008), semantic fluency (P = 0.027), depressive symptoms (P = 0.008), and quality of life (P = 0.008) at postintervention. At 3-month follow-up, this group maintained verbal memory improvements (P = 0.047) and depressive symptoms amelioration (P = 0.026). The T-CT group revealed significant improvements in sustained attention for long periods (P = 0.020), verbal memory (P = 0.014), and executive functions (P = 0.047) postintervention. A between-group analysis demonstrated that the FBI-CT group exhibited greater improvements in depressive symptoms (P = 0.042). Conclusions: Overall, we found support for the feasibility and acceptability of both training approaches. Our findings show promise regarding the preliminary impact of the FBI-CT intervention, but due to study limitations such as the small sample size, we cannot conclude that FBI-CT is a more effective approach than T-CT for enhancing cognitive and noncognitive outcomes of chronic psychiatric inpatients. Clinical trials (number: NCT05100849).

Automatic Cognitive Fatigue Detection Using Wearable fNIRS and Machine Learning.

Wearable sensors have increasingly been applied in healthcare to generate data and monitor patients unobtrusively. Their application for Brain-Computer Interfaces (BCI) allows for unobtrusively monitoring one's cognitive state over time. A particular state relevant in multiple domains is cognitive fatigue, which may impact performance and attention, among other capabilities. The monitoring of this state will be applied in real learning settings to detect and advise on effective break periods. In this study, two functional near-infrared spectroscopy (fNIRS) wearable devices were employed to build a BCI to automatically detect the state of cognitive fatigue using machine learning algorithms. An experimental procedure was developed to effectively induce cognitive fatigue that included a close-to-real digital lesson and two standard cognitive tasks: Corsi-Block task and a concentration task. Machine learning models were user-tuned to account for the individual dynamics of each participant, reaching classification accuracy scores of around 70.91 ± 13.67 %. We concluded that, although effective for some subjects, the methodology needs to be individually validated before being applied. Moreover, time on task was not a particularly determining factor for classification, i.e., to induce cognitive fatigue. Further research will include other physiological signals and human-computer interaction variables.

Evaluation of a Low-Cost Virtual Reality Surround-Screen Projection System.

Two of the most popular mediums for virtual reality are head-mounted displays and surround-screen projection systems, such as CAVE Automatic Virtual Environments. In recent years, HMDs suffered a significant reduction in cost and have become widespread consumer products. In contrast, CAVEs are still expensive and remain accessible to a limited number of researchers. This study aims to evaluate both objective and subjective characteristics of a CAVE-like monoscopic low-cost virtual reality surround-screen projection system compared to advanced setups and HMDs. For objective results, we measured the head position estimation accuracy and precision of a low-cost active infrared (IR) based tracking system, used in the proposed low-cost CAVE, relatively to an infrared marker-based tracking system, used in a laboratory-grade CAVE system. For subjective characteristics, we investigated the sense of presence and cybersickness elicited in users during a visual search task outside personal space, beyond arms reach, where the importance of stereo vision is diminished. Thirty participants rated their sense of presence and cybersickness after performing the VR search task with our CAVE-like system and a modern HMD. The tracking showed an accuracy error of 1.66 cm and .4 mm of precision jitter. The system was reported to elicit presence but at a lower level than the HMD, while causing significant lower cybersickness. Our results were compared to a previous study performed with a laboratory-grade CAVE and support that a VR system implemented with low-cost devices could be a viable alternative to laboratory-grade CAVEs for visual search tasks outside the user's personal space.

The Benefits of Custom Exergames for Fitness, Balance, and Health-Related Quality of Life: A Randomized Controlled Trial with Community-Dwelling Older Adults.

Objective: This research aimed to measure the benefits in older adults' motor performance and quality of life during a 12-week-long multidimensional training combining custom-made exergames and traditional exercise in a complementary manner, compared with traditional training alone. Materials and Methods: Community-dwelling older adults participated in a randomized controlled trial (N = 31) consisting of two weekly exercise sessions of 60 minutes for 12 weeks. Participants allocated to the exergames group (n = 15) had one individual session of exergames and one traditional exercise group session per week. Control group participants (n = 16) had two weekly traditional exercise group sessions. Outcome measures on fitness, balance, and health-related quality of life were measured at the start of the intervention, 6th, 12th, and 16th week (1-month follow-up). Results: The exergames group showed a significant increase in lower-body and upper-body strength from pre- to postintervention. When compared with control, participants had significantly higher developments of upper-body strength from pre- to postassessments. There was a significant decrease in shoulder range of motion between the end of the intervention and follow-up for participants in both conditions. Balance increased significantly during the intervention but decreased at follow-up in both conditions. The mental component of health-related quality of life was significantly higher at the end compared with the start of the intervention in the exergames group, and this difference was significantly higher when compared with control. Conclusion: Integrating personalized exergames designed for multidimensional fitness training in traditional settings can be an effective strategy to enhance older adults' motor performance and mental well-being.

