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- NeuRow: an immersive VR environment for motor-imagery training with the use of brain-computer interfaces and vibrotactile feedbackPublication . Bermúdez i Badia, Sergi; Ferreira, André; Vourvopoulos, AthanasiosMotor-Imagery offers a solid foundation for the development of Brain-Computer Interfaces (BCIs), capable of direct brain-to-computer communication but also effective in alleviating neurological impairments. The fusion of BCIs with Virtual Reality (VR) allowed the enhancement of the field of virtual rehabilitation by including patients with low-level of motor control with limited access to treatment. BCI-VR technology has pushed research towards finding new solutions for better and reliable BCI control. Based on our previous work, we have developed NeuRow, a novel multiplatform prototype that makes use of multimodal feedback in an immersive VR environment delivered through a state-of-the-art Head Mounted Display (HMD). In this article we present the system design and development, including important features for creating a closed neurofeedback loop in an implicit manner, and preliminary data on user performance and user acceptance of the system.
- Eye gaze patterns after stroke: correlates of a VR action execution and observation taskPublication . Alves, Júlio; Vourvopoulos, Athanasios; Bernardino, Alexandre; Bermúdez i Badia, SergiThe concept of a partially shared neural circuitry between action observation and action execution in healthy participants has been demonstrated through a number of studies. However, little research has been done in this regard utilizing eye movement metrics in rehabilitation contexts.In this study we approach action observation and action execution by combining a virtual environment and eye tracking technology. Participants consisted of stroke survivors, and were required to perform a simple reachand-grab and place-and-release task with both their paretic and non-paretic arm. Results showed congruency in gaze metrics between action execution and action observation, for distribution and duration of gaze events. Furthermore, in action observation, longer smooth pursuit segments were detected when observing the representation of the paretic arm, thus providing evidence that the affected circuitry may be activated during observation of the simulated action. These results can lead to novel rehabilitation methods using virtual reality technology.
- An assistive mobile platform for delivering knowledge of performance feedbackPublication . Neves, Davide; Vourvopoulos, Athanasios; Cameirão, Mónica S.; Bermúdez i Badia, SergiUpper limb motor deficits caused by stroke have a big impact on a person’s daily activities and independence. One strategy for promoting motor relearning consists on the delivery of meaningful feedback during rehabilitative training. In this paper we describe the development and first evaluation of a system that combines a portable arm orthosis device and a mobile application running on a tablet in order to provide knowledge of performance to stroke patients while performing therapy. Here we present preliminary results and discuss the potential of this technology.
- Impact of age, VR, immersion, and spatial resolution on classifier performance for a MI-based BCIPublication . Blanco-Mora, D. A.; Aldridge, A.; Jorge, C.; Vourvopoulos, A.; Figueiredo, P.; Bermúdez i Badia, S.There are many factors outlined in the signal processing pipeline that impact brain–computer interface (BCI) performance, but some methodological factors do not depend on signal processing. Nevertheless, there is a lack of research assessing the effect of such factors. Here, we investigate the impact of VR, immersiveness, age, and spatial resolution on the classifier performance of a Motor Imagery (MI) electroencephalography (EEG)-based BCI in naïve participants. We found significantly better performance for VR compared to non-VR (15 electrodes: VR 77.48 ± 6.09%, non-VR 73.5 ± 5.89%, p = 0.0096; 12 electrodes: VR 73.26 ± 5.2%, non-VR 70.87 ± 4.96%, p = 0.0129; 7 electrodes: VR 66.74 ± 5.92%, non-VR 63.09 ± 8.16%, p = 0.0362) and better performance for higher electrode quantity, but no significant differences were found between immersive and non immersive VR. Finally, there was not a statistically significant correlation found between age and classifier performance, but there was a direct relation found between spatial resolution (electrode quantity) and classifier performance (r = 1, p = 0.0129, VR; r = 0.99, p = 0.0859, non-VR).
- EEG correlates of video game experience and user profile in motor-imagery-based brain–computer interactionPublication . Vourvopoulos, Athanasios; Bermúdez i Badia, Sergi; Liarokapis, FotisThrough the use of brain–computer interfaces (BCIs), neurogames have become increasingly more advanced by incorporating immersive virtual environments and 3D worlds. However, training both the user and the systemrequireslongandrepetitivetrialsresultinginfatigueand lowperformance.Moreover,manyusersareunabletovoluntarilymodulatetheamplitudeoftheirbrainactivitytocontrol theneurofeedbackloop.Inthisstudy,wearefocusingonthe effect that gaming experience has in brain activity modulation as an attempt to systematically identify the elements that contribute to high BCI control and to be utilized in neurogamedesign.Basedonthecurrentliterature,wearguethat experienced gamers could have better performance in BCI trainingduetoenhancedsensorimotorlearningderivedfrom gaming. To investigate this, two experimental studies were conducted with 20 participants overall, undergoing 3 BCI sessions,resultingin88EEGdatasets.Resultsindicate(a)an effectfrombothdemographicandgamingexperiencedatato theactivitypatternsofEEGrhythms,and(b)increasedgamingexperiencemightnotincreasesignificantlyperformance, but it could provide faster learning for ‘Hardcore’ gamers.