The use of game modes to promote engagement and social involvement in multi-user serious games: a within-person randomized trial with stroke survivors.

BACKGROUND: Serious games are promising for stroke rehabilitation, with studies showing a positive impact on reducing motor and cognitive deficits. However, most of the evidence is in the context of single-user rehabilitation, and little is known concerning the impact in multi-user settings. This study evaluates the impact that different game modes can have on engagement and social involvement during a two-user game. Specifically, we want to understand the benefits of game modalities based on competition, co-activation, and collaboration and analyze the influence of different motor and cognitive deficits and personality traits. METHODS: We developed a two-player setup-using tangible objects and a large screen interactive table-for upper limb rehabilitation purposes. We implemented a game that, while keeping the same basic mechanics, can be played in the three different modes (Competitive, Co-active, and Collaborative). We ran a within-person randomized study with 21 stroke survivors that were paired and played the game in its three versions. We used the Game Experience Questionnaire-Core Module to assess engagement and the Social Presence Module to assess Social Involvement. For personality, motor, and cognitive function, users answered the International Personality Item Pool (short version), Fugl-Meyer Assessment-Upper Extremity, Modified Ashworth Scale, and Montreal Cognitive Assessment, respectively. RESULTS: The Collaborative mode promoted significantly more Behavioral Involvement. The Competitive mode promoted more Flow and Challenge than the Co-active mode with participants with better cognitive performance, with low extraversion, or with higher motor skills. Participants with higher cognitive deficits reported more Competence with the Co-active mode. CONCLUSIONS: Our results indicate that, for multi-user motor rehabilitation settings, the collaborative mode is the more appropriate gaming approach to promote social involvement, showing a high potential for increasing adherence and effectiveness of therapy. Additionally, we show that a player's motor and cognitive ability and personality should be considered when designing personalized tasks for multiplayer settings.

A comparison of two personalization and adaptive cognitive rehabilitation approaches: a randomized controlled trial with chronic stroke patients.

BACKGROUND: Paper-and-pencil tasks are still widely used for cognitive rehabilitation despite the proliferation of new computer-based methods, like VR-based simulations of ADL's. Studies have established construct validity of VR assessment tools with their paper-and-pencil version by demonstrating significant associations with their traditional construct-driven measures. However, VR rehabilitation intervention tools are mostly developed to include mechanisms such as personalization and adaptation, elements that are disregarded in their paper-and-pencil counterparts, which is a strong limitation of comparison studies. Here we compare the clinical impact of a personalized and adapted paper-and-pencil training and a content equivalent and more ecologically valid VR-based ADL's simulation. METHODS: We have performed a trial with 36 stroke patients comparing Reh@City v2.0 (adaptive cognitive training through everyday tasks VR simulations) with Task Generator (TG: content equivalent and adaptive paper-and-pencil training). The intervention comprised 12 sessions, with a neuropsychological assessment pre, post-intervention and follow-up, having as primary outcomes: general cognitive functioning (assessed by the Montreal Cognitive Assessment - MoCA), attention, memory, executive functions and language specific domains. RESULTS: A within-group analysis revealed that the Reh@City v2.0 improved general cognitive functioning, attention, visuospatial ability and executive functions. These improvements generalized to verbal memory, processing speed and self-perceived cognitive deficits specific assessments. TG only improved in orientation domain on the MoCA, and specific processing speed and verbal memory outcomes. However, at follow-up, processing speed and verbal memory improvements were maintained, and a new one was revealed in language. A between-groups analysis revealed Reh@City v2.0 superiority in general cognitive functioning, visuospatial ability, and executive functions on the MoCA. CONCLUSIONS: The Reh@City v2.0 intervention with higher ecological validity revealed higher effectiveness with improvements in different cognitive domains and self-perceived cognitive deficits in everyday life, and the TG intervention retained fewer cognitive gains for longer. TRIAL REGISTRATION: The trial is registered at ClinicalTrials.gov, number NCT02857803. Registered 5 August 2016, .

Impact of game mode in multi-user serious games for upper limb rehabilitation: a within-person randomized trial on engagement and social involvement.

BACKGROUND: Serious games have been increasingly used for motor rehabilitation. However, it is not well known how different game features can be used to impact specific skills properly. Here, we study how the mode (competitive, co-active, collaborative) in which a multi-user game is presented impacts engagement and social involvement. METHODS: We collected data from 20 pairs of community-dwelling older adults (71.5 ± 8.7 years) in a study following a within-persons design. The participants performed a two-player upper limb rehabilitation game with three conditions (Competitive, Co-active, and Collaborative modes). Engagement and social involvement were assessed through the Core Module and Social Presence Module, respectively, from the Game Experience Questionnaire. To infer the impact of personality and cognitive function, users answered the International Personality Item Pool (short version) and the Montreal Cognitive Assessment, respectively. RESULTS: Results show that the Collaborative game mode promotes more social involvement when compared to Competitive and Co-active modes. This result is mostly explained by those participants with higher cognitive skills, and those that are more extrovert. Extrovert participants feel more empathy and are behaviorally more involved when playing the Collaborative mode. Also, the Collaborative mode is shown to be appropriate to promote interaction with participants that previously had a distant relationship, while the Competitive mode seems to be more beneficial to promote empathy between players with a closer relationship. CONCLUSIONS: The Collaborative game mode elicited significantly higher social involvement in terms of Empathy, Positive Affect, and Behavioral Involvement. Hence, this game mode seems to be the most adequate choice to be used in multiplayer rehabilitation settings, where social interaction is intended.

Lessons Learned from Gamifying Functional Fitness Training Through Human-Centered Design Methods in Older Adults.

Background: The design of meaningful and enjoyable Exergames for fitness training in older adults possesses critical challenges in matching user's needs and motivators with game elements. These challenges are often due to the lack of knowledge of seniors' game preferences and technology literacy as well as a poor involvement of the target population in the design process. Objective: This research aims at describing a detailed and scrutinized use case of applying human-centered design methodologies in the gamification of fitness training routines and illustrates how to incorporate seniors' feedback in the game design pipeline. Materials and Methods: We focus on how to use the insights from human-centered inquiries to improve in-game elements, such as mechanics or esthetics, and how to iterate the game design process based on playtesting sessions in the field. Results: We present a set of four Exergames created to train the critical functional fitness areas of older adults. We show how through rapid prototyping methods and multidisciplinary research, Exergames can be rigorously designed and developed to match individual physical capabilities. Moreover, we propose a set of guidelines for the design of context-aware Exergames based on the lessons learned. Conclusion: We highlight the process followed; it depicts 19 weeks of various activities delivering particular and actionable items that can be used as a checklist for future games for health design projects.

Efficacy and Brain Imaging Correlates of an Immersive Motor Imagery BCI-Driven VR System for Upper Limb Motor Rehabilitation: A Clinical Case Report.

To maximize brain plasticity after stroke, a plethora of rehabilitation strategies have been explored. These include the use of intensive motor training, motor-imagery (MI), and action-observation (AO). Growing evidence of the positive impact of virtual reality (VR) techniques on recovery following stroke has been shown. However, most VR tools are designed to exploit active movement, and hence patients with low level of motor control cannot fully benefit from them. Consequently, the idea of directly training the central nervous system has been promoted by utilizing MI with electroencephalography (EEG)-based brain-computer interfaces (BCIs). To date, detailed information on which VR strategies lead to successful functional recovery is still largely missing and very little is known on how to optimally integrate EEG-based BCIs and VR paradigms for stroke rehabilitation. The purpose of this study was to examine the efficacy of an EEG-based BCI-VR system using a MI paradigm for post-stroke upper limb rehabilitation on functional assessments, and related changes in MI ability and brain imaging. To achieve this, a 60 years old male chronic stroke patient was recruited. The patient underwent a 3-week intervention in a clinical environment, resulting in 10 BCI-VR training sessions. The patient was assessed before and after intervention, as well as on a one-month follow-up, in terms of clinical scales and brain imaging using functional MRI (fMRI). Consistent with prior research, we found important improvements in upper extremity scores (Fugl-Meyer) and identified increases in brain activation measured by fMRI that suggest neuroplastic changes in brain motor networks. This study expands on the current body of evidence, as more data are needed on the effect of this type of interventions not only on functional improvement but also on the effect of the intervention on plasticity through brain imaging.