- RehabNet: a distributed architecture for motor and cognitive neuro-rehabilitationPublication . Vourvopoulos, Athanasios; Faria, Ana Lúcia; Cameirão, Mónica S.; Bermúdez i Badia, SergiEvery year millions of people worldwide suffer from stroke, resulting in motor and/or cognitive disability. As a result, patients experience an increased loss of independence, autonomy and low self-esteem. Evolving to a chronic condition, stroke requires of continuous rehabilitation and therapy. Current ICT approaches, with the use of robotics and Virtual Reality, show some benefits over conventional therapy. However, most of the novel approaches are suitable only for a reduced subset of patients. RehabNet proposes an inclusive approach towards an open and distributed architecture for ‘in-home’ neurorehabilitation and monitoring by means of non-invasive ICT. In this paper we present the RehabNet architecture, its design and the implementation of a combined motor-and-cognitive system for post-stroke rehabilitation.
- Motor priming in virtual reality can augment motor-imagery training efficacy in restorative brain-computer interaction: a within-subject analysisPublication . Vourvopoulos, Athanasios; Bermúdez i Badia, SergiThe 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.
- Development and assessment of a self-paced BCI-VR paradigm using multimodal stimulation and adaptive performancePublication . Vourvopoulos, Athanasios; Ferreira, André; Bermúdez i Badia, SergiMotor-Imagery based Brain-Computer Interfaces (BCIs) can provide alternative communication pathways to neurologically impaired patients. The combination of BCIs and Virtual Reality (VR) can provide induced illusions of movement to patients with low-level of motor control during motor rehabilitation tasks. Unfortunately, current BCI systems lack reliability and good performance levels in comparison with other types of computer interfaces. To date, there is little evidence on how BCI-based motor training needs to be designed for transferring rehabilitation improvements to real life. Based on our previous work, we showcase the development and assessment of NeuRow, a novel multiplatform immersive VR environment that makes use of multimodal stimulation through vision, sound and vibrotactile feedback and delivered through a VR Head Mounted Display. In addition, we integrated the Adaptive Performance Engine (APE), a statistical approach to optimize user control in a selfpaced BCI-VR paradigm. In this paper, we describe the development and pilot assessment of NeuRow as well as its integration and assessment with APE.
- Optimizing performance of non-expert users in brain-computer interaction by means of an adaptive performance enginePublication . Ferreira, André; Vourvopoulos, Athanasios; Bermúdez i Badia, SergiBrain–Computer Interfaces (BCIs) are become increasingly more available at reduced costs and are being incorporated into immersive virtual environments and video games for serious applications. Most research in BCIs focused on signal processing techniques and has neglected the interaction aspect of BCIs. This has created an imbalance between BCI classification performance and online control quality of the BCI interaction. This results in user fatigue and loss of interest over time. In the health domain, BCIs provide a new way to overcome motor-related disabilities, promoting functional and structural plasticity in the brain. In order to exploit the advantages of BCIs in neurorehabilitation we need to maximize not only the classification performance of such systems but also engagement and the sense of competence of the user. Therefore, we argue that the primary goal should not be for users to be trained to successfully use a BCI system but to adapt the BCI interaction to each user in order to maximize the level of control on their actions, whatever their performance level is. To achieve this, we developed the Adaptive Performance Engine (APE) and tested with data from 20 naïve BCI users. APE can provide user specific performance improvements up to approx. 20% and we compare it with previous methods. Finally, we contribute with an open motor-imagery datasets with 2400 trials from naïve users.
- Clinical effects of immersive multimodal BCI-VR training after bilateral neuromodulation with rTMS on upper limb motor recovery after stroke. a study protocol for a randomized controlled trialPublication . Sánchez Cuesta, Francisco José; Arroyo-Ferrer, Aida; González-Zamorano, Yeray; Vourvopoulos, Athanasios; Bermúdez i Badia, Sergi; Figueiredo, Patricia; Serrano, José Ignacio; Romero, Juan PabloThe motor sequelae after a stroke are frequently persistent and cause a high degree of disability. Cortical ischemic or hemorrhagic strokes affecting the cortico spinal pathways are known to cause a reduction of cortical excitability in the lesioned area not only for the local connectivity impairment but also due to a contralateral hemisphere inhibitory action. Non-invasive brain stimulation using high frequency repetitive magnetic transcranial stimulation (rTMS) over the lesioned hemisphere and contralateral cortical inhibition using low-frequency rTMS have been shown to increase the excitability of the lesioned hemisphere. Mental representation techniques, neurofeedback, and virtual reality have also been shown to increase cortical excitability and complement conventional rehabilitation. Materials and Methods: We aim to carry out a single-blind, randomized, controlled trial aiming to study the efficacy of immersive multimodal Brain–Computer Interfacing-Virtual Reality (BCI-VR) training after bilateral neuromodulation with rTMS on upper limb motor recovery after subacute stroke (>3 months) compared to neuromodulation combined with conventional motor imagery tasks. This study will include 42 subjects in a randomized controlled trial design. The main expected outcomes are changes in the Motricity Index of the Arm (MI), dynamometry of the upper limb, score according to Fugl-Meyer for upper limb (FMA-UE), and changes in the Stroke Impact Scale (SIS). The evaluation will be carried out before the intervention, after each intervention and 15 days after the last session. Conclusions: This trial will show the additive value of VR immersive motor imagery as an adjuvant therapy combined with a known effective neuromodulation approach opening new perspectives for clinical rehabilitation protocols.