Toward Emotionally Adaptive Virtual Reality for Mental Health Applications.

Here, we introduce the design and preliminary validation of a general-purpose architecture for affective-driven procedural content generation in virtual reality (VR) applications in mental health and wellbeing. The architecture supports seven commercial physiological sensing technologies and can be deployed in immersive and non-immersive VR systems. To demonstrate the concept, we developed the "The Emotional Labyrinth," a non-linear scenario in which navigation in a procedurally generated three-dimensional maze is entirely decided by the user, and whose features are dynamically adapted according to a set of emotional states. During navigation, affective states are dynamically represented through pictures, music, and animated visual metaphors chosen to represent and induce affective states. The underlying hypothesis is that exposing users to multimodal representations of their affective states can create a feedback loop that supports emotional self-awareness and fosters more effective emotional regulation strategies. We carried out a first study to, first, assess the effectiveness of the selected metaphors in inducing target emotions, and second, identify relevant psycho-physiological markers of the emotional experience generated by the labyrinth. Results show that the Emotional Labyrinth is overall a pleasant experience in which the proposed procedural content generation can induce distinctive psycho-physiological patterns, generally coherent with the meaning of the metaphors used in the labyrinth design. Furthermore, collected psycho-physiological responses such as electrocardiography, respiration, electrodermal activity, and electromyography are used to generate computational models of users' reported experience. These models enable the future implementation of the closed loop mechanism to adapt the Labyrinth procedurally to the users' affective state.

Capturing Expert Knowledge for the Personalization of Cognitive Rehabilitation: Study Combining Computational Modeling and a Participatory Design Strategy.

BACKGROUND: Cognitive impairments after stroke are not always given sufficient attention despite the critical limitations they impose on activities of daily living (ADLs). Although there is substantial evidence on cognitive rehabilitation benefits, its implementation is limited because of time and human resource's demands. Moreover, many cognitive rehabilitation interventions lack a robust theoretical framework in the selection of paper-and-pencil tasks by the clinicians. In this endeavor, it would be useful to have a tool that could generate standardized paper-and-pencil tasks, parameterized according to patients' needs. OBJECTIVE: In this study, we aimed to present a framework for the creation of personalized cognitive rehabilitation tasks based on a participatory design strategy. METHODS: We selected 11 paper-and-pencil tasks from standard clinical practice and parameterized them with multiple configurations. A total of 67 tasks were assessed according to their cognitive demands (attention, memory, language, and executive functions) and overall difficulty by 20 rehabilitation professionals. RESULTS: After assessing the internal consistency of the data-that is, alpha values from .918 to .997-we identified the parameters that significantly affected cognitive functions and proposed specific models for each task. Through computational modeling, we operationalized the tasks into their intrinsic parameters and developed a Web tool that generates personalized paper-and-pencil tasks-the Task Generator (TG). CONCLUSIONS: Our framework proposes an objective and quantitative personalization strategy tailored to each patient in multiple cognitive domains (attention, memory, language, and executive functions) derived from expert knowledge and materialized in the TG app, a cognitive rehabilitation Web tool.

Combined Cognitive-Motor Rehabilitation in Virtual Reality Improves Motor Outcomes in Chronic Stroke - A Pilot Study.

Stroke is one of the most common causes of acquired disability, leaving numerous adults with cognitive and motor impairments, and affecting patients' capability to live independently. Virtual Reality (VR) based methods for stroke rehabilitation have mainly focused on motor rehabilitation but there is increasing interest toward the integration of cognitive training for providing more effective solutions. Here we investigate the feasibility for stroke recovery of a virtual cognitive-motor task, the Reh@Task, which combines adapted arm reaching, and attention and memory training. 24 participants in the chronic stage of stroke, with cognitive and motor deficits, were allocated to one of two groups (VR, Control). Both groups were enrolled in conventional occupational therapy, which mostly involves motor training. Additionally, the VR group underwent training with the Reh@Task and the control group performed time-matched conventional occupational therapy. Motor and cognitive competences were assessed at baseline, end of treatment (1 month) and at a 1-month follow-up through the Montreal Cognitive Assessment, Single Letter Cancelation, Digit Cancelation, Bells Test, Fugl-Meyer Assessment Test, Chedoke Arm and Hand Activity Inventory, Modified Ashworth Scale, and Barthel Index. Our results show that both groups improved in motor function over time, but the Reh@Task group displayed significantly higher between-group outcomes in the arm subpart of the Fugl-Meyer Assessment Test. Improvements in cognitive function were significant and similar in both groups. Overall, these results are supportive of the viability of VR tools that combine motor and cognitive training, such as the Reh@Task. Trial Registration: This trial was not registered because it is a small clinical study that addresses the feasibility of a prototype device.

Motor priming in virtual reality can augment motor-imagery training efficacy in restorative brain-computer interaction: a within-subject analysis.

BACKGROUND: The use of Brain-Computer Interface (BCI) technology in neurorehabilitation provides new strategies to overcome stroke-related motor limitations. Recent studies demonstrated the brain's capacity for functional and structural plasticity through BCI. However, it is not fully clear how we can take full advantage of the neurobiological mechanisms underlying recovery and how to maximize restoration through BCI. In this study we investigate the role of multimodal virtual reality (VR) simulations and motor priming (MP) in an upper limb motor-imagery BCI task in order to maximize the engagement of sensory-motor networks in a broad range of patients who can benefit from virtual rehabilitation training. METHODS: In order to investigate how different BCI paradigms impact brain activation, we designed 3 experimental conditions in a within-subject design, including an immersive Multimodal Virtual Reality with Motor Priming (VRMP) condition where users had to perform motor-execution before BCI training, an immersive Multimodal VR condition, and a control condition with standard 2D feedback. Further, these were also compared to overt motor-execution. Finally, a set of questionnaires were used to gather subjective data on Workload, Kinesthetic Imagery and Presence. RESULTS: Our findings show increased capacity to modulate and enhance brain activity patterns in all extracted EEG rhythms matching more closely those present during motor-execution and also a strong relationship between electrophysiological data and subjective experience. CONCLUSIONS: Our data suggest that both VR and particularly MP can enhance the activation of brain patterns present during overt motor-execution. Further, we show changes in the interhemispheric EEG balance, which might play an important role in the promotion of neural activation and neuroplastic changes in stroke patients in a motor-imagery neurofeedback paradigm. In addition, electrophysiological correlates of psychophysiological responses provide us with valuable information about the motor and affective state of the user that has the potential to be used to predict MI-BCI training outcome based on user's profile. Finally, we propose a BCI paradigm in VR, which gives the possibility of motor priming for patients with low level of motor control.

The impact of positive, negative and neutral stimuli in a virtual reality cognitive-motor rehabilitation task: a pilot study with stroke patients.

BACKGROUND: Virtual Reality (VR) based methods for stroke rehabilitation have mainly focused on motor rehabilitation, but there is increasing interest in integrating motor and cognitive training to increase similarity to real-world settings. Unfortunately, more research is needed for the definition of which type of content should be used in the design of these tools. One possibility is the use of emotional stimuli, which are known to enhance attentional processes. According to the Socioemotional Selectivity Theory, as people age, the emotional salience arises for positive and neutral, but not for negative stimuli. METHODS: For this study we developed a cognitive-motor VR task involving attention and short-term memory, and we investigated the impact of using emotional images of varying valence. The task consisted of finding a target image, shown for only two seconds, among fourteen neutral distractors, and selecting it through arm movements. After performing the VR task, a recall task took place and the patients had to identify the target images among a valence-matched number of distractors. Ten stroke patients participated in a within-subjects experiment with three conditions based on the valence of the images: positive, negative and neutral. Eye movements were recorded during VR task performance with an eye tracking system. RESULTS: Our results show decreased attention for negative stimuli in the VR task performance when compared to neutral stimuli. The recall task shows significantly more wrongly identified images (false memories) for negative stimuli than for neutral. Regression and correlation analyses with the Montreal Cognitive Assessment and the Geriatric Depression Scale revealed differential effects of cognitive function and depressive symptomatology in the encoding and recall of positive, negative and neutral images. Further, eye movement data shows reduced search patterns for wrongly selected stimuli containing emotional content. CONCLUSIONS: The results of this study suggest that it is feasible to use emotional content in a VR based cognitive-motor task for attention and memory training after stroke. Stroke survivors showed less attention towards negative information, exhibiting reduced visual search patterns and more false memories. We have also shown that the use of emotional stimuli in a VR task can provide additional information regarding patient's mood and cognitive status